[
  {
    "path": ".gitignore",
    "content": "# Created by .ignore support plugin (hsz.mobi)\n### Python template\n# Byte-compiled / optimized / DLL files\n__pycache__/\n*.py[cod]\n*$py.class\n\n# C extensions\n*.so\n\n# Distribution / packaging\n.Python\nbuild/\ndevelop-eggs/\ndist/\ndownloads/\neggs/\n.eggs/\nlib/\nlib64/\nparts/\nsdist/\nvar/\nwheels/\npip-wheel-metadata/\nshare/python-wheels/\n*.egg-info/\n.installed.cfg\n*.egg\nMANIFEST\n\n# PyInstaller\n#  Usually these files are written by a python script from a template\n#  before PyInstaller builds the exe, so as to inject date/other infos into it.\n*.manifest\n*.spec\n\n# Installer logs\npip-log.txt\npip-delete-this-directory.txt\n\n# Unit test / coverage reports\nhtmlcov/\n.tox/\n.nox/\n.coverage\n.coverage.*\n.cache\nnosetests.xml\ncoverage.xml\n*.cover\n.hypothesis/\n.pytest_cache/\n\n# Translations\n*.mo\n*.pot\n\n# Django stuff:\n*.log\nlocal_settings.py\ndb.sqlite3\ndb.sqlite3-journal\n\n# Flask stuff:\ninstance/\n.webassets-cache\n\n# Scrapy stuff:\n.scrapy\n\n# Sphinx documentation\ndocs/_build/\n\n# PyBuilder\ntarget/\n\n# Jupyter Notebook\n.ipynb_checkpoints\n\n# IPython\nprofile_default/\nipython_config.py\n\n# pyenv\n.python-version\n\n# pipenv\n#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.\n#   However, in case of collaboration, if having platform-specific dependencies or dependencies\n#   having no cross-platform support, pipenv may install dependencies that don't work, or not\n#   install all needed dependencies.\n#Pipfile.lock\n\n# celery beat schedule file\ncelerybeat-schedule\n\n# SageMath parsed files\n*.sage.py\n\n# Environments\n.env\n.venv\nenv/\nvenv/\nENV/\nenv.bak/\nvenv.bak/\n\n# Spyder project settings\n.spyderproject\n.spyproject\n\n# Rope project settings\n.ropeproject\n\n# mkdocs documentation\n/site\n\n# mypy\n.mypy_cache/\n.dmypy.json\ndmypy.json\n\n# Pyre type checker\n.pyre/\n\n### JetBrains template\n# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and WebStorm\n# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839\n\n# User-specific stuff\n.idea/**/workspace.xml\n.idea/**/tasks.xml\n.idea/**/usage.statistics.xml\n.idea/**/dictionaries\n.idea/**/shelf\n\n# Generated files\n.idea/**/contentModel.xml\n\n# Sensitive or high-churn files\n.idea/**/dataSources/\n.idea/**/dataSources.ids\n.idea/**/dataSources.local.xml\n.idea/**/sqlDataSources.xml\n.idea/**/dynamic.xml\n.idea/**/uiDesigner.xml\n.idea/**/dbnavigator.xml\n\n# Gradle\n.idea/**/gradle.xml\n.idea/**/libraries\n\n# Gradle and Maven with auto-import\n# When using Gradle or Maven with auto-import, you should exclude module files,\n# since they will be recreated, and may cause churn.  Uncomment if using\n# auto-import.\n# .idea/modules.xml\n# .idea/*.iml\n# .idea/modules\n# *.iml\n# *.ipr\n\n# CMake\ncmake-build-*/\n\n# Mongo Explorer plugin\n.idea/**/mongoSettings.xml\n\n# File-based project format\n*.iws\n\n# IntelliJ\nout/\n\n# mpeltonen/sbt-idea plugin\n.idea_modules/\n\n# JIRA plugin\natlassian-ide-plugin.xml\n\n# Cursive Clojure plugin\n.idea/replstate.xml\n\n# Crashlytics plugin (for Android Studio and IntelliJ)\ncom_crashlytics_export_strings.xml\ncrashlytics.properties\ncrashlytics-build.properties\nfabric.properties\n\n# Editor-based Rest Client\n.idea/httpRequests\n\n# Android studio 3.1+ serialized cache file\n.idea/caches/build_file_checksums.ser\n\n# OSX\n#\n.DS_Store\n"
  },
  {
    "path": ".idea/.gitignore",
    "content": "# Default ignored files\n/shelf/\n/workspace.xml\n# Datasource local storage ignored files\n/dataSources/\n/dataSources.local.xml\n# Editor-based HTTP Client requests\n/httpRequests/\n"
  },
  {
    "path": ".idea/NewsMTSC.iml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<module type=\"JAVA_MODULE\" version=\"4\">\n  <component name=\"NewModuleRootManager\" inherit-compiler-output=\"true\">\n    <exclude-output />\n    <content url=\"file://$MODULE_DIR$\">\n      <excludeFolder url=\"file://$MODULE_DIR$/NewsSentiment.egg-info\" />\n      <excludeFolder url=\"file://$MODULE_DIR$/dist\" />\n    </content>\n    <orderEntry type=\"jdk\" jdkName=\"Python 3.7 (newsmtsc)\" jdkType=\"Python SDK\" />\n    <orderEntry type=\"sourceFolder\" forTests=\"false\" />\n  </component>\n</module>"
  },
  {
    "path": ".idea/misc.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<project version=\"4\">\n  <component name=\"PhpWorkspaceProjectConfiguration\" backward_compatibility_performed=\"true\" />\n  <component name=\"ProjectRootManager\">\n    <output url=\"file://$PROJECT_DIR$/out\" />\n  </component>\n</project>"
  },
  {
    "path": ".idea/modules.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<project version=\"4\">\n  <component name=\"ProjectModuleManager\">\n    <modules>\n      <module fileurl=\"file://$PROJECT_DIR$/.idea/NewsMTSC.iml\" filepath=\"$PROJECT_DIR$/.idea/NewsMTSC.iml\" />\n    </modules>\n  </component>\n</project>"
  },
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    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<project version=\"4\">\n  <component name=\"VcsDirectoryMappings\">\n    <mapping directory=\"\" vcs=\"Git\" />\n  </component>\n</project>"
  },
  {
    "path": "CODE_OF_CONDUCT.md",
    "content": "# Contributor Covenant Code of Conduct\n\n## Our Pledge\n\nIn the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.\n\n## Our Standards\n\nExamples of behavior that contributes to creating a positive environment include:\n\n* Using welcoming and inclusive language\n* Being respectful of differing viewpoints and experiences\n* Gracefully accepting constructive criticism\n* Focusing on what is best for the community\n* Showing empathy towards other community members\n\nExamples of unacceptable behavior by participants include:\n\n* The use of sexualized language or imagery and unwelcome sexual attention or advances\n* Trolling, insulting/derogatory comments, and personal or political attacks\n* Public or private harassment\n* Publishing others' private information, such as a physical or electronic address, without explicit permission\n* Other conduct which could reasonably be considered inappropriate in a professional setting\n\n## Our Responsibilities\n\nProject maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.\n\nProject maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.\n\n## Scope\n\nThis Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.\n\n## Enforcement\n\nInstances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at felix.hamborg@uni-konstanz.de. The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.\n\nProject maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership.\n\n## Attribution\n\nThis Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at [http://contributor-covenant.org/version/1/4][version]\n\n[homepage]: http://contributor-covenant.org\n[version]: http://contributor-covenant.org/version/1/4/\n"
  },
  {
    "path": "LICENSE",
    "content": "This project uses code from various projects, who may have their own license or copyright.\n- ABSA-PyTorch by Yury Soong et al., available at https://github.com/songyouwei/ABSA-PyTorch\n- early-stopping-pytorch by Bjarten, available at https://github.com/Bjarten/early-stopping-pytorch\n\nFor newly developed files, the license information is:\n\nCopyright 2020 Felix Hamborg\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n"
  },
  {
    "path": "MANIFEST.in",
    "content": "include READMEpypi.md\ninclude pythoninfo.md\n"
  },
  {
    "path": "NewsSentiment/.gitignore",
    "content": ""
  },
  {
    "path": "NewsSentiment/DatasetPreparer.py",
    "content": "\"\"\"\nUsed by controller.py to prepare datasets for an experiment, thereby most importantly considering whether the experiment\nuses cross validation or not.\n\nCurrently, the class is partially hard coded for the poltsanews dataset.\n\"\"\"\nimport math\nimport os\nimport random\nfrom collections import Counter\nfrom shutil import copyfile\n\nimport jsonlines\nfrom tabulate import tabulate\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\nfrom NewsSentiment.fxlogger import get_logger\n\n\nclass DatasetPreparer:\n    def __init__(self, name, basepath_datasets, task_format, human, non_human):\n        # only used for newsmtsc format\n        SentimentClasses.Sentiment3ForNewsMtsc()\n        self.basepath_datasets = basepath_datasets\n        self.name = name\n        self.human_created_filenames = human\n        self.non_human_created_filenames = non_human\n        self.human_created_filepaths = [\n            self.get_filepath_by_name(x) for x in self.human_created_filenames\n        ]\n        self.non_human_created_filepaths = [\n            self.get_filepath_by_name(x) for x in self.non_human_created_filenames\n        ]\n        self.data_types = [\"human\", \"nonhum\"]\n\n        self.sets_info = None\n\n        self.random_seed = 1337\n        random.seed(self.random_seed)\n        self.logger = get_logger()\n\n        self.examples_human = self.files_to_dictlst(self.human_created_filepaths)\n        self.examples_nonhum = self.files_to_dictlst(self.non_human_created_filepaths)\n\n        self.task_format = task_format\n\n        self.logger.info(\n            \"shuffling example lists with seed {}\".format(self.random_seed)\n        )\n        random.shuffle(self.examples_human)\n        random.shuffle(self.examples_nonhum)\n\n        self.logger.info(\n            \"{} examples read created by humans (from: {})\".format(\n                len(self.examples_human), self.human_created_filepaths\n            )\n        )\n        self.logger.info(\n            \"{} examples read not created by humans (from: {})\".format(\n                len(self.examples_nonhum), self.non_human_created_filepaths\n            )\n        )\n\n    def get_filepath_by_name(self, filename):\n        return os.path.join(self.basepath_datasets, self.name, filename)\n\n    def file_to_dictlst(self, filepath):\n        dict_lst = []\n        with jsonlines.open(filepath, \"r\") as reader:\n            for line in reader:\n                dict_lst.append(line)\n        self.logger.debug(\"{} examples read from {}\".format(len(dict_lst), filepath))\n        return dict_lst\n\n    def files_to_dictlst(self, list_filepaths):\n        dict_lst = []\n        for filepath in list_filepaths:\n            dict_lst.extend(self.file_to_dictlst(filepath))\n        return dict_lst\n\n    def create_slices(self, data_type):\n        \"\"\"\n\n        :param sets_info:\n        :param data_type: 'human', 'nonhum'\n        :return:\n        \"\"\"\n        set_names = list(self.sets_info.keys())\n        assert data_type in self.data_types\n\n        # get some vars\n        _id_relative_weight = \"{}-rel-weight\".format(data_type)\n        _id_examples = \"{}-examples\".format(data_type)\n\n        prev_split_pos = 0\n        for set_index, set_name in enumerate(set_names):\n            cur_setinfo = self.sets_info[set_name]\n\n            if _id_relative_weight in cur_setinfo:\n                cur_relative_weight = cur_setinfo[_id_relative_weight]\n\n                if cur_relative_weight:\n                    split_pos = prev_split_pos + math.floor(\n                        cur_relative_weight * len(self.examples_human)\n                    )\n                    if set_index == len(set_names) - 1:\n                        # just to be sure to not miss a single example because of rounding\n                        split_pos = len(self.examples_human)\n\n                    example_slice = self.examples_human[prev_split_pos:split_pos]\n                    cur_setinfo[_id_examples] = example_slice\n                    self.logger.info(\n                        \"{}: added {} {} examples ({:.2f})\".format(\n                            set_name, len(example_slice), data_type, cur_relative_weight\n                        )\n                    )\n\n                    prev_split_pos = split_pos\n                else:\n                    cur_setinfo[_id_examples] = []\n\n    def merge_slices(self):\n        total_examples_count = 0\n        for set_name, cur_set in self.sets_info.items():\n            cur_merged_data = []\n            for data_type in self.data_types:\n                _id_examples = \"{}-examples\".format(data_type)\n\n                if _id_examples in cur_set:\n                    cur_merged_data.extend(cur_set[_id_examples])\n\n            cur_set[\"examples\"] = cur_merged_data\n            total_examples_count += len(cur_merged_data)\n\n        for set_name, cur_set in self.sets_info.items():\n            cur_set[\"examples-rel\"] = len(cur_set[\"examples\"]) / total_examples_count\n\n    def _get_label_counts(self, tasks):\n        label_counts = Counter()\n        if self.task_format == \"newsmtsc\":\n            for task in tasks:\n                assert len(task[\"targets\"]) >= 1, f\"no target in task: {task}\"\n                for target in task[\"targets\"]:\n                    label = SentimentClasses.polarity2label(target[\"polarity\"])\n                    label_counts[label] += 1\n        elif self.task_format == \"newstsc\":\n            for task in tasks:\n                label_counts[task[\"label\"]] += 1\n        else:\n            raise NotImplementedError(f\"unknown data format. {self.task_format}\")\n        return dict(label_counts)\n\n    def print_set_info(self):\n        header = [\n            \"set_name\",\n            \"human rel\",\n            \"human abs\",\n            \"non-hum rel\",\n            \"non-hum abs\",\n            \"rel\",\n            \"abs\",\n            \"pos\",\n            \"neu\",\n            \"neg\",\n        ]\n        rows = []\n        for set_name, cur_set in self.sets_info.items():\n            if \"file\" in cur_set:\n                num_lines = sum(\n                    1 for line in open(self.get_filepath_by_name(cur_set[\"file\"]), encoding=\"utf8\")\n                )\n                row = [set_name, -1, -1, -1, -1, cur_set[\"file\"], num_lines, -1, -1, -1]\n            else:\n                label_counts = self._get_label_counts(\n                    [*(cur_set[\"human-examples\"]), *(cur_set[\"nonhum-examples\"])]\n                )\n                row = [\n                    set_name,\n                    cur_set[\"human-rel-weight\"],\n                    len(cur_set[\"human-examples\"]),\n                    cur_set[\"nonhum-rel-weight\"],\n                    len(cur_set[\"nonhum-examples\"]),\n                    cur_set[\"examples-rel\"],\n                    len(cur_set[\"examples\"]),\n                    label_counts[\"positive\"],\n                    label_counts[\"neutral\"],\n                    label_counts[\"negative\"],\n                ]\n            rows.append(row)\n\n        self.logger.info(\"\\n\" + tabulate(rows, header))\n\n    def init_set(self, sets_info):\n        self.sets_info = sets_info\n\n        set_names = list(self.sets_info.keys())\n\n        weights_human = Counter()\n        weights_nonhum = Counter()\n        nonnull_set_names = []\n        self.filecopy_sets = {}\n\n        # sum weights and thereby filter datasets that are 0 in size\n        for set_name in set_names:\n            setinfo = self.sets_info[set_name]\n\n            if \"file\" in setinfo:\n                self.filecopy_sets[set_name] = setinfo[\"file\"]\n            else:\n                weights_human[set_name] = setinfo[\"human-weight\"]\n                weights_nonhum[set_name] = setinfo[\"nonhum-weight\"]\n\n                if setinfo[\"human-weight\"] + setinfo[\"nonhum-weight\"] > 0:\n                    nonnull_set_names.append(set_name)\n                else:\n                    self.logger.info(\n                        \"discard {}, because would be empty\".format(set_name)\n                    )\n        set_names = nonnull_set_names\n\n        human_weight_sum = sum(weights_human.values())\n        nonhuman_weight_sum = sum(weights_nonhum.values())\n\n        # add relative weights\n        for set_name in set_names:\n            cur_setinfo = self.sets_info[set_name]\n            if cur_setinfo[\"human-weight\"]:\n                cur_setinfo[\"human-rel-weight\"] = (\n                    cur_setinfo[\"human-weight\"] / human_weight_sum\n                )\n            else:\n                cur_setinfo[\"human-rel-weight\"] = 0\n            if cur_setinfo[\"nonhum-weight\"]:\n                cur_setinfo[\"nonhum-rel-weight\"] = (\n                    cur_setinfo[\"nonhum-weight\"] / nonhuman_weight_sum\n                )\n            else:\n                cur_setinfo[\"nonhum-rel-weight\"] = 0\n        # at this point, setsinfo contains only positive (non-0) relative weights (or no such key, if the abs. pad_value was 0, too)\n\n        # create slices\n        self.create_slices(\"human\")\n        self.create_slices(\"nonhum\")\n\n        # merge human and non human sets in each set\n        self.merge_slices()\n\n        self.print_set_info()\n\n    def export(self, savepath):\n        for set_name, cur_set in self.sets_info.items():\n            if \"file\" not in cur_set:\n                set_savefolder = os.path.join(savepath, self.name)\n                os.makedirs(set_savefolder, exist_ok=True)\n                set_savepath = os.path.join(set_savefolder, set_name + \".jsonl\")\n\n                with jsonlines.open(set_savepath, \"w\") as writer:\n                    writer.write_all(cur_set[\"examples\"])\n                self.logger.debug(\n                    \"created set (abs={}) at {}\".format(\n                        len(cur_set[\"examples\"]), set_savepath\n                    )\n                )\n\n        for set_name, filename in self.filecopy_sets.items():\n            set_savefolder = os.path.join(savepath, self.name)\n            os.makedirs(set_savefolder, exist_ok=True)\n            set_savepath = os.path.join(set_savefolder, set_name + \".jsonl\")\n            set_sourcepath = self.get_filepath_by_name(filename)\n\n            copyfile(set_sourcepath, set_savepath)\n            self.logger.debug(\"copied set to {}\".format(set_savepath))\n\n    @classmethod\n    def poltsanews_rel801010_allhuman(cls, basepath):\n        name = \"poltsanews\"\n        task_format = \"newstsc_old\"\n        human_created_filenames = [\"human.jsonl\"]\n        non_human_created_filenames = [\"train_20191021_233454.jsonl\"]\n\n        dprep = cls(\n            name,\n            basepath,\n            task_format,\n            human_created_filenames,\n            non_human_created_filenames,\n        )\n\n        sets_info = {\n            \"train\": {\"human-weight\": 80, \"nonhum-weight\": 0},\n            \"dev\": {\"human-weight\": 10, \"nonhum-weight\": 0},\n            \"test\": {\"human-weight\": 10, \"nonhum-weight\": 0},\n        }\n\n        dprep.init_set(sets_info)\n        return dprep, name, task_format\n\n    @classmethod\n    def poltsanews_crossval8010_allhuman(cls, basepath):\n        name = \"poltsanews\"\n        task_format = \"newstsc_old\"\n        human_created_filenames = [\"human.jsonl\"]\n        non_human_created_filenames = [\"train_20191021_233454.jsonl\"]\n\n        dprep = cls(\n            name,\n            basepath,\n            task_format,\n            human_created_filenames,\n            non_human_created_filenames,\n        )\n\n        sets_info = {\n            \"crossval\": {\"human-weight\": 80, \"nonhum-weight\": 0},\n            \"test\": {\"human-weight\": 10, \"nonhum-weight\": 0},\n        }\n\n        dprep.init_set(sets_info)\n        return dprep, name, task_format\n\n    @classmethod\n    def acl14twitter(cls, basepath):\n        name = \"acl14twitter\"\n        task_format = \"newsmtsc\"\n        human_created_filenames = [\"train.raw.jsonl\"]\n        non_human_created_filenames = []\n\n        dprep = cls(\n            name,\n            basepath,\n            task_format,\n            human_created_filenames,\n            non_human_created_filenames,\n        )\n\n        sets_info = {\n            \"train\": {\"human-weight\": 80, \"nonhum-weight\": 0},\n            \"dev\": {\"human-weight\": 10, \"nonhum-weight\": 0},\n            \"test\": {\"file\": \"test.raw.jsonl\"},\n        }\n\n        dprep.init_set(sets_info)\n        return dprep, name, task_format\n\n    @classmethod\n    def semeval14laptops(cls, basepath):\n        name = \"semeval14laptops\"\n        task_format = \"newsmtsc\"\n        human_created_filenames = [\"Laptops_Train.xml.seg.jsonl\"]\n        non_human_created_filenames = []\n\n        dprep = cls(\n            name,\n            basepath,\n            task_format,\n            human_created_filenames,\n            non_human_created_filenames,\n        )\n\n        sets_info = {\n            \"train\": {\"human-weight\": 80, \"nonhum-weight\": 0},\n            \"dev\": {\"human-weight\": 10, \"nonhum-weight\": 0},\n            \"test\": {\"file\": \"Laptops_Test_Gold.xml.seg.jsonl\"},\n        }\n\n        dprep.init_set(sets_info)\n        return dprep, name, task_format\n\n    @classmethod\n    def semeval14restaurants(cls, basepath):\n        name = \"semeval14restaurants\"\n        task_format = \"newsmtsc\"\n        human_created_filenames = [\"Restaurants_Train.xml.seg.jsonl\"]\n        non_human_created_filenames = []\n\n        dprep = cls(\n            name,\n            basepath,\n            task_format,\n            human_created_filenames,\n            non_human_created_filenames,\n        )\n\n        sets_info = {\n            \"train\": {\"human-weight\": 80, \"nonhum-weight\": 0},\n            \"dev\": {\"human-weight\": 10, \"nonhum-weight\": 0},\n            \"test\": {\"file\": \"Restaurants_Test_Gold.xml.seg.jsonl\"},\n        }\n\n        dprep.init_set(sets_info)\n        return dprep, name, task_format\n\n    @classmethod\n    def newsmtsc_devtest_mt(cls, basepath):\n        name = \"newsmtsc-train-and-test-mt\"\n        task_format = \"newsmtsc\"\n        human_created_filenames = [\"devtest_mtsc_only.jsonl\"]\n        non_human_created_filenames = []\n        dprep = cls(\n            name,\n            basepath,\n            task_format,\n            human_created_filenames,\n            non_human_created_filenames,\n        )\n\n        sets_info = {\n            \"train\": {\"file\": \"train.jsonl\"},\n            \"dev\": {\"human-weight\": 30, \"nonhum-weight\": 0},\n            \"test\": {\"human-weight\": 70, \"nonhum-weight\": 0},\n        }\n\n        dprep.init_set(sets_info)\n        return dprep, name, task_format\n\n    @classmethod\n    def newsmtsc_devtest_rw(cls, basepath):\n        name = \"newsmtsc-train-and-test-rw\"\n        task_format = \"newsmtsc\"\n        human_created_filenames = [\"devtest_mtsc_and_single_primaries.jsonl\"]\n        non_human_created_filenames = []\n        dprep = cls(\n            name,\n            basepath,\n            task_format,\n            human_created_filenames,\n            non_human_created_filenames,\n        )\n\n        sets_info = {\n            \"train\": {\"file\": \"train.jsonl\"},\n            \"dev\": {\"human-weight\": 30, \"nonhum-weight\": 0},\n            \"test\": {\"human-weight\": 70, \"nonhum-weight\": 0},\n        }\n\n        dprep.init_set(sets_info)\n        return dprep, name, task_format\n\n\nif __name__ == \"__main__\":\n    DatasetPreparer.sentinews(\"controller_data/datasets\")\n"
  },
  {
    "path": "NewsSentiment/SentimentClasses.py",
    "content": "from typing import Iterable\n\n\nclass SentimentClasses:\n    FILLUP_POLARITY_VALUE = -100\n    FILLUP_POLARITY_LABEL = \"fillup\"\n    SENTIMENT_CLASSES = None\n\n    @staticmethod\n    def initialize(sentiment_classes: dict):\n        SentimentClasses.SENTIMENT_CLASSES = sentiment_classes\n\n    @staticmethod\n    def get_num_classes():\n        return len(SentimentClasses.SENTIMENT_CLASSES)\n\n    @staticmethod\n    def __evaluate_boundary(given_value: float, boundary: tuple):\n        operator = boundary[0]\n        value = boundary[1]\n        if operator == \"<=\":\n            return given_value <= value\n        elif operator == \"<\":\n            return given_value < value\n        elif operator == \">=\":\n            return given_value >= value\n        elif operator == \">\":\n            return given_value > value\n        elif operator == \"==\":\n            return given_value == value\n        else:\n            raise ValueError\n\n    @staticmethod\n    def __evaluate_boundaries_of_class(\n        given_value: float, sentiment_boundaries: Iterable[tuple]\n    ):\n        assert len(sentiment_boundaries) >= 1\n        for boundary in sentiment_boundaries:\n            is_valid = SentimentClasses.__evaluate_boundary(given_value, boundary)\n            if not is_valid:\n                return False\n        return True\n\n    @staticmethod\n    def __get_legacy_information():\n        # self.polarity_associations = {\"positive\": 2, \"neutral\": 1, \"negative\": 0}\n        # self.polarity_associations_inv = {2: \"positive\", 1: \"neutral\", 0: \"negative\"}\n        # self.sorted_expected_label_values = [0, 1, 2]\n        # self.sorted_expected_label_names = [\"negative\", \"neutral\", \"positive\"]\n\n        sentiment_labels = list(SentimentClasses.SENTIMENT_CLASSES.keys())\n        sentiment_normalized_values = []\n        for label in sentiment_labels:\n            sentiment_normalized_values.append(\n                SentimentClasses.SENTIMENT_CLASSES[label][\"normalized_polarity\"]\n            )\n\n        polarity_associations = {}\n        polarity_associations_inv = {}\n        for label, value in zip(sentiment_labels, sentiment_normalized_values):\n            polarity_associations[label] = value\n            polarity_associations_inv[value] = label\n\n        return {\n            \"polarity_associations\": polarity_associations,\n            \"polarity_associations_inv\": polarity_associations_inv,\n            \"sorted_expected_label_values\": sentiment_normalized_values,\n            \"sorted_expected_label_names\": sentiment_labels,\n        }\n\n    @staticmethod\n    def get_sorted_expected_label_names():\n        return SentimentClasses.__get_legacy_information()[\n            \"sorted_expected_label_names\"\n        ]\n\n    @staticmethod\n    def get_sorted_expected_label_values():\n        return SentimentClasses.__get_legacy_information()[\n            \"sorted_expected_label_values\"\n        ]\n\n    @staticmethod\n    def get_polarity_associations():\n        return SentimentClasses.__get_legacy_information()[\"polarity_associations\"]\n\n    @staticmethod\n    def get_polarity_associations_inverse():\n        return SentimentClasses.__get_legacy_information()[\"polarity_associations_inv\"]\n\n    @staticmethod\n    def __find_sentiment_class(polarity: float):\n        resulting_class = None\n        for sentiment_label, info in SentimentClasses.SENTIMENT_CLASSES.items():\n            sentiment_boundaries = info[\"boundaries\"]\n            sentiment_normalized_polarity = info[\"normalized_polarity\"]\n            is_in_class_boundaries = SentimentClasses.__evaluate_boundaries_of_class(\n                polarity, sentiment_boundaries\n            )\n            if is_in_class_boundaries:\n                # check polarity is not in another class, too\n                assert (\n                    resulting_class is None\n                ), f\"overlapping sentiment classes; previous class: {resulting_class}\"\n                resulting_class = (sentiment_label, sentiment_normalized_polarity)\n\n        # check that a class was found\n        assert resulting_class, f\"result is not defined for polarity: {polarity}\"\n\n        return resulting_class\n\n    @staticmethod\n    def polarity2label(polarity: float) -> str:\n        if polarity == SentimentClasses.FILLUP_POLARITY_VALUE:\n            return SentimentClasses.FILLUP_POLARITY_LABEL\n\n        sentiment_class = SentimentClasses.__find_sentiment_class(polarity)\n        label = sentiment_class[0]\n        return label\n\n    @staticmethod\n    def polarity2normalized_polarity(polarity: float) -> int:\n        if polarity == SentimentClasses.FILLUP_POLARITY_VALUE:\n            return int(SentimentClasses.FILLUP_POLARITY_VALUE)\n\n        sentiment_class = SentimentClasses.__find_sentiment_class(polarity)\n        normalized_polarity = sentiment_class[1]\n        return normalized_polarity\n\n    @staticmethod\n    def Sentiment3ForNewsMtsc():\n        sentiment_classes = {\n            \"positive\": {\n                \"boundaries\": [(\">=\", 5), (\"<=\", 7)],\n                \"normalized_polarity\": 2,\n            },\n            \"neutral\": {\"boundaries\": [(\">\", 3), (\"<\", 5)], \"normalized_polarity\": 1},\n            \"negative\": {\n                \"boundaries\": [(\">=\", 1), (\"<=\", 3)],\n                \"normalized_polarity\": 0,\n            },\n        }\n        SentimentClasses.initialize(sentiment_classes)\n\n    @staticmethod\n    def SentimentStrong3ForNewsMtsc():\n        sentiment_classes = {\n            \"positive\": {\n                \"boundaries\": [(\">=\", 6), (\"<=\", 7)],\n                \"normalized_polarity\": 2,\n            },\n            \"neutral\": {\"boundaries\": [(\">\", 2), (\"<\", 6)], \"normalized_polarity\": 1},\n            \"negative\": {\n                \"boundaries\": [(\">=\", 1), (\"<=\", 2)],\n                \"normalized_polarity\": 0,\n            },\n        }\n        SentimentClasses.initialize(sentiment_classes)\n\n    @staticmethod\n    def SentimentWeak3ForNewsMtsc():\n        sentiment_classes = {\n            \"positive\": {\n                \"boundaries\": [(\">=\", 4.5), (\"<=\", 7)],\n                \"normalized_polarity\": 2,\n            },\n            \"neutral\": {\n                \"boundaries\": [(\">\", 3.5), (\"<\", 4.5)],\n                \"normalized_polarity\": 1,\n            },\n            \"negative\": {\n                \"boundaries\": [(\">=\", 1), (\"<=\", 3.5)],\n                \"normalized_polarity\": 0,\n            },\n        }\n        SentimentClasses.initialize(sentiment_classes)\n"
  },
  {
    "path": "NewsSentiment/__init__.py",
    "content": "from NewsSentiment.infer import TargetSentimentClassifier\n"
  },
  {
    "path": "NewsSentiment/__main__.py",
    "content": "import argparse\n\nfrom NewsSentiment.download import Download\n\nif __name__ == '__main__':\n    parser = argparse.ArgumentParser(prog='NewsSentiment')\n    subparsers = parser.add_subparsers(dest='action')\n\n    subparser_download = subparsers.add_parser('download', help=Download.add_subparser.__doc__)\n    Download.add_subparser(subparser_download)\n\n    args = parser.parse_args()\n    action = args.action\n    del args.action\n\n    if action == 'download':\n        Download.run_from_parser(args)\n"
  },
  {
    "path": "NewsSentiment/combinations_default.py",
    "content": "from NewsSentiment.consts import BERT_BASE_UNCASED\n\ncombinations_default_0 = {\n    \"own_model_name\": [\n        # baselines: single\n        \"notargetclsbert\",\n        \"lcf_bert\",\n        \"lcf_bert2\",\n        \"lcfs_bert\",\n        \"lcft_bert\",\n        \"aen_bert\",\n        \"spc_bert\",\n        \"tdbert\",\n        \"tdbert-qa-mul\",\n        \"tdbert-qa-con\",\n        # own models: single\n        \"tdbertlikesingle\",\n        \"lcfst_bert\",\n        \"grutsc\",\n        # own models: multi\n        \"tdbertlikemulti\",\n        # \"tdbertlikemulti_dense\",\n        \"seq2seq\",\n        \"seq2seq_withouttargetmask\",\n        \"contrasting\",\n        # baselines\n        # \"random_single\",\n        # \"random_multi\",\n    ],\n    \"optimizer\": [\"adam\"],\n    \"initializer\": [\"xavier_uniform_\"],\n    \"learning_rate\": [\"2e-5\", \"3e-5\", \"5e-5\"],\n    \"batch_size\": [\n        \"16\",\n        # \"32\",\n    ],  # ['16', '32'],\n    \"balancing\": [\"None\"],  # ['None', 'lossweighting', 'oversampling'],\n    \"devmode\": [\"False\"],\n    \"num_epoch\": [\"2\", \"3\", \"4\"],\n    \"loss\": [\n        \"crossentropy\",\n        \"crossentropy_lsr\",\n        \"sequence\",\n        \"crossentropy_crossweight\",\n    ],\n    # \"spc_lm_representation_distilbert\": [\"mean_last\"],\n    # ['sum_last', 'sum_last_four', 'sum_last_two', 'sum_all', 'mean_last', 'mean_last_four', 'mean_last_two', 'mean_all'],\n    # \"spc_lm_representation\": [\"pooler_output\"],\n    # ['pooler_output', 'sum_last', 'sum_last_four', 'sum_last_two', 'sum_all', 'mean_last', 'mean_last_four', 'mean_last_two', 'mean_all'],\n    # \"spc_input_order\": [\"text_target\"],  # 'target_text',\n    # \"aen_lm_representation\": [\"last\"],\n    # ['last', 'sum_last_four', 'sum_last_two', 'sum_all', 'mean_last_four'],  # 'mean_last_two', 'mean_all'],\n    \"eval_only_after_last_epoch\": [\"True\"],\n    \"local_context_focus\": [\"cdm\", \"cdw\"],\n    \"SRD\": [\"3\", \"4\", \"5\"],\n    \"pretrained_model_name\": [\"default\"],\n    # ['default', 'bert_news_ccnc_10mio_3ep', 'laptops_and_restaurants_2mio_ep15', 'laptops_1mio_ep30', 'restaurants_10mio_ep3'],\n    \"state_dict\": [\"None\"],\n    # ['None', 'lcf_bert_acl14twitter_val_recall_avg_0.7349_epoch3', 'lcf_bert_semeval14laptops_val_recall_avg_0.7853_epoch3', 'lcf_bert_semeval14restaurants_val_recall_avg_0.7672_epoch2', 'lcf_bert_newstsc_val_recall_avg_0.5954_epoch3'],\n    \"single_targets\": [\n        \"True\"\n    ],  # using conditions in controller.py, we have single_targets only for single target models\n    \"multi_targets\": [\n        \"True\"\n    ],  # using conditions in controller.py, we have multi_targets only for multi target models\n    \"targetclasses\": [\n        \"newsmtsc3\",\n        #\"newsmtsc3strong\",\n        #\"newsmtsc3weak\",\n    ],\n    \"knowledgesources\": [\n        \"nrc_emotions\", \"mpqa_subjectivity\", \"bingliu_opinion\", \"liwc\",\n        \"nrc_emotions mpqa_subjectivity\", \"nrc_emotions liwc\",\n        \"nrc_emotions bingliu_opinion\", \"mpqa_subjectivity bingliu_opinion\",\n        \"mpqa_subjectivity liwc\", \"bingliu_opinion liwc\",\n        \"nrc_emotions mpqa_subjectivity bingliu_opinion\",\n        \"nrc_emotions mpqa_subjectivity liwc\",\n        \"nrc_emotions liwc bingliu_opinion\",\n        \"liwc mpqa_subjectivity bingliu_opinion\",\n        \"nrc_emotions mpqa_subjectivity bingliu_opinion liwc\",\n        \"zeros\",\n    ],\n    \"is_use_natural_target_phrase_for_spc\": [\n        \"True\",\n        \"False\"\n    ],\n    \"default_lm\": [\n        BERT_BASE_UNCASED,\n    ],\n    \"coref_mode_in_training\": [\n        \"ignore\",\n        \"in_targetmask\",\n        \"additional_examples\"\n    ],\n}\n"
  },
  {
    "path": "NewsSentiment/consts.py",
    "content": "BERT_BASE_UNCASED = \"bert-base-uncased\"\nROBERTA_BASE = \"roberta-base\"\nXLNET_BASE_CASED = \"xlnet-base-cased\"\nALBERT_BASE = \"albert-base-v2\"\nALBERT_LARGE = \"albert-large-v2\"\nALBERT_XLARGE = \"albert-xlarge-v2\"\nALBERT_XXLARGE = \"albert-xxlarge-v2\"\n__DEFAULT_LM = None\n\n\ndef set_default_lm(new_name: str):\n    global __DEFAULT_LM\n    __DEFAULT_LM = new_name\n\n\ndef get_default_lm():\n    return __DEFAULT_LM\n\n\nFIELD_TEXT_IDS_WITH_SPECIAL_TOKENS = \"text_ids_with_special_tokens\"\nFIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK = (\n    FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS + \"_target_mask\"\n)\nFIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES = (\n    FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS + \"_selectedknowledgesources\"\n)\nFIELD_IS_OVERFLOW = \"is_overflow\"\nFIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS = (\n    \"text_then_target_ids_with_special_tokens\"\n)\n# we used to have text-then-target target mask here, but won't use it,\n# since it would be identical to the text target mask (since we only\n# want to mark the target within the text, but not in the 2nd target\n# component)\n# FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK = (\n#    FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS + \"_target_mask\"\n# )\n# same for knowledge sources\n# FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_KNOWLEDGE_SOURCES = (\n#         FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS + \"_selectedknowledgesources\"\n# )\nFIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS = (\n    FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS + \"_segment_ids\"\n)\nFIELD_TARGET_IDS_WITH_SPECIAL_TOKENS = \"target_ids_with_special_tokens\"\nFIELD_SYNTAX_HOP_DISTANCE_TO_TARGET = \"syntax_hop_distance_to_target\"\nFIELD_SYNTAX_DEPENDENCY_MATRIX = \"syntax_dependency_matrix\"\n"
  },
  {
    "path": "NewsSentiment/controller.py",
    "content": "\"\"\"\nDefinitions:\nsetup: represents a fixed, unique combination of for instance:\n* model, e.g., BERT, DISTILBERT\n* hyper-parameters, such as learning rate loss function, weights of classes for loss function\n* others, such as softmax,\n* input style, e.g., input style: QA style, AEN, ...\n\nProcedure:\nGiven a single annotated dataset named alldat (also called both.jsonl, since it consists of both splits of the devtest\nset):\n* splits alldat into testdat and remainderdat\n\nGiven a set of experiment setup descriptions\n1) Iterate setup descriptions, for each:\na) create 10-fold CV to well evaluate the performance of that particular setup\nb) return model from best epoch (or from best fold???!?)\n2) retrievel all best performing models and test them on testdat\n3) return model that performs best on testdat\n\"\"\"\nfrom threading import Lock\nimport argparse\nimport multiprocessing\nimport os\nimport subprocess\nimport time\nfrom collections import Counter, defaultdict\nfrom datetime import datetime\nfrom itertools import product\n\nfrom jsonlines import jsonlines\nfrom tabulate import tabulate\nfrom tqdm import tqdm\n\nfrom NewsSentiment.combinations_ensemble import combinations_ensemble\nfrom NewsSentiment.combinations_final_lcf2 import combinations_final_lcf2\nfrom NewsSentiment.combinations_final_nostance import combinations_final_nostance\nfrom NewsSentiment.combinations_final_spc import combinations_final_spc\nfrom NewsSentiment.combinations_final_stance0 import combinations_final_stance0\nfrom NewsSentiment.combinations_final_stance1 import combinations_final_stance1\nfrom NewsSentiment.combinations_final_tdbert import combinations_final_tdbert\nfrom NewsSentiment.combinations_top import combinations_top\nfrom NewsSentiment.DatasetPreparer import DatasetPreparer\nfrom NewsSentiment.combinations_default import combinations_default_0\nfrom NewsSentiment.combinations_top4otherdomains import combinations_top4otherdomains\nfrom NewsSentiment.combinations_top_coref16 import combinations_top_coref16\nfrom NewsSentiment.combinations_top_coref8 import combinations_top_coref8\nfrom NewsSentiment.combinations_top_coref8_stanceno import combinations_top_coref8_stanceno\nfrom NewsSentiment.combinations_top_finetuned import combinations_top_finetuned\nfrom NewsSentiment.diskdict import DiskDict\nfrom NewsSentiment.fxlogger import get_logger\nfrom NewsSentiment.train import str2bool\n\ncompleted_tasks = None  # will be DiskDict later\ncompleted_tasks_in_this_run_count = 0\nlock = Lock()\n\n\ndef start_worker(\n    experiment_id,\n    experiment_named_id,\n    named_combination,\n    cmd,\n    human_cmd,\n    experiment_path,\n    running_processes,\n):\n    if \"--device\" in cmd:\n        device_index_in_list = cmd.index(\"--device\")\n        device = cmd[device_index_in_list + 1]\n    else:\n        device = -1\n\n    running_processes[experiment_id] = (True, device)\n    logger = get_logger()\n\n    logger.debug(\"starting single setup: {}\".format(human_cmd))\n    with open(os.path.join(experiment_path, \"stdlog.out\"), \"w\") as file_stdout, open(\n        os.path.join(experiment_path, \"stdlog.err\"), \"w\"\n    ) as file_stderr:\n        completed_process = subprocess.run(cmd, stdout=file_stdout, stderr=file_stderr)\n\n    experiment_details = get_experiment_result_detailed(experiment_path)\n\n    running_processes[experiment_id] = (False, device)\n    return {\n        **named_combination,\n        **{\"rc\": completed_process.returncode, \"experiment_id\": experiment_id},\n        \"details\": experiment_details,\n        \"experiment_named_id\": experiment_named_id,\n    }\n\n\ndef on_task_done(x):\n    with lock:\n        # result_list is modified only by the main process, not the pool workers.\n        completed_tasks[x[\"experiment_named_id\"]] = x\n        completed_tasks.sync_to_disk()\n        global completed_tasks_in_this_run_count\n        completed_tasks_in_this_run_count += 1\n\n\ndef on_task_error(x):\n    with lock:\n        # result_list is modified only by the main process, not the pool workers.\n        completed_tasks[x[\"experiment_named_id\"]] = x\n        completed_tasks.sync_to_disk()\n        global completed_tasks_in_this_run_count\n        completed_tasks_in_this_run_count += 1\n\n\ndef get_experiment_result_detailed(experiment_path):\n    experiment_results_path = os.path.join(experiment_path, \"experiment_results.jsonl\")\n    try:\n        with jsonlines.open(experiment_results_path, \"r\") as reader:\n            lines = []\n            for line in reader:\n                lines.append(line)\n            assert len(lines) == 1\n        return lines[0]\n    except FileNotFoundError:\n        return None\n\n\nclass SetupController:\n    def __init__(self, options):\n        self.logger = get_logger()\n        self.opt = options\n\n        if self.opt.cuda_devices:\n            # to run on SCC\n            if self.opt.cuda_devices == \"SGE_GPU\":\n                self.cuda_devices = os.environ.get(\"SGE_GPU\")\n            else:\n                self.cuda_devices = self.opt.cuda_devices\n\n            if self.cuda_devices:\n                self.logger.info(\"cuda devices:\" + self.cuda_devices)\n                self.cuda_devices = self.cuda_devices.split(\",\")\n                self.logger.info(\n                    f\"was assigned {len(self.cuda_devices)} cuda devices: \"\n                    f\"{self.cuda_devices}\"\n                )\n                if self.opt.num_workers < 0:\n                    self.logger.info(\n                        f\"num_workers < 0: using cuda device count. setting \"\n                        f\"num_workers={len(self.cuda_devices)}\"\n                    )\n                    self.opt.num_workers = len(self.cuda_devices)\n\n        else:\n            # do not use CUDA\n            self.cuda_devices = None\n\n        self.snem = \"f1_macro\"\n        self.experiment_base_path = self.opt.experiments_path\n\n        args_names_ordered = [\n            \"own_model_name\",\n            \"optimizer\",\n            \"initializer\",\n            \"learning_rate\",\n            \"batch_size\",\n            \"balancing\",\n            \"num_epoch\",\n            \"loss\",\n            \"eval_only_after_last_epoch\",\n            \"devmode\",\n            \"local_context_focus\",\n            \"SRD\",\n            \"pretrained_model_name\",\n            \"state_dict\",\n            \"single_targets\",\n            \"multi_targets\",\n            \"targetclasses\",\n            \"knowledgesources\",\n            \"is_use_natural_target_phrase_for_spc\",\n            \"default_lm\",\n            \"coref_mode_in_training\",\n        ]\n\n        combinations = None\n        if self.opt.combi_mode == \"default\":\n            combinations = combinations_default_0\n        elif self.opt.combi_mode == \"top\":\n            combinations = combinations_top\n        elif self.opt.combi_mode == \"top_coref8\":\n            combinations = combinations_top_coref8\n        elif self.opt.combi_mode == \"top_coref8_stanceno\":\n            combinations = combinations_top_coref8_stanceno\n        elif self.opt.combi_mode == \"top_coref16\":\n            combinations = combinations_top_coref16\n        elif self.opt.combi_mode == \"top_finetuned\":\n            combinations = combinations_top_finetuned\n        elif self.opt.combi_mode == \"top4otherdomains\":\n            combinations = combinations_top4otherdomains\n        elif self.opt.combi_mode == \"ensemble\":\n            combinations = combinations_ensemble\n        elif self.opt.combi_mode == \"final_stance0\":\n            combinations = combinations_final_stance0\n        elif self.opt.combi_mode == \"final_stance1\":\n            combinations = combinations_final_stance1\n        elif self.opt.combi_mode == \"final_nostance\":\n            combinations = combinations_final_nostance\n        elif self.opt.combi_mode == \"final_tdbert\":\n            combinations = combinations_final_tdbert\n        elif self.opt.combi_mode == \"final_lcf2\":\n            combinations = combinations_final_lcf2\n        elif self.opt.combi_mode == \"final_spc\":\n            combinations = combinations_final_spc\n\n        if not combinations:\n            raise ValueError(\n                \"combination(mode={}, id={}) not defined\".format(\n                    self.opt.combi_mode, self.opt.combi_id\n                )\n            )\n\n        # key: name of parameter that is only applied if its conditions are met\n        # pad_value: list of tuples, consisting of parameter name and the pad_value it needs to have in order for the\n        # condition to be satisfied\n        # Note that all tuples in this list are OR connected, so if at least one is satisfied, the conditions are met.\n        # If we need AND connected conditions, my idea is to add an outer list, resulting in a list of lists (of\n        # tuples) where all lists are AND connected.\n        # If a condition is not satisfied, the corresponding parameter will still be pass\n        # if a key is not listed here, there are no conditions and thus the key / parameter will be used always\n        conditions = {\n            \"is_use_natural_target_phrase_for_spc\": [(\"own_model_name\", \"spc_bert\")],\n            \"spc_lm_representation\": [(\"own_model_name\", \"spc_bert\"),],\n            \"spc_input_order\": [(\"own_model_name\", \"spc_bert\"),],\n            \"aen_lm_representation\": [(\"own_model_name\", \"aen_bert\"),],\n            \"use_early_stopping\": [(\"num_epoch\", \"10\"),],\n            \"local_context_focus\": [\n                (\"own_model_name\", \"lcf_bert\"),\n                (\"own_model_name\", \"lcf_bert2\"),\n                (\"own_model_name\", \"lcfs_bert\"),\n                (\"own_model_name\", \"lcfst_bert\"),\n            ],\n            \"SRD\": [\n                (\"own_model_name\", \"lcf_bert\"),\n                (\"own_model_name\", \"lcf_bert2\"),\n                (\"own_model_name\", \"lcfs_bert\"),\n                (\"own_model_name\", \"lcfst_bert\"),\n            ],\n            \"single_targets\": [\n                # we need single_targets mode only for models that are single target\n                (\"own_model_name\", \"lcf_bert\"),\n                (\"own_model_name\", \"lcf_bert2\"),\n                (\"own_model_name\", \"lcfs_bert\"),\n                (\"own_model_name\", \"lcft_bert\"),\n                (\"own_model_name\", \"lcfst_bert\"),\n                (\"own_model_name\", \"aen_bert\"),\n                (\"own_model_name\", \"spc_bert\"),\n                (\"own_model_name\", \"tdbert\"),\n                (\"own_model_name\", \"EnsembleTopA\"),\n                (\"own_model_name\", \"EnsembleTopB\"),\n                (\"own_model_name\", \"tdbert-qa-mul\"),\n                (\"own_model_name\", \"tdbert-qa-con\"),\n                (\"own_model_name\", \"tdbertlikesingle\"),\n                (\"own_model_name\", \"notargetclsbert\"),\n                (\"own_model_name\", \"random_single\"),\n                (\"own_model_name\", \"grutsc\"),\n            ],\n            \"multi_targets\": [\n                (\"own_model_name\", \"tdbertlikemulti\"),\n                (\"own_model_name\", \"tdbertlikemulti_dense\"),\n                (\"own_model_name\", \"seq2seq\"),\n                (\"own_model_name\", \"seq2seq_withouttargetmask\"),\n                (\"own_model_name\", \"random_multi\"),\n                (\"own_model_name\", \"contrasting\"),\n            ],\n            \"knowledgesources\": [\n                (\"own_model_name\", \"EnsembleTopA\"),\n                (\"own_model_name\", \"EnsembleTopB\"),\n                (\"own_model_name\", \"grutsc\"),\n            ],\n            \"pretrained_model_name\": [(\"default_lm\", \"bert-base-uncased\"),],\n        }\n\n        assert set(args_names_ordered) == set(combinations.keys()), (\n            f\"mismatch args_names_ordered vs. combinations: \"\n            f\"{set(args_names_ordered).symmetric_difference(combinations)}\"\n        )\n\n        self.experiment_base_id = (\n            self.opt.dataset + \"_\" + datetime.today().strftime(\"%Y%m%d-%H%M%S\")\n        )\n        self.basecmd = [\"python\", \"train.py\"]\n        self.basepath = \"controller_data\"\n        self.basepath_data = os.path.join(self.basepath, \"datasets\")\n\n        combination_count = 1\n        _combination_values = []\n        for arg_name in args_names_ordered:\n            arg_values = list(combinations[arg_name])\n            combination_count = combination_count * len(arg_values)\n            _combination_values.append(arg_values)\n\n        combinations = list(product(*_combination_values))\n        assert len(combinations) == combination_count\n\n        self.logger.info(\n            \"{} arguments, totaling in {} combinations\".format(\n                len(args_names_ordered), combination_count\n            )\n        )\n\n        # apply conditions\n        self.logger.info(\"applying conditions...\")\n        self.named_combinations, count_duplicates = self._apply_conditions(\n            combinations, args_names_ordered, conditions\n        )\n        self.logger.info(\n            \"applied conditions. removed {} combinations. {} -> {}\".format(\n                count_duplicates, combination_count, len(self.named_combinations)\n            )\n        )\n        self.combination_count = len(self.named_combinations)\n\n        # expand by number of runs per experiment\n        expanded_named_combinations = []\n        for named_combination in self.named_combinations:\n            for run_id in range(self.opt.num_runs_per_experiment):\n                expanded_named_combination = named_combination.copy()\n                expanded_named_combination[\"run_id\"] = run_id\n                expanded_named_combinations.append(expanded_named_combination)\n        self.logger.info(\n            \"expanded to %s runs per experiment. combination count: %s -> %s\",\n            self.opt.num_runs_per_experiment,\n            self.combination_count,\n            len(expanded_named_combinations),\n        )\n        self.named_combinations = expanded_named_combinations\n        self.combination_count = len(self.named_combinations)\n\n        if self.opt.dataset == \"semeval14restaurants\":\n            (\n                self.dataset_preparer,\n                self.datasetname,\n                self.task_format,\n            ) = DatasetPreparer.semeval14restaurants(self.basepath_data)\n        elif self.opt.dataset == \"semeval14laptops\":\n            (\n                self.dataset_preparer,\n                self.datasetname,\n                self.task_format,\n            ) = DatasetPreparer.semeval14laptops(self.basepath_data)\n        elif self.opt.dataset == \"acl14twitter\":\n            (\n                self.dataset_preparer,\n                self.datasetname,\n                self.task_format,\n            ) = DatasetPreparer.acl14twitter(self.basepath_data)\n        elif (\n            self.opt.dataset\n            == \"newsmtsc_devtest_rw\"\n        ):\n            (\n                self.dataset_preparer,\n                self.datasetname,\n                self.task_format,\n            ) = DatasetPreparer.newsmtsc_devtest_rw(\n                self.basepath_data\n            )\n        elif (\n                self.opt.dataset\n                == \"newsmtsc_devtest_mt\"\n        ):\n            (\n                self.dataset_preparer,\n                self.datasetname,\n                self.task_format,\n            ) = DatasetPreparer.newsmtsc_devtest_mt(\n                self.basepath_data\n            )\n        else:\n            raise Exception(\"unknown dataset: {}\".format(self.opt.dataset))\n\n    def _apply_conditions(self, combinations, args_names_ordered, conditions):\n        named_combinations = []\n        seen_experiment_ids = set()\n        count_duplicates = 0\n\n        with tqdm(total=len(combinations)) as pbar:\n            for combination in combinations:\n                named_combination = {}\n                full_named_combination = self._args_combination_to_single_arg_values(\n                    combination, args_names_ordered\n                )\n\n                # for a parameter combination, pass only those parameters that are valid\n                # for that combination\n                for arg_index, arg_name in enumerate(args_names_ordered):\n                    # iterate each parameter and validate - using the other parameter\n                    # names and values - whether its conditions are met\n                    if self._check_conditions(\n                        arg_name, full_named_combination, conditions\n                    ):\n                        # if yes, pass it\n                        named_combination[arg_name] = combination[arg_index]\n                        self.logger.debug(\n                            \"using '{}' in combination {}\".format(arg_name, combination)\n                        )\n                    else:\n                        self.logger.debug(\n                            \"not using '{}' in combination {}\".format(\n                                arg_name, combination\n                            )\n                        )\n\n                # check if experiment_id of named combination was already seen\n                experiment_id = self._experiment_named_id_from_named_combination(\n                    named_combination\n                )\n                if experiment_id not in seen_experiment_ids:\n                    seen_experiment_ids.add(experiment_id)\n                    named_combinations.append(named_combination)\n                else:\n                    count_duplicates += 1\n\n                pbar.update(1)\n\n        return named_combinations, count_duplicates\n\n    def _check_conditions(self, arg_name, full_named_combination, conditions):\n        \"\"\"\n        For a given parameter, checks whether its conditions are satisfied. If so, returns True, else False.\n        :param arg_name:\n        :param arg_value:\n        :return:\n        \"\"\"\n        if arg_name in conditions and len(conditions[arg_name]) >= 1:\n            # at this point we know that there are conditions for the given parameters\n            or_connected_conditions = conditions[arg_name]\n\n            for cond_tup in or_connected_conditions:\n                cond_param_name = cond_tup[0]\n                cond_param_value = cond_tup[1]\n\n                # get parameter and its pad_value in current combination\n                if full_named_combination[cond_param_name] == cond_param_value:\n                    return True\n\n            # since there was at least one condition due to our check above, we return\n            # False here, since the for loop did not return True\n            return False\n\n        else:\n            # if there is no condition associated with arg_name just return true\n            return True\n\n    def _build_args(self, named_args):\n        args_list = []\n        for arg_name, arg_val in named_args.items():\n            self._add_arg(args_list, arg_name, arg_val)\n\n        return args_list\n\n    def _add_arg(self, args_list, name, value):\n        args_list.append(\"--\" + name)\n        args_list.append(str(value))\n        return args_list\n\n    def _prepare_experiment_env(self, experiment_path):\n        os.makedirs(experiment_path, exist_ok=True)\n        self.dataset_preparer.export(os.path.join(experiment_path, \"datasets\"))\n\n    def _args_combination_to_single_arg_values(\n        self, args_combination, args_names_ordered\n    ):\n        args_names_values = {}\n        for arg_index, arg_name in enumerate(args_names_ordered):\n            args_names_values[arg_name] = args_combination[arg_index]\n        return args_names_values\n\n    def _experiment_named_id_from_named_combination(self, named_combination):\n        return \"__\".join([\"{}={}\".format(k, v) for (k, v) in named_combination.items()])\n\n    def prepare_single_setup(self, named_combination, experiment_id, pool_index):\n        experiment_path = \"{}/{}/\".format(self.experiment_base_id, experiment_id)\n        experiment_path = os.path.join(self.experiment_base_path, experiment_path)\n\n        self._prepare_experiment_env(experiment_path)\n\n        args = self._build_args(named_combination)\n        self._add_arg(args, \"snem\", self.snem)\n        self._add_arg(args, \"dataset_name\", self.datasetname)\n        self._add_arg(args, \"experiment_path\", experiment_path)\n        self._add_arg(args, \"data_format\", self.task_format)\n\n        if self.cuda_devices:\n            # we use the pool_index to get the respective pool's cuda device\n            cuda_device_id = self.cuda_devices[pool_index]\n            cuda_device_name = \"cuda:\" + str(cuda_device_id)\n            self._add_arg(args, \"device\", cuda_device_name)\n\n        cmd = self.basecmd + args\n        human_cmd = \" \".join(cmd)\n\n        with open(os.path.join(experiment_path, \"experiment_cmd.sh\"), \"w\") as writer:\n            writer.write(human_cmd)\n\n        return cmd, human_cmd, experiment_path\n\n    def run(self):\n        global completed_tasks\n\n        if not self.opt.results_path:\n            results_path = \"results/default_results_{}\".format(self.datasetname)\n        else:\n            results_path = self.opt.results_path\n\n        if not self.opt.continue_run:\n            self.logger.info(\"not continuing\")\n            os.remove(results_path)\n        else:\n            self.logger.info(\"continuing previous run(s)\")\n\n        completed_tasks = DiskDict(results_path)\n        self.logger.info(\"found {} previous results\".format(len(completed_tasks)))\n\n        self.logger.info(\"preparing experiment setups...\")\n        experiment_descs = defaultdict(list)\n        previous_tasks = Counter()\n        with tqdm(total=self.combination_count) as pbar:\n            for i, named_combination in enumerate(self.named_combinations):\n                _experiment_named_id = self._experiment_named_id_from_named_combination(\n                    named_combination\n                )\n                # i modulo the number of workers determines which pool this experiment\n                # will run in. the pool_index will also later be used to determine\n                # which cuda device (if any) to use, thereby making sure, that all tasks\n                # of one pool use the same device, whereas each device will be used\n                # solely by only one pool (this way, we make sure that at no time two\n                # or more tasks will run that use the same cuda device)\n                pool_index = i % self.opt.num_workers\n\n                if _experiment_named_id in completed_tasks:\n                    task_desc = completed_tasks[_experiment_named_id]\n\n                    if task_desc[\"rc\"] != 0:\n                        if self.opt.rerun_non_rc0:\n                            self.logger.debug(\n                                \"task {} was already executed, \"\n                                \"but with rc={}. rerunning.\".format(\n                                    _experiment_named_id, task_desc[\"rc\"]\n                                )\n                            )\n                            (\n                                cmd,\n                                human_cmd,\n                                experiment_path,\n                            ) = self.prepare_single_setup(\n                                named_combination, i, pool_index\n                            )\n\n                            experiment_descs[pool_index].append(\n                                (\n                                    i,\n                                    _experiment_named_id,\n                                    named_combination,\n                                    cmd,\n                                    human_cmd,\n                                    experiment_path,\n                                )\n                            )\n\n                            previous_tasks[\"new\"] += 1\n                            del completed_tasks[_experiment_named_id]\n                        else:\n                            self.logger.debug(\n                                \"task {} was already executed, but with rc={}. not \"\n                                \"rerunning.\".format(\n                                    _experiment_named_id, task_desc[\"rc\"]\n                                )\n                            )\n                            previous_tasks[\"rcnon0\"] += 1\n                    else:\n                        # rerun tasks where the rc != 0 (always rerun tasks that have\n                        # not been executed at all, yet)\n                        self.logger.debug(\n                            \"skipping experiment: {}\".format(_experiment_named_id)\n                        )\n                        self.logger.debug(\n                            \"previous result: {}\".format(\n                                completed_tasks[_experiment_named_id]\n                            )\n                        )\n                        previous_tasks[\"rc0\"] += 1\n                else:\n                    (cmd, human_cmd, experiment_path,) = self.prepare_single_setup(\n                        named_combination, i, pool_index\n                    )\n\n                    experiment_descs[pool_index].append(\n                        (\n                            i,\n                            _experiment_named_id,\n                            named_combination,\n                            cmd,\n                            human_cmd,\n                            experiment_path,\n                        )\n                    )\n                    previous_tasks[\"new\"] += 1\n                pbar.update(1)\n\n        self.logger.info(\n            \"summary (new is also increased for tasks that were executed previously \"\n            \"but yielded rc!=0 - if rerun_non_rc0==True\"\n        )\n        self.logger.info(\"{}\".format(previous_tasks))\n\n        self.logger.info(\"starting {} experiments\".format(self.combination_count))\n        self.logger.info(\n            \"creating {} process pools with each 1 worker\".format(self.opt.num_workers)\n        )\n\n        if self.cuda_devices and len(self.cuda_devices) != self.opt.num_workers:\n            self.logger.warning(\n                \"number of cuda devices does not match number of workers: \"\n                \"{} vs. {}\".format(len(self.cuda_devices), self.opt.num_workers)\n            )\n\n        manager = multiprocessing.Manager()\n        running_processes = manager.dict()\n        for pool_index in range(self.opt.num_workers):\n            pool = multiprocessing.Pool(processes=1, maxtasksperchild=1)\n            for desc in experiment_descs[pool_index]:\n                proc_args = desc + (running_processes,)  # must be a tuple\n                pool.apply_async(\n                    start_worker,\n                    args=proc_args,\n                    callback=on_task_done,\n                    error_callback=on_task_error,\n                )\n            self.logger.info(\n                f\"created pool with {len(experiment_descs[pool_index])} tasks, each \"\n                f\"processed by 1 worker\"\n            )\n\n        self.logger.info(\"waiting for workers to complete all jobs...\")\n        prev_count_done = 0\n        with tqdm(total=previous_tasks[\"new\"], initial=prev_count_done) as pbar:\n            while completed_tasks_in_this_run_count < previous_tasks[\"new\"]:\n                time.sleep(10)\n                update_inc = completed_tasks_in_this_run_count - prev_count_done\n\n                if update_inc > 0:\n                    pbar.update(update_inc)\n                    prev_count_done = completed_tasks_in_this_run_count\n                    completed_tasks.sync_to_disk()\n\n                best_dev_snem, best_experiment_id = self._get_best_dev_snem()\n                sorted_running_procs = sorted(\n                    self._get_running_processes(running_processes),\n                    key=lambda running_device: running_device[1],\n                )\n                pbar.set_postfix_str(\n                    f\"dev-snem: {best_dev_snem:.3f} ({best_experiment_id}); prcs: {sorted_running_procs}\"\n                )\n\n        # save to disk\n        completed_tasks.sync_to_disk()\n        self.logger.info(\n            f\"finished all tasks ({completed_tasks_in_this_run_count} of \"\n            f\"{previous_tasks['new']})\"\n        )\n\n        # clone the results so that we can process them while not modifying the original\n        processed_results = dict(completed_tasks)\n\n        experiments_rc_overview = Counter()\n        non_okay_experiment_ids = []\n        for experiment_named_id, experiment_result in processed_results.items():\n            rc = experiment_result[\"rc\"]\n            experiments_rc_overview[rc] += 1\n\n            if rc != 0:\n                if rc == 99:\n                    pass\n                else:\n                    non_okay_experiment_ids.append(experiment_result[\"experiment_id\"])\n\n        self.logger.warning(\n            f\"{len(non_okay_experiment_ids)} experiments did not return 0: \"\n            f\"{sorted(non_okay_experiment_ids)}\"\n        )\n\n        # snem-based performance sort\n        sorted_results = list(dict(processed_results).values())\n        for result in sorted_results:\n            if result[\"details\"]:\n                result[\"dev_snem\"] = result[\"details\"][\"dev_stats\"][self.snem]\n                del result[\"details\"]\n            else:\n                result[\"dev_snem\"] = -1.0\n        sorted_results.sort(key=lambda x: x[\"dev_snem\"], reverse=True)\n        headers = list(sorted_results[0].keys())\n        rows = [x.values() for x in sorted_results]\n\n        self.logger.info(\"all experiments finished. statistics:\")\n        self.logger.debug(\"snem-based performances:\")\n        self.logger.debug(\"\\n\" + tabulate(rows, headers))\n        self.logger.info(\"return codes: {}\".format(experiments_rc_overview))\n        self.logger.info(\n            \"best dev-snem: %s (id: %s)\",\n            sorted_results[0][\"dev_snem\"],\n            sorted_results[0][\"experiment_id\"],\n        )\n\n    def _get_best_dev_snem(self):\n        best_dev_snem = -1.0\n        experiment_id = -1\n        # to avoid that the dict is modified while iterating it, copy it for temporary use\n        # if we're unlucky this could happen otherwise: RuntimeError: dictionary changed size during iteration\n        tmp_tasks = completed_tasks.copy()\n        for task in tmp_tasks.values():\n            if task.get(\"details\") and task[\"details\"].get(\"dev_stats\"):\n                best_dev_snem = max(\n                    best_dev_snem, task[\"details\"][\"dev_stats\"][self.snem]\n                )\n                experiment_id = task[\"experiment_id\"]\n        return best_dev_snem, experiment_id\n\n    def _get_running_processes(self, running_processes):\n        return [\n            (exp_id, running_device[1])\n            for exp_id, running_device in running_processes.items()\n            if running_device[0]\n        ]\n\n\nif __name__ == \"__main__\":\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--dataset\", default=None, type=str)\n    parser.add_argument(\"--experiments_path\", default=\"./experiments\", type=str)\n    parser.add_argument(\n        \"--continue_run\", type=str2bool, nargs=\"?\", const=True, default=True\n    )\n    parser.add_argument(\n        \"--rerun_non_rc0\", type=str2bool, nargs=\"?\", const=True, default=True\n    )\n    parser.add_argument(\"--num_workers\", type=int, default=1)\n    parser.add_argument(\"--results_path\", type=str, default=None)\n    parser.add_argument(\"--combi_mode\", type=str, required=True)\n    parser.add_argument(\"--combi_id\", type=int, default=0)\n    parser.add_argument(\n        \"--cuda_devices\",\n        type=str,\n        default=None,\n        help=\"Comma separated list of cuda device IDs, e.g., \"\n        \"0,1,2,3; or SGE_GPU to read this list from \"\n        \"the environment variable SGE_GPU. If not defined,\"\n        \"CPU will be used instead of GPU.\",\n    )\n    parser.add_argument(\"--num_runs_per_experiment\", type=int, default=1)\n    parser.add_argument(\n        \"--only_calc_combinations\", type=str2bool, nargs=\"?\", const=True, default=False\n    )\n    opt = parser.parse_args()\n\n    if opt.only_calc_combinations:\n        SetupController(opt)\n    else:\n        SetupController(opt).run()\n"
  },
  {
    "path": "NewsSentiment/controller_data/datasets/NewsMTSC-dataset/devtest_mt.jsonl",
    "content": "{\"primary_gid\": \"allsides_1002_402_12_former FBI director James B. Comey_51_56\", \"sentence_normalized\": \"While White House officials said in the days after Comey's dismissal that it was largely the result of a memo written by Deputy Attorney General Rod J. Rosenstein criticizing the FBI director's handling of the investigation into Hillary Clinton’s use of a private email server when she was secretary of state, Trump suggested in the NBC interview that the Russian investigation played a role in his decision.\", \"targets\": [{\"Input.gid\": \"allsides_1002_402_12_Hillary Clinton’s_229_246\", \"from\": 229, \"to\": 246, \"mention\": \"Hillary Clinton’s\", \"polarity\": 2.0, \"further_mentions\": [{\"from\": 282, \"to\": 285, \"mention\": \"she\"}]}, {\"Input.gid\": \"allsides_1002_402_12_former FBI director James B. 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Assistant Director Peter Strzok damaged the integrity of the entire Clinton email probe, Horowitz writes.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4525031_-1_6_Clinton_117_124\", \"from\": 117, \"to\": 124, \"mention\": \"Clinton\", \"polarity\": 2.0}, {\"Input.gid\": \"polusa_v1_4525031_-1_6_Strzok_29_35\", \"from\": 29, \"to\": 35, \"mention\": \"Strzok\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_4537616_-1_4_Zulfikar Ali Bhutto_1262_1281\", \"sentence_normalized\": \"A timeline of major political and other events in Pakistan's history:\\n__Aug. 14, 1947: Pakistan emerges as a sovereign state after getting independence when the departing British left India and split the subcontinent;\\n__Sept. 11, 1948: Pakistan's founder Mohammad Ali Jinnah dies;\\n__Oct. 16, 1951: Pakistan first prime minister, Liaquat Ali Khan, is assassinated in a gun attack at a rally in the city of Rawalpind, triggering political instability;\\n__Oct. 7, 1958: President Iskander Mirza abolishes 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Muhammad Ayub Khan, then army chief becomes administrator;\\n__Oct. 27, 1958: Ayub forces the president to step down; Mirza is sent to exile in Britain where he later dies; Ayub declared himself president;\\n__March 25, 1969: After months of rioting in West and East Pakistan, Khan hands over power to army chief Gen. Agha Mohammed Yahya Khan;\\n__Dec. 7, 1970: East Pakistan-based Awami League wins general elections; Yahya Khan delays transfer of power, triggering widespread rioting in East Pakistan; civil war breaks out;\\n__Dec. 16, 1971: Pakistan troops surrender in East Pakistan after Indian armed intervention in the civil war; East Pakistan becomes independent Bangladesh;\\n__Dec. 20, 1971: Yahya Khan resigns, Zulfikar Ali Bhutto becomes president; a parliamentary system of government is adopted and Bhutto becomes prime minister;\\n__July 5, 1977: Army chief Gen. Ziaul Haq seizes power;\\n__April 4, 1979: Bhutto is hanged after the Supreme Court upholds death sentence on charges of conspiracy to murder and Gen. Zia rejects a mercy petition; Bhutto's daughter, Benazir Bhutto, takes up her father's legacy;\\n__Aug. 17, 1988: Gen. Zia dies in a mysterious plane crash;\\n__Nov. 16, 1988: Benazir Bhutto becomes Pakistan's first woman prime minister;\\n__Aug. 6, 1990: Benazir Bhutto's government is dismissed amid charges of corruption and mismanagement;\\n__Oct. 24, 1990: Parliamentary elections are held and Nawaz Sharif becomes prime minister;\\n__April 19, 1993: President Ghulam Ishaq Khan dismisses Sharif government on corruption charges but the Supreme Court reinstates Sharif; Sharif and Khan fail to reconcile and end conflict so the then-army chief Gen. 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Roosevelt_65_86\", \"sentence_normalized\": \"Standing on a platform set in the middle of a grassy memorial to Franklin D. Roosevelt on the East River island named after him, Mrs. Clinton invoked his legacy.\", \"targets\": [{\"Input.gid\": \"allsides_3126_1283_10_Franklin D. Roosevelt_65_86\", \"from\": 65, \"to\": 86, \"mention\": \"Franklin D. Roosevelt\", \"polarity\": 6.0, \"further_mentions\": [{\"from\": 124, \"to\": 127, \"mention\": \"him\"}]}]}\n{\"primary_gid\": \"polusa_v1_38941265_-1_31_Ridd_44_48\", \"sentence_normalized\": \"Among the allegations, the university says Ridd had “perpetuated a view that you were not allowed to talk to your wife about the disciplinary process, when in fact this was contrary to what you were told by verbally, and in writing … ”. He had denigrated a colleague, disclosed confidential information and “failed to take reasonable steps to avoid or manage a conflict of interest between your own interests and the interests of the Institute of Public Affairs (IPA) and the interests of the university”.\", \"targets\": [{\"Input.gid\": \"polusa_v1_38941265_-1_31_Ridd_44_48\", \"from\": 43, \"to\": 47, \"mention\": \"Ridd\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_52876943_-1_13_Najib_0_6\", \"sentence_normalized\": \"Najib said the facts would show he \\\"returned a large sum of money\\\" right after he lost the national election this past spring.\", \"targets\": [{\"Input.gid\": \"polusa_v1_52876943_-1_13_Najib_0_6\", \"from\": 0, \"to\": 5, \"mention\": \"Najib\", \"polarity\": 6.0, \"further_mentions\": [{\"from\": 32, \"to\": 34, \"mention\": \"he\"}, {\"from\": 0, \"to\": 5, \"mention\": \"Najib\"}, {\"from\": 79, \"to\": 81, \"mention\": \"he\"}]}]}\n{\"primary_gid\": \"polusa_v1_79065322_-1_84_Arpaio_12_18\", \"sentence_normalized\": \"Otherwise, Arpaio doesn’t demonstrate much interest in policy—trade or the deficit or health care—aside from the broad strokes of the Trump agenda.\", \"targets\": [{\"Input.gid\": \"polusa_v1_79065322_-1_84_Arpaio_12_18\", \"from\": 11, \"to\": 17, \"mention\": \"Arpaio\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_5299_2251_8_Edward Snowden_21_35\", \"sentence_normalized\": \"A former contractor, Edward Snowden, leaked information on the programs last week.\", \"targets\": [{\"Input.gid\": \"allsides_5299_2251_8_Edward Snowden_21_35\", \"from\": 21, \"to\": 35, \"mention\": \"Edward Snowden\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_4604_1927_11_Paul Ryan_0_4\", \"sentence_normalized\": \"Ryan also acknowledged that the possibility of the House passing a bill that could reach the president's desk by the end of the year is still \\\"clearly in doubt.\\\"\", \"targets\": [{\"Input.gid\": \"allsides_4604_1927_11_Paul Ryan_0_4\", \"from\": 0, \"to\": 4, \"mention\": \"Ryan\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"allsides_1916_779_13_former CIA Director Michael Hayden_0_14\", \"sentence_normalized\": \"Michael Hayden on Trump: If someone else said that outside the hall, he’d be in the back of a police wagon https://t.co/4DFkNks2Kj — The Situation Room (@CNNSitRoom) August 9, 2016 “It suggests either a very bad taste reference to political assassination and an attempt at humor or an incredible insensitivity … to the prevalence of a political assassination inside of American history and how that is a topic that we don’t ever come close to, even when we think we’re trying to be light-hearted,” the ex-CIA leader said.\", \"targets\": [{\"Input.gid\": \"allsides_1916_779_13_former CIA Director Michael Hayden_0_14\", \"from\": 0, \"to\": 14, \"mention\": \"Michael Hayden\", \"polarity\": 4.0, \"further_mentions\": [{\"from\": 498, \"to\": 515, \"mention\": \"the ex-CIA leader\"}, {\"from\": 0, \"to\": 23, \"mention\": \"Michael Hayden on Trump\"}]}]}\n{\"primary_gid\": \"polusa_v1_79062260_-1_56_Mr. Epstein_327_338\", \"sentence_normalized\": \"EPSTEIN'S FINANCIAL TRAIL TRACES BACK TO DEUTSCHE BANK — NYT's David Enrich and Jo Becker: \\\"As Deutsche Bank officials this year scrambled to extricate themselves from a yearslong relationship with Jeffrey Epstein, the wealthy financier charged this month with sex trafficking, they uncovered suspicious transactions in which Mr. Epstein had moved money out of the United States.\", \"targets\": [{\"Input.gid\": \"polusa_v1_79062260_-1_56_Mr. Epstein_327_338\", \"from\": 326, \"to\": 337, \"mention\": \"Mr. Epstein\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_4594072_-1_17_President Trump_14_29\", \"sentence_normalized\": \"Now, back to President Trump.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4594072_-1_17_President Trump_14_29\", \"from\": 13, \"to\": 28, \"mention\": \"President Trump\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"allsides_2866_1170_29_McCarthy_90_98\", \"sentence_normalized\": \"The decision to step down was closely held; Fox News is told House Majority Leader Kevin McCarthy, R-Calif., was only informed of Boehner's decision \\\"one minute\\\" before Boehner told the GOP conference.\", \"targets\": [{\"Input.gid\": \"allsides_2866_1170_29_McCarthy_90_98\", \"from\": 89, \"to\": 97, \"mention\": \"McCarthy\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"allsides_3373_1391_67_Mario Givens_41_47\", \"sentence_normalized\": \"The report also includes statements from Givens and another woman who was there that night, Yolonda Whitaker, said she saw Slager stun Givens \\\"for no reason.\\\"\", \"targets\": [{\"Input.gid\": \"allsides_3373_1391_67_Brown_115_118\", \"from\": 115, \"to\": 118, \"mention\": \"she\", \"polarity\": 4.0}, {\"Input.gid\": \"allsides_3373_1391_67_Mario Givens_41_47\", \"from\": 41, \"to\": 47, \"mention\": \"Givens\", \"polarity\": 4.0, \"further_mentions\": [{\"from\": 135, \"to\": 141, \"mention\": \"Givens\"}]}]}\n{\"primary_gid\": \"polusa_v1_115879353_-1_19_candidate Donald Trump_1_6\", \"sentence_normalized\": \"Trump Organization officials did not immediately respond to ABC News requests for comment.\", \"targets\": [{\"Input.gid\": \"polusa_v1_115879353_-1_19_candidate Donald Trump_1_6\", \"from\": 0, \"to\": 5, \"mention\": \"Trump\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_52922821_-1_3_Michel Martin_76_89\", \"sentence_normalized\": \"John Hickenlooper (D-Colo.) shares his response to the bill and tells NPR's Michel Martin about his own bipartisan plan he created with Gov.\", \"targets\": [{\"Input.gid\": \"polusa_v1_52922821_-1_3_Michel Martin_76_89\", \"from\": 76, \"to\": 89, \"mention\": \"Michel Martin\", \"polarity\": 4.0}, {\"Input.gid\": \"polusa_v1_52922821_-1_3_John Hickenlooper (D-Colo.)_0_27\", \"from\": 0, \"to\": 27, \"mention\": \"John Hickenlooper (D-Colo.)\", \"polarity\": 4.0, \"further_mentions\": [{\"from\": 120, \"to\": 122, \"mention\": \"he\"}, {\"from\": 35, \"to\": 38, \"mention\": \"his\"}, {\"from\": 96, \"to\": 99, \"mention\": \"his\"}]}]}\n{\"primary_gid\": \"allsides_1810_737_6_Powell_44_52\", \"sentence_normalized\": \"\\\"Yup, the whole birther movement was racist,\\\" Powell wrote, according to BuzzFeed.\", \"targets\": [{\"Input.gid\": \"allsides_1810_737_6_Powell_44_52\", \"from\": 44, \"to\": 52, \"mention\": \"\\\" Powell\", \"polarity\": 6.0, \"further_mentions\": [{\"from\": 46, \"to\": 52, \"mention\": \"Powell\"}]}]}\n{\"primary_gid\": \"polusa_v1_4168551_-1_26_Elizabeth Warren_1_7\", \"sentence_normalized\": \"Warren took to Twitter to tip her hat to Booker's selfie game after the two posed together with a young woman while campaigning last month in South Carolina.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4168551_-1_26_Elizabeth Warren_1_7\", \"from\": 0, \"to\": 6, \"mention\": \"Warren\", \"polarity\": 6.0}]}\n{\"primary_gid\": \"allsides_6243_2686_21_Mr. Romney_142_157\", \"sentence_normalized\": \"“We are shocked that, at a time when the United States of America is confronting the tragic death of one of our diplomatic officers in Libya, Governor Romney would choose to launch a political attack,” said Ben LaBolt, a campaign spokesman, early Wednesday morning.\", \"targets\": [{\"Input.gid\": \"allsides_6243_2686_21_Mr. Romney_142_157\", \"from\": 142, \"to\": 157, \"mention\": \"Governor Romney\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_4885368_-1_0_Deputy Australian Prime Minister Barnaby Joyce_0_46\", \"sentence_normalized\": \"Deputy Australian Prime Minister Barnaby Joyce resigns over sex scandal\", \"targets\": [{\"Input.gid\": \"polusa_v1_4885368_-1_0_Deputy Australian Prime Minister Barnaby Joyce_0_46\", \"from\": 0, \"to\": 46, \"mention\": \"Deputy Australian Prime Minister Barnaby Joyce\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_4021330_-1_16_Mr. Souza_78_87\", \"sentence_normalized\": \"Alice Gabriner, the international photo editor of Time Magazine, worked with Mr. Souza at the White House during the early years of Mr. Obama’s first term.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4021330_-1_16_Mr. Souza_78_87\", \"from\": 77, \"to\": 86, \"mention\": \"Mr. Souza\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"polusa_v1_53001849_-1_0_Austin_0_6\", \"sentence_normalized\": \"Austin Tice, Jounalist Held In Syria, Is Alive, White House Tells His Parents\", \"targets\": [{\"Input.gid\": \"polusa_v1_53001849_-1_0_Austin_0_6\", \"from\": 0, \"to\": 6, \"mention\": \"Austin\", \"polarity\": 4.0}, {\"Input.gid\": \"polusa_v1_53001849_-1_0_Jounalist Held_13_27\", \"from\": 13, \"to\": 27, \"mention\": \"Jounalist Held\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"polusa_v1_4345315_-1_18_Clay Aiken_4_7\", \"sentence_normalized\": \"But her credibility is totally shot.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4345315_-1_18_Clay Aiken_4_7\", \"from\": 4, \"to\": 7, \"mention\": \"her\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_5183_2192_27_Snowden lawyer Anatoly Kucherena_0_9\", \"sentence_normalized\": \"Kucherena said he is arranging the trip.\", \"targets\": [{\"Input.gid\": \"allsides_5183_2192_27_Snowden lawyer Anatoly Kucherena_0_9\", \"from\": 0, \"to\": 9, \"mention\": \"Kucherena\", \"polarity\": 4.0, \"further_mentions\": [{\"from\": 15, \"to\": 17, \"mention\": \"he\"}]}]}\n"
  },
  {
    "path": "NewsSentiment/controller_data/datasets/NewsMTSC-dataset/readme.md",
    "content": "# Welcome\n\nThe files contained in this archive are part of the dataset \"NewsMTSC\" described in our paper \"NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles\" published at the EACL 2021.\n\n## Dataset\n\n### Files\nThe dataset consists of three splits. In practical terms, we suggest to use the files as follows (more detailed information can be found in the paper):\n\n* `train.jsonl` - For **training**.\n* `devtest_mt.jsonl` - To evaluate a model's classification performance only on sentences that contain **at least two target mentions**. Note that the mentions were extracted to refer to different persons but in a few cases might indeed refer to the same person since we extracted them automatically.\n* `devtest_rw.jsonl` - To evaluate a model's classification performance on a \"**real-world**\" set of sentences, i.e., the set was created with the objective to resemble real-world distribution as to sentiment and other factors mentioned in the paper.\n\n\n### Format\nEach split is stored in a JSONL file. In JSONL, each line represents one JSON object. In our dataset, each JSON object consists of:\n\n1. `sentence_normalized`: a single sentence\n2. `primary_gid`: an identifier that is unique within NewsMTSC\n3. `targets`: one or more targets\n\nEach target in `targets` consists of:\n\n1. `Input.gid`: an identifier that is unique within NewsMTSC\n2. `from`: the character-based, 0-indexed position of the first character of the target's mention within `sentence_normalized`\n3. `to`: the last character of the target's mention\n4. `mention`: the text of the mention\n5. `polarity`: the sentiment of the sentence concerning the target's mention (2.0 = negative, 4.0 = neutral, 6.0 = positive)\n6. `further_mentions` (optional): one or more coreferential mentions of the target within the sentence. Note that these were extracted automatically and thus might be incorrecet or not be complete. Further, our annotators labeled the sentiment concerning the main mention, which - depending on the sentence - might not be identical to the sentiment of the coreferences.\n\n```\n{\n   \"primary_gid\":\"allsides_1192_476_17_— Judge Neil M. Gorsuch_126_139\",\n   \"sentence_normalized\":\"But neither side harbored any doubts, based on the judge’s opinions, other writings and the president who nominated him, that Judge Gorsuch would be a reliable conservative committed to following the original understanding of those who drafted and ratified the Constitution.\",\n   \"targets\":[\n      {\n         \"Input.gid\":\"allsides_1192_476_17_— Judge Neil M. Gorsuch_126_139\",\n         \"from\":126,\n         \"to\":139,\n         \"mention\":\"Judge Gorsuch\",\n         \"polarity\":6.0,\n         \"further_mentions\":[\n            {\n               \"from\":116,\n               \"to\":119,\n               \"mention\":\"him\"\n            }\n         ]\n      }\n   ]\n}\n```\n\n## Contact\n\nIf you want to get in touch, feel free to contact Felix Hamborg. If you find an issue with the dataset or model or have a question concerning either, please open an issue in the repository.\n\n* Web: [https://felix.hamborg.eu/](https://felix.hamborg.eu/)\n* Mail: [felix.hamborg@uni-konstanz.de](mailto:felix.hamborg@uni-konstanz.de)\n* Repository: [https://github.com/fhamborg/NewsMTSC](https://github.com/fhamborg/NewsMTSC)\n\n\n## How to cite\n\nIf you use the dataset or parts of it, please cite our paper:\n\n```\n@InProceedings{Hamborg2021b,\n  author    = {Hamborg, Felix and Donnay, Karsten},\n  title     = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles},\n  booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},\n  year      = {2021},\n  month     = {Apr.},\n  location  = {Virtual Event},\n}\n```\n"
  },
  {
    "path": "NewsSentiment/controller_data/datasets/NewsMTSC-dataset/train.jsonl",
    "content": "{\"primary_gid\": \"allsides_1000_401_25_Reality Leigh Winner_0_6\", \"sentence_normalized\": \"Winner wrote that she had a 30-minute private meeting with the Republican lawmaker’s state policy director.\", \"targets\": [{\"Input.gid\": \"allsides_1000_401_25_Reality Leigh Winner_0_6\", \"from\": 0, \"to\": 6, \"mention\": \"Winner\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"allsides_1000_401_3_Reality Leigh Winner_0_3\", \"sentence_normalized\": \"She also recently referred to President Trump as a “piece of shit” because of his position on the Dakota Access Pipeline (DAPL) protests.\", \"targets\": [{\"Input.gid\": \"allsides_1000_401_3_Reality Leigh Winner_0_3\", \"from\": 0, \"to\": 3, \"mention\": \"She\", \"polarity\": 2.0}, {\"Input.gid\": \"allsides_1000_401_3_’ Trump_30_45\", \"from\": 30, \"to\": 45, \"mention\": \"President Trump\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_1018_408_1_Hillary Clinton_2_17\", \"sentence_normalized\": \"Hillary Clinton blamed the Democratic National Committee, Facebook, and conspiracy site Infowars Wednesday for her election defeat during an interview in which she pointed at a total of 18 alleged guilty parties for her big loss.\", \"targets\": [{\"Input.gid\": \"allsides_1018_408_1_Hillary Clinton_2_17\", \"from\": 0, \"to\": 15, \"mention\": \"Hillary Clinton\", \"polarity\": 2.0, \"further_mentions\": [{\"from\": 216, \"to\": 219, \"mention\": \"her\"}, {\"from\": 160, \"to\": 163, \"mention\": \"she\"}, {\"from\": 111, \"to\": 114, \"mention\": \"her\"}]}, {\"Input.gid\": \"allsides_1018_408_1_Facebook_60_68\", \"from\": 58, \"to\": 66, \"mention\": \"Facebook\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_1018_408_8_Hillary Clinton_77_84\", \"sentence_normalized\": \"(RELATED: The 44 Most Damning Stories From WikiLeaks) During the same event, Clinton also attacked Facebook, Twitter bots, The New York Times, Steve Bannon, and the media in general.\", \"targets\": [{\"Input.gid\": \"allsides_1018_408_8_WikiLeaks_43_52\", \"from\": 43, \"to\": 52, \"mention\": \"WikiLeaks\", \"polarity\": 4.0}, {\"Input.gid\": \"allsides_1018_408_8_Hillary Clinton_77_84\", \"from\": 77, \"to\": 84, \"mention\": \"Clinton\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_1019_408_0_former Secretary of State Hillary Clinton_8_15\", \"sentence_normalized\": \"Hillary Clinton takes \\\"responsibility\\\" for loss, but says others contributed\", \"targets\": [{\"Input.gid\": \"allsides_1019_408_0_former Secretary of State Hillary Clinton_8_15\", \"from\": 8, \"to\": 15, \"mention\": \"Clinton\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_1019_408_9_former Secretary of State Hillary Clinton_0_7\", \"sentence_normalized\": \"Clinton also looked to social media, saying sites like Facebook and Twitter have been \\\"victimized by deliberate efforts to shape the conversation and push it towards conspiracies, lies, false information.\\\"\", \"targets\": [{\"Input.gid\": \"allsides_1019_408_9_former Secretary of State Hillary Clinton_0_7\", \"from\": 0, \"to\": 7, \"mention\": \"Clinton\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"allsides_101_41_7_President Donald Trump_0_5\", \"sentence_normalized\": \"Trump's unhinged Twitter attacks, frequent off-the-cuff remarks, slurring and very peculiar drinking habits have led to some psychiatrists, mental-health experts and administration critics to call the president's mental stability into question, as the Salon video below notes.\", \"targets\": [{\"Input.gid\": \"allsides_101_41_7_President Donald Trump_0_5\", \"from\": 0, \"to\": 5, \"mention\": \"Trump\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_102_41_18_Bill Clinton_0_15\", \"sentence_normalized\": \"Hillary Clinton continues to face fire for alleged pay-for-play schemes involving her work while secretary at the State Department and simultaneous affiliation with the Clinton Foundation, and for the curious Uranium One dealings with Russia she helped shape while serving under Barack Obama.\", \"targets\": [{\"Input.gid\": \"allsides_102_41_18_Bill Clinton_0_15\", \"from\": 0, \"to\": 15, \"mention\": \"Hillary Clinton\", \"polarity\": 2.0, \"further_mentions\": [{\"from\": 242, \"to\": 245, \"mention\": \"she\"}, {\"from\": 82, \"to\": 85, \"mention\": \"her\"}]}]}\n{\"primary_gid\": \"allsides_1031_412_3_Donald Trump's_0_5\", \"sentence_normalized\": \"Trump accepted Dubke’s offer to stay while on his first overseas trip as president this month.\", \"targets\": [{\"Input.gid\": \"allsides_1031_412_3_Donald Trump's_0_5\", \"from\": 0, \"to\": 5, \"mention\": \"Trump\", \"polarity\": 4.0, \"further_mentions\": [{\"from\": 46, \"to\": 49, \"mention\": \"his\"}]}]}\n{\"primary_gid\": \"allsides_1031_412_7_Donald Trump's_94_99\", \"sentence_normalized\": \"“The reasons for my departure are personal, but it has been my great honor to serve President Trump and this administration,” Dubke, 47, wrote in an email to friends, according to Politico.\", \"targets\": [{\"Input.gid\": \"allsides_1031_412_7_Donald Trump's_94_99\", \"from\": 94, \"to\": 99, \"mention\": \"Trump\", \"polarity\": 6.0}]}\n{\"primary_gid\": \"allsides_1037_415_1_President Donald Trump_0_24\", \"sentence_normalized\": \"President Donald Trump hurled more jabs at the \\\"fake news media\\\" Sunday morning, describing White House \\\"leaks\\\" as \\\"fabricated lies\\\" and saying stories with \\\"sources say\\\" make it \\\"very possible\\\" those \\\"sources don't exist\\\" and are made up by \\\"fake news writers.\\\"\", \"targets\": [{\"Input.gid\": \"allsides_1037_415_1_President Donald Trump_0_24\", \"from\": 0, \"to\": 22, \"mention\": \"President Donald Trump\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_1039_415_17_Trump_30_39\", \"sentence_normalized\": \"It was a familiar morning for Mr. Trump on his favored medium — and for a nation that had, for a little more than a week, gone without the president’s stream-of-consciousness missives.\", \"targets\": [{\"Input.gid\": \"allsides_1039_415_17_Trump_30_39\", \"from\": 30, \"to\": 39, \"mention\": \"Mr. Trump\", \"polarity\": 2.0, \"further_mentions\": [{\"from\": 43, \"to\": 46, \"mention\": \"his\"}]}, {\"Input.gid\": \"allsides_1039_415_17_Mr. Corker_30_39\", \"from\": 30, \"to\": 39, \"mention\": \"Mr. Trump\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"allsides_1039_415_28_Sunday_17_23\", \"sentence_normalized\": \"But he seemed on Sunday to be as aggrieved as ever by what he considers unfair news coverage.\", \"targets\": [{\"Input.gid\": \"allsides_1039_415_28_Sunday_17_23\", \"from\": 17, \"to\": 23, \"mention\": \"Sunday\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"allsides_1042_416_12_Mr. Trump_59_70\", \"sentence_normalized\": \"“The leaders did want to know what his time frame was, and [Mr. Trump] said, look, ‘This is something where I want to get to the right decision.\", \"targets\": [{\"Input.gid\": 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  },
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  },
  {
    "path": "NewsSentiment/controller_data/datasets/newsmtsc-train-and-test-mt/devtest_mtsc_only.jsonl",
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\"polusa_v1_4503577_-1_18_“Mr. Cohen_26_39\", \"sentence_normalized\": \"TRUMP FIRES BROADSIDE AT MICHAEL COHEN, DENIES CLAIM ON MEETING WITH RUSSIAN LAWYER\\nOver the weekend, Davis clarified his claims.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4503577_-1_18_President Trump_1_6\", \"from\": 0, \"to\": 5, \"mention\": \"TRUMP\", \"polarity\": 2.0}, {\"Input.gid\": \"polusa_v1_4503577_-1_18_“Mr. Cohen_26_39\", \"from\": 25, \"to\": 38, \"mention\": \"MICHAEL COHEN\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_4519718_-1_39_Michael Cohen_33_38\", \"sentence_normalized\": \"Then you’d claim that Trump and Cohen violated campaign finance law because they didn’t publicly disclose those payments, despite the fact that disclosing them would nullify the reason for making them in the first place --which was to keep the whole thing secret.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4519718_-1_39_President Trump_23_28\", \"from\": 22, \"to\": 27, \"mention\": \"Trump\", 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Assistant Director Peter Strzok damaged the integrity of the entire Clinton email probe, Horowitz writes.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4525031_-1_6_Clinton_117_124\", \"from\": 117, \"to\": 124, \"mention\": \"Clinton\", \"polarity\": 2.0}, {\"Input.gid\": \"polusa_v1_4525031_-1_6_Strzok_29_35\", \"from\": 29, \"to\": 35, \"mention\": \"Strzok\", \"polarity\": 2.0}]}\n{\"primary_gid\": \"polusa_v1_4537616_-1_4_Zulfikar Ali Bhutto_1262_1281\", \"sentence_normalized\": \"A timeline of major political and other events in Pakistan's history:\\n__Aug. 14, 1947: Pakistan emerges as a sovereign state after getting independence when the departing British left India and split the subcontinent;\\n__Sept. 11, 1948: Pakistan's founder Mohammad Ali Jinnah dies;\\n__Oct. 16, 1951: Pakistan first prime minister, Liaquat Ali Khan, is assassinated in a gun attack at a rally in the city of Rawalpind, triggering political instability;\\n__Oct. 7, 1958: President Iskander Mirza abolishes the constitution and declares martial law; Gen. Muhammad Ayub Khan, then army chief becomes administrator;\\n__Oct. 27, 1958: Ayub forces the president to step down; Mirza is sent to exile in Britain where he later dies; Ayub declared himself president;\\n__March 25, 1969: After months of rioting in West and East Pakistan, Khan hands over power to army chief Gen. Agha Mohammed Yahya Khan;\\n__Dec. 7, 1970: East Pakistan-based Awami League wins general elections; Yahya Khan delays transfer of power, triggering widespread rioting in East Pakistan; civil war breaks out;\\n__Dec. 16, 1971: Pakistan troops surrender in East Pakistan after Indian armed intervention in the civil war; East Pakistan becomes independent Bangladesh;\\n__Dec. 20, 1971: Yahya Khan resigns, Zulfikar Ali Bhutto becomes president; a parliamentary system of government is adopted and Bhutto becomes prime minister;\\n__July 5, 1977: Army chief Gen. 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Martin, Jr., Morrison Professor of American History and Citizenship Robin Einhorn, Preston Hotchkis Professor in the History of the United States Kristin Hanson, Associate Professor, English Patricia Baquedano-Lopez, Associate Professor of Education Joseph Wolf, Professor Emeritus, Mathematics You-tien Hsing, Professor, Geography Glynda Hull, Professor, Education Richard B. Norgaard, Professor Emeritus of Energy and Resources Ellen L. Simms, Professor of Integrative Biology Katherine Snyder, Associate Professor, Department of English Kathleen Donegan, Associate Professor, Department of English and Associate Dean of Arts and Humanities Trinh T. Minh-ha, Professor of Rhetoric and of Gender & Women’s Studies Suzanne Guerlac, Professor, Department of French Mel Y. Chen, Associate Professor, Department of Gender and Women’s Studies Margaret W. Conkey, Department of Anthropology Darcy Grimaldo Grigsby, Professor, History of Art Mariane C Ferme, Professor, Department of Anthropology Lyn Hejinian, John F Hotchkis Professor of English Michael Watts, Professor Emeritus, Geography Antonio Montalban, Associate Professor, Mathematics Samera Esmeir, Associate Professor, Rhetoric Louise Fortmann, Professor Emerita, Dept of Environmental Science, Policy and Management Joseph Lavery, Assistant Professor, Dept. of English Lynn Huntsinger, Professor, Dept Environmental Science, Policy, and Management Ramona Naddaff, Associate Professor, Rhetoric Daniel Boyarin, Taubman Professor of Talmudic Culture, Near Eastern Studies and Rhetoric Gillian Hart, Professor Emerita, Geography Charles C. 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\"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"battery life\", \"polarity\": 6, \"from\": 4, \"to\": 16}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the battery life is excellent , the display is excellent , and downloading apps is a breeze .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"display\", \"polarity\": 6, \"from\": 36, \"to\": 43}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the battery life is excellent , the display is excellent , and downloading apps is a breeze .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"downloading apps\", \"polarity\": 6, \"from\": 63, \"to\": 79}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the screen , the software and the smoothness of the operating system .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"screen\", \"polarity\": 6, \"from\": 4, \"to\": 10}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the screen , the software and the smoothness of the operating system .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"software\", \"polarity\": 6, \"from\": 17, \"to\": 25}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the screen , the software and the smoothness of the operating system .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"operating system\", \"polarity\": 6, \"from\": 52, \"to\": 68}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i have dropped mine a couple times with only a slim plastic case covering it .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"slim plastic case\", \"polarity\": 4, \"from\": 47, \"to\": 64}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i also made a recovery usb stick .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"recovery usb stick\", \"polarity\": 4, \"from\": 14, \"to\": 32}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"but with this laptop , the bass is very weak and the sound comes out sounding tinny .\", \"targets\": [{\"Input.gid\": 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\"mention\": \"bluetooth interface\", \"polarity\": 2, \"from\": 37, \"to\": 56}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"further , this mac mini has a sloppy bluetooth interface -lrb- courtesy of the mac os -rrb- and the range is poor .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"mac os\", \"polarity\": 2, \"from\": 79, \"to\": 85}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"further , this mac mini has a sloppy bluetooth interface -lrb- courtesy of the mac os -rrb- and the range is poor .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"range\", \"polarity\": 2, \"from\": 100, \"to\": 105}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"if you start on the far right side and scroll to your left the start menu will automatically come up .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"start menu\", \"polarity\": 4, \"from\": 63, \"to\": 73}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"my only gripe would be the 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800 which in my experience works better then usb3 -lrb- in pc enabled with usb3 -rrb- i was not originally sold on the mac os i felt it was inferior in many ways to windows 7 .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"windows 7\", \"polarity\": 6, \"from\": 201, \"to\": 210}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i like itunes , the apparent security , the mini form factor , all the nice graphics stuff .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"itunes\", \"polarity\": 6, \"from\": 7, \"to\": 13}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i like itunes , the apparent security , the mini form factor , all the nice graphics stuff .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"security\", \"polarity\": 6, \"from\": 29, \"to\": 37}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i like itunes , the apparent security , the mini form factor , all the nice graphics stuff .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"mini form factor\", \"polarity\": 6, \"from\": 44, \"to\": 60}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i like itunes , the apparent security , the mini form factor , all the nice graphics stuff .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"graphics stuff\", \"polarity\": 6, \"from\": 76, \"to\": 90}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the first time i used the card reader it took half an hour and a pair of tweezers to remove the card .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"card reader\", \"polarity\": 2, \"from\": 26, \"to\": 37}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the first time i used the card reader it took half an hour and a pair of tweezers to remove the card .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"remove the card\", \"polarity\": 2, \"from\": 85, \"to\": 100}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"after replacing the spinning hard disk with an 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\"sentence_normalized\": \"with the needs of a professional photographer i generally need to keep up with the best specs .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"specs\", \"polarity\": 4, \"from\": 88, \"to\": 93}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \" packing and everything was perfect\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"packing\", \"polarity\": 6, \"from\": 1, \"to\": 8}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i called toshiba where i gave them the serial number and they informed me that they were having issues with the mother boards .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"mother boards\", \"polarity\": 4, \"from\": 112, \"to\": 125}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i seem to be having repeat problems as the mother board in this one is diagnosed as faulty , related to the graphics card .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"mother board\", \"polarity\": 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107}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"it also comes with 4g of ram but if you 're like me you want to max that out so i immediately put 8g of ram in her and i 've never used a computer that performs better .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"performs\", \"polarity\": 6, \"from\": 152, \"to\": 160}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"this computer is also awesome for my sons virtual home schooling .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"virtual home schooling\", \"polarity\": 6, \"from\": 42, \"to\": 64}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \" cost is more as compared to other brands .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"cost\", \"polarity\": 2, \"from\": 1, \"to\": 5}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"also ... - excellent operating system - size and weight for optimal mobility - excellent durability of the battery - the functions provided by the trackpad is unmatched by any other brand -\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"operating system\", \"polarity\": 6, \"from\": 21, \"to\": 37}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"also ... - excellent operating system - size and weight for optimal mobility - excellent durability of the battery - the functions provided by the trackpad is unmatched by any other brand -\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"size\", \"polarity\": 6, \"from\": 40, \"to\": 44}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"also ... - excellent operating system - size and weight for optimal mobility - excellent durability of the battery - the functions provided by the trackpad is unmatched by any other brand -\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"weight\", \"polarity\": 6, \"from\": 49, \"to\": 55}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"also ... - excellent operating system - size and weight for optimal 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155}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"this hardware seems to be better than the imac in that it is n't $ 1400 and smaller .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"hardware\", \"polarity\": 6, \"from\": 5, \"to\": 13}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 've had it for about 2 months now and found no issues with software or updates .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"software\", \"polarity\": 4, \"from\": 61, \"to\": 69}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 've had it for about 2 months now and found no issues with software or updates .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"updates\", \"polarity\": 4, \"from\": 73, \"to\": 80}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the latest version does not have a disc drive .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"disc drive\", \"polarity\": 4, \"from\": 35, \"to\": 45}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \" screen - although some people might complain about low res which i think is ridiculous .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"screen\", \"polarity\": 6, \"from\": 1, \"to\": 7}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"screen - although some people might complain about low res which i think is ridiculous .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"res\", \"polarity\": 6, \"from\": 55, \"to\": 58}]}\n"
  },
  {
    "path": "NewsSentiment/controller_data/datasets/semeval14laptops/Laptops_Train.xml.seg.jsonl",
    "content": "{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i charge it at night and skip taking the cord with me because of the good battery life .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"cord\", \"polarity\": 4, \"from\": 41, \"to\": 45}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i charge it at night and skip taking the cord with me because of the good battery life .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"battery life\", \"polarity\": 6, \"from\": 74, \"to\": 86}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the tech guy then said the service center does not do 1-to-1 exchange and i have to direct my concern to the `` sales '' team , which is the retail shop which i bought my netbook from .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"service center\", \"polarity\": 2, \"from\": 27, \"to\": 41}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the tech guy then said the service center does not do 1-to-1 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\"sentence_normalized\": \"it is of high quality , has a killer gui , is extremely stable , is highly expandable , is bundled with lots of very good applications , is easy to use , and is absolutely gorgeous .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"gui\", \"polarity\": 6, \"from\": 37, \"to\": 40}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"it is of high quality , has a killer gui , is extremely stable , is highly expandable , is bundled with lots of very good applications , is easy to use , and is absolutely gorgeous .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"applications\", \"polarity\": 6, \"from\": 122, \"to\": 134}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"it is of high quality , has a killer gui , is extremely stable , is highly expandable , is bundled with lots of very good applications , is easy to use , and is absolutely gorgeous .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"use\", \"polarity\": 6, \"from\": 148, \"to\": 151}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"easy to start up and does not overheat as much as other laptops .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"start up\", \"polarity\": 6, \"from\": 8, \"to\": 16}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i even got my teenage son one , because of the features that it offers , like , ichat , photobooth , garage band and more !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"features\", \"polarity\": 6, \"from\": 47, \"to\": 55}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i even got my teenage son one , because of the features that it offers , like , ichat , photobooth , garage band and more !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"ichat\", \"polarity\": 6, \"from\": 80, \"to\": 85}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i even got my teenage son one , because of the features that it offers , like , ichat , photobooth , garage band and more !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"photobooth\", \"polarity\": 6, \"from\": 88, \"to\": 98}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i even got my teenage son one , because of the features that it offers , like , ichat , photobooth , garage band and more !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"garage band\", \"polarity\": 6, \"from\": 101, \"to\": 112}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"great laptop that offers many great features !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"features\", \"polarity\": 6, \"from\": 36, \"to\": 44}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"one night i turned the freaking thing off after using it , the next day i turn it on , no gui , screen all dark , power light steady , hard drive light steady and not flashing as it usually does .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"gui\", \"polarity\": 2, \"from\": 90, \"to\": 93}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"one night i turned the freaking thing off after using it , the next day i turn it on , no gui , screen all dark , power light steady , hard drive light steady and not flashing as it usually does .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"screen\", \"polarity\": 2, \"from\": 96, \"to\": 102}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"one night i turned the freaking thing off after using it , the next day i turn it on , no gui , screen all dark , power light steady , hard drive light steady and not flashing as it usually does .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"power light\", \"polarity\": 4, \"from\": 114, \"to\": 125}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"one night i turned the freaking thing off after using it , the next day i turn it on , no gui , screen all dark , power light steady , hard drive ligh t steady and not flashing as it usually does .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"hard drive ligh\", \"polarity\": 2, \"from\": 135, \"to\": 150}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"my only disappointment with the 13 '' model is that they 're the only ones in the macbook pro line up without an i5 or i7 processor and dual graphics cards , however the trade-off is that you achieve a longer battery life -lrb- of about 2 more hours -rrb- .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"processor\", \"polarity\": 2, \"from\": 122, \"to\": 131}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"my only disappointment with the 13 '' model is that they 're the only ones in the macbook pro line up without an i5 or i7 processor and dual graphics cards , however the trade-off is that you achieve a longer battery life -lrb- of about 2 more hours -rrb- .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"graphics cards\", \"polarity\": 2, \"from\": 141, \"to\": 155}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"my only disappointment with the 13 '' model is that they 're the only ones in the macbook pro line up without an i5 or i7 processor and dual graphics cards , however the trade-off is that you achieve a longer battery life -lrb- of about 2 more hours -rrb- .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"battery life\", \"polarity\": 6, \"from\": 209, \"to\": 221}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i took it back for an asus and same thing - blue screen which required me to remove the battery to reset .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"battery\", \"polarity\": 4, \"from\": 88, \"to\": 95}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"in the shop , these macbooks are encased in a soft rubber enclosure - so you will never know about the razor edge until you buy it , get it home , break the seal and use it -lrb- very clever con -rrb- .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": 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am more than satisfied .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"speed\", \"polarity\": 6, \"from\": 4, \"to\": 9}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"this laptop meets every expectation and windows 7 is great !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"windows 7\", \"polarity\": 6, \"from\": 40, \"to\": 49}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i can barely use any usb devices because they will not stay connected properly .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"usb devices\", \"polarity\": 2, \"from\": 21, \"to\": 32}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"when i finally had everything running with all my software installed i plugged in my droid to recharge and the system crashed .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"software\", \"polarity\": 4, \"from\": 50, \"to\": 58}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"when i finally had everything running 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\"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"30\\\" hd monitor\", \"polarity\": 6, \"from\": 32, \"to\": 46}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i also got the added bonus of a 30 '' hd monitor , which really helps to extend my screen and keep my eyes fresh !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"screen\", \"polarity\": 4, \"from\": 83, \"to\": 89}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the machine is slow to boot up and occasionally crashes completely .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"boot up\", \"polarity\": 2, \"from\": 23, \"to\": 30}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"after paying several hundred dollars for this service , it is frustrating that you can not get help after hours .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"service\", \"polarity\": 2, \"from\": 46, \"to\": 53}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i love the operating system and 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  },
  {
    "path": "NewsSentiment/controller_data/datasets/semeval14restaurants/Restaurants_Test_Gold.xml.seg.jsonl",
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\"polarity\": 4, \"from\": 47, \"to\": 71}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i stopped by for some brunch today and had the vegan cranberry pancakes and some rice milk .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"rice milk\", \"polarity\": 4, \"from\": 81, \"to\": 90}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"sweet irish bartender is always happy and able to bring a smile to my friends a my face .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"bartender\", \"polarity\": 6, \"from\": 12, \"to\": 21}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"its good to go there for drinks if you do n't want to get drunk because you 'll be lucky if you can get one drink an hour the service is so bad .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"service\", \"polarity\": 2, \"from\": 126, \"to\": 133}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"its good to go there for drinks if you do n't want to get drunk because you 'll be lucky if you can get one drink an hour the service is so bad .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"drink\", \"polarity\": 4, \"from\": 108, \"to\": 113}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"its good to go there for drinks if you do n't want to get drunk because you 'll be lucky if you can get one drink an hour the service is so bad .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"drinks\", \"polarity\": 4, \"from\": 25, \"to\": 31}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"anyway , the owner was fake .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"owner\", \"polarity\": 2, \"from\": 13, \"to\": 18}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \" owner is pleasant and entertaining .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"owner\", \"polarity\": 6, \"from\": 1, \"to\": 6}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i have never in my life sent back food before , 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1, \"to\": 18}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"creamy appetizers -- taramasalata , eggplant salad , and greek yogurt -lrb- with cuccumber , dill , and garlic -rrb- taste excellent when on warm pitas .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"warm pitas\", \"polarity\": 4, \"from\": 141, \"to\": 151}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"creamy appetizers -- taramasalata , eggplant salad , and greek yogurt -lrb- with cuccumber , dill , and garlic -rrb- taste excellent when on warm pitas .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"taramasalata\", \"polarity\": 6, \"from\": 21, \"to\": 33}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"creamy appetizers -- taramasalata , eggplant salad , and greek yogurt -lrb- with cuccumber , dill , and garlic -rrb- taste excellent when on warm pitas .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"eggplant salad\", \"polarity\": 6, \"from\": 36, \"to\": 50}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"creamy appetizers -- taramasalata , eggplant salad , and greek yogurt (with cuccumber, dill, and garlic) taste excellent when on warm pitas .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"greek yogurt (with cuccumber, dill, and garlic)\", \"polarity\": 6, \"from\": 57, \"to\": 104}]}\n"
  },
  {
    "path": "NewsSentiment/controller_data/datasets/semeval14restaurants/Restaurants_Train.xml.seg.jsonl",
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whatever you feel like eating , whether it 's on the menu or not .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"kitchen\", \"polarity\": 6, \"from\": 56, \"to\": 63}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the food is uniformly exceptional , with a very capable kitchen which will proudly whip up whatever you feel like eating , whether it 's on the menu or not .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"menu\", \"polarity\": 4, \"from\": 144, \"to\": 148}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"not only was the food outstanding , but the little ` perks ' were great .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"food\", \"polarity\": 6, \"from\": 17, \"to\": 21}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"not only was the food outstanding , but the little ' perks ' were great .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"perks\", \"polarity\": 6, \"from\": 53, \"to\": 58}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"our agreed favorite is the orrechiete with sausage and chicken -lrb- usually the waiters are kind enough to split the dish in half so you get to sample both meats -rrb- .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"orrechiete with sausage and chicken\", \"polarity\": 6, \"from\": 27, \"to\": 62}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"our agreed favorite is the orrechiete with sausage and chicken -lrb- usually the waiters are kind enough to split the dish in half so you get to sample both meats -rrb- .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"waiters\", \"polarity\": 6, \"from\": 81, \"to\": 88}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"our agreed favorite is the orrechiete with sausage and chicken -lrb- usually the waiters are kind enough to split the dish in half so you get to sample both meats -rrb- .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"meats\", \"polarity\": 4, \"from\": 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\"-1\", \"sentence_normalized\": \"honestly the worst sushi my husband and i had in our entire lives .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"sushi\", \"polarity\": 2, \"from\": 19, \"to\": 24}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"however , if you want great food at a great price and do n't mind the decor , you ca n't beat this place .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"food\", \"polarity\": 6, \"from\": 28, \"to\": 32}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"however , if you want great food at a great price and do n't mind the decor , you ca n't beat this place .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"price\", \"polarity\": 6, \"from\": 44, \"to\": 49}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"however , if you want great food at a great price and do n't mind the decor , you ca n't beat this place .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"decor\", \"polarity\": 2, \"from\": 70, \"to\": 75}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"what makes this restaurant special are the authentic sichuan cooking and being the only one in nyc that offers authentic chongqing hotpot .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"sichuan cooking\", \"polarity\": 6, \"from\": 53, \"to\": 68}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"what makes this restaurant special are the authentic sichuan cooking and being the only one in nyc that offers authentic chongqing hotpot .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"chongqing hotpot\", \"polarity\": 6, \"from\": 121, \"to\": 137}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"our tiny table for two -lrb- dinner plates hung over edge -rrb- was right in the middle of one of the lanes of waiter traffic .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"table\", \"polarity\": 2, \"from\": 9, \"to\": 14}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"our tiny table for two -lrb- dinner plates hung over edge -rrb- was right in the middle of one of the lanes of waiter traffic .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"waiter traffic\", \"polarity\": 2, \"from\": 111, \"to\": 125}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"our tiny table for two -lrb- dinner plates hung over edge -rrb- was right in the middle of one of the lanes of waiter traffic .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"dinner plates\", \"polarity\": 2, \"from\": 29, \"to\": 42}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"sake collection was excellent -lrb- try nanbu bijin -rrb- , but pricy .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"nanbu bijin\", \"polarity\": 6, \"from\": 40, \"to\": 51}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"interesting other dishes for a change include chicken in curry sauce and salmon caserole .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"dishes\", \"polarity\": 6, \"from\": 18, \"to\": 24}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"interesting other dishes for a change include chicken in curry sauc e and salmon caserole .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"chicken in curry sauc\", \"polarity\": 6, \"from\": 46, \"to\": 67}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"interesting other dishes for a change include chicken in curry sauce and salmon caserole .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"salmon caserole\", \"polarity\": 6, \"from\": 73, \"to\": 88}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"one of my favorites though was the angry lobster , a cold lobster salad that was magnificent .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"angry lobster\", \"polarity\": 6, \"from\": 35, \"to\": 48}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"one of my favorites though was the angry lobster , a cold lobster salad that was magnificent .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"cold lobster salad\", \"polarity\": 6, \"from\": 53, \"to\": 71}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"ask for usha , the nicest bartender in manhattan .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"bartender\", \"polarity\": 6, \"from\": 26, \"to\": 35}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the service is outstanding and my crab-cake eggs benedict could not have been better .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"service\", \"polarity\": 6, \"from\": 4, \"to\": 11}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the service is outstanding and my crab-cake eggs benedict could not have been better .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"crab-cake eggs benedict\", \"polarity\": 6, \"from\": 34, \"to\": 57}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the place 's decor and hidden bathrooms made for a good laugh .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"decor\", \"polarity\": 6, \"from\": 13, \"to\": 18}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the place 's decor and hidden bathrooms made for a good laugh .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"bathrooms\", \"polarity\": 6, \"from\": 30, \"to\": 39}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"its location is good and the fact that hutner college is near and their prices are very reasonable , makes students go back to suan again and again .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"location\", \"polarity\": 6, \"from\": 4, \"to\": 12}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"its location is good and the fact that hutner college is near and their prices are very reasonable , makes students go back to suan again and again .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"prices\", \"polarity\": 6, \"from\": 72, \"to\": 78}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"a wonderful place !\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"place\", \"polarity\": 6, \"from\": 12, \"to\": 17}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \" deliveries often take up to an hour and the prices are higher than most other pizzerias in the area .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"deliveries\", \"polarity\": 2, \"from\": 1, \"to\": 11}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"deliveries often take up to an hour and the prices are higher than most other pizzerias in the area .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"prices\", \"polarity\": 2, \"from\": 44, \"to\": 50}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"kind of a small place but i guess if they are not too busy might be able to fit a group or kids .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"place\", \"polarity\": 2, \"from\": 16, \"to\": 21}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we also ordered two hot dogs thinking they would be pretty good since there is a whole section on the menu devoted to them .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"hot dogs\", \"polarity\": 4, \"from\": 20, \"to\": 28}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we also ordered two hot dogs thinking they would be pretty good since there is a whole section on the menu devoted to them .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"menu\", \"polarity\": 4, \"from\": 102, \"to\": 106}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 've had the chicken with garlic sauce , chicken with black bean sauce , and hunan chicken .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"chicken with garlic sauce\", \"polarity\": 4, \"from\": 14, \"to\": 39}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 've had the chicken with garlic sauce , chicken with black bean sauce , and hunan chicken .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"chicken with black bean sauce\", \"polarity\": 4, \"from\": 42, \"to\": 71}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 've had the chicken with garlic sauce , chicken with black bean sauce , and hunan chicken .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"hunan chicken\", \"polarity\": 4, \"from\": 78, \"to\": 91}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"because of the delicate thin crust , take-out pies get soggy in their boxes .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"take-out pies\", \"polarity\": 2, \"from\": 37, \"to\": 50}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"because of the delicate thin crust , take-out pies get soggy in their boxes .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"crust\", \"polarity\": 2, \"from\": 29, \"to\": 34}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the dish had like 6 pieces of beef in it .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"dish\", \"polarity\": 4, \"from\": 4, \"to\": 8}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the dish had like 6 pieces of beef in it .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"beef\", \"polarity\": 4, \"from\": 30, \"to\": 34}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we got in line and were served while in line a bannan fritter .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"bannan fritter\", \"polarity\": 4, \"from\": 47, \"to\": 61}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we got in line and were served while in line a bannan fritter .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"served\", \"polarity\": 4, \"from\": 24, \"to\": 30}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"it might have been a little too spicy for my friend , which you can couteract with eat more rice and keeping water on hand .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"rice\", \"polarity\": 4, \"from\": 92, \"to\": 96}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"it might have been a little too spicy for my friend , which you can couteract with eat more rice and keeping water on hand .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"water\", \"polarity\": 4, \"from\": 109, \"to\": 114}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"this place is always very crowded and popular .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"place\", \"polarity\": 6, \"from\": 5, \"to\": 10}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \" appetizers are somewhere around $ 7 each and the main dishes are between $ 11 and $ 16 .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"appetizers\", \"polarity\": 4, \"from\": 1, \"to\": 11}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"appetizers are somewhere around $ 7 each and the main dishes are between $ 11 and $ 16 .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"main dishes\", \"polarity\": 4, \"from\": 49, \"to\": 60}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"my wife and i went to orsay for valentine 's dinner .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"dinner\", \"polarity\": 4, \"from\": 45, \"to\": 51}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i do n't know about you guys , but when i go somewhere to eat i go for the food not for the atmosphere .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"food\", \"polarity\": 4, \"from\": 75, \"to\": 79}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i do n't know about you guys , but when i go somewhere to eat i go for the food not for the atmosphere .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"atmosphere\", \"polarity\": 4, \"from\": 92, \"to\": 102}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"a gentleman , maybe the manager , came to our table , and without so much as a smile or greeting asked for our order .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"manager\", \"polarity\": 2, \"from\": 24, \"to\": 31}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"a gentleman , maybe the manager , came to our table , and without so much as a smile or greeting asked for our order .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"gentleman\", \"polarity\": 2, \"from\": 2, \"to\": 11}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"a gentleman , maybe the manager , came to our table , and without so much as a smile or greeting asked for our order .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"table\", \"polarity\": 4, \"from\": 46, \"to\": 51}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we were tired and cold when we got to the restaurant , then we sat down to begin ordering appetizers .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"appetizers\", \"polarity\": 4, \"from\": 90, \"to\": 100}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 've had pizza both times and the caprese salad appetizer .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"pizza\", \"polarity\": 4, \"from\": 10, \"to\": 15}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 've had pizza both times and the caprese salad appetizer .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"caprese salad appetizer\", \"polarity\": 4, \"from\": 35, \"to\": 58}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"he was terribly thirsty after the meal too .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"meal\", \"polarity\": 2, \"from\": 34, \"to\": 38}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i was n't there for the half-price saturday night special , but tuesday night .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"half-price saturday night special\", \"polarity\": 4, \"from\": 24, \"to\": 57}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"if you like the food and the value you get from some of chinatown restaurants , this is not the place for you .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"food\", \"polarity\": 4, \"from\": 16, \"to\": 20}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"if you like the food and the value you get from some of chinatown restaurants , this is not the place for you .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"value\", \"polarity\": 4, \"from\": 29, \"to\": 34}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the selection changes frequently but the basic dishes are always available .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"selection\", \"polarity\": 4, \"from\": 4, \"to\": 13}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the selection changes frequently but the basic dishes are always available .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"basic dishes\", \"polarity\": 4, \"from\": 41, \"to\": 53}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"get the soup and a nosh -lrb- pastrami sandwich -rrb- for $ 8 and you 're golden .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"soup\", \"polarity\": 6, \"from\": 8, \"to\": 12}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"get the soup and a nosh (pastrami sandwich) for $ 8 and you 're golden .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"nosh (pastrami sandwich)\", \"polarity\": 6, \"from\": 19, \"to\": 43}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i have to say that if this what makes it easier to get a saet a lunch - i dont mind .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"lunch\", \"polarity\": 4, \"from\": 64, \"to\": 69}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"my family and i ate here last night for our annual christmas dinner with the family members who would rather spend the holidays with friends out-of-town .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"christmas dinner\", \"polarity\": 4, \"from\": 51, \"to\": 67}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i grew up on these bagels .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"bagels\", \"polarity\": 6, \"from\": 19, \"to\": 25}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we were told that they were booked solid and no other table was available .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"table\", \"polarity\": 2, \"from\": 54, \"to\": 59}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the restaraurant is very small so reservations are a must .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"reservations\", \"polarity\": 4, \"from\": 34, \"to\": 46}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"to my right , the hostess stood over a busboy and hissed rapido , rapido as he tried to clear and re-set a table for six .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"hostess\", \"polarity\": 2, \"from\": 18, \"to\": 25}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"to my right , the hostess stood over a busboy and hissed rapido , rapido as he tried to clear and re-set a table for six .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"busboy\", \"polarity\": 4, \"from\": 39, \"to\": 45}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"to my right , the hostess stood over a busboy and hissed rapido , rapido as he tried to clear and re-set a table for six .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"table\", \"polarity\": 4, \"from\": 107, \"to\": 112}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"after dealing with subpar pizza all over the kensington neighborhood - i 've found little toninos .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"pizza\", \"polarity\": 2, \"from\": 26, \"to\": 31}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"then we ordered a dinosaur rolls and white tuna sashimi .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"dinosaur rolls\", \"polarity\": 4, \"from\": 18, \"to\": 32}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"then we ordered a dinosaur rolls and white tuna sashimi .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"white tuna sashimi\", \"polarity\": 4, \"from\": 37, \"to\": 55}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i 'm partial to the gnocchi .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"gnocchi\", \"polarity\": 6, \"from\": 20, \"to\": 27}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"they were able to squeeze me in at 6 after i called the night before my anniversary for a friday night reservation and told me they 'd treat us well for the occasion .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"reservation\", \"polarity\": 4, \"from\": 103, \"to\": 114}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"note that they do not serve beer , you must bring your own .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"beer\", \"polarity\": 2, \"from\": 28, \"to\": 32}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we ate outside at haru 's sake bar because haru 's restaurant next door was overflowing .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"bar\", \"polarity\": 4, \"from\": 31, \"to\": 34}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"the service was typical short-order , dinner type .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"service\", \"polarity\": 4, \"from\": 4, \"to\": 11}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we shared a bottle of sake , an order of edamames , and she had the sushi plate while i had the sashimi .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"bottle of sake\", \"polarity\": 4, \"from\": 12, \"to\": 26}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we shared a bottle of sake , an order of edamames , and she had the sushi plate while i had the sashimi .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"edamames\", \"polarity\": 4, \"from\": 41, \"to\": 49}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we shared a bottle of sake , an order of edamames , and she had the sushi plat e while i had the sashimi .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"sushi plat\", \"polarity\": 4, \"from\": 68, \"to\": 78}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"we shared a bottle of sake , an order of edamames , and she had the sushi plate while i had the sashimi .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"sashimi\", \"polarity\": 4, \"from\": 96, \"to\": 103}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"i ca n't believe people complain about no cheese sticks ?\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"cheese sticks\", \"polarity\": 4, \"from\": 42, \"to\": 55}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"from the appetizers we ate , the dim sum and other variety of foods , it was impossible to criticize the food .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"appetizers\", \"polarity\": 6, \"from\": 9, \"to\": 19}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"from the appetizers we ate , the dim sum and other variety of foods , it was impossible to criticize the food .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"dim sum\", \"polarity\": 6, \"from\": 33, \"to\": 40}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"from the appetizers we ate , the dim sum and other variety of foods , it was impossible to criticize the food .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"foods\", \"polarity\": 6, \"from\": 62, \"to\": 67}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"from the appetizers we ate , the dim sum and other variety of foods , it was impossible to criticize the food .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"food\", \"polarity\": 6, \"from\": 105, \"to\": 109}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"each table has a pot of boiling water sunken into its surface , and you get platters of thin sliced meats , various vegetables , and rice and glass noodles .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"table\", \"polarity\": 4, \"from\": 5, \"to\": 10}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"each table has a pot of boiling water sunken into its surface , and you get platters of thin sliced meats , various vegetables , and rice and glass noodles .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"pot of boiling water\", \"polarity\": 4, \"from\": 17, \"to\": 37}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"each table has a pot of boiling water sunken into its surface , and you get platters of thin sliced meats , various vegetables , and rice and glass noodles .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"meats\", \"polarity\": 4, \"from\": 100, \"to\": 105}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"each table has a pot of boiling water sunken into its surface , and you get platters of thin sliced meats , various vegetables , and rice and glass noodles .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"vegetables\", \"polarity\": 4, \"from\": 116, \"to\": 126}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"each table has a pot of boiling water sunken into its surface , and you get platters of thin sliced meats , various vegetables , and rice and glass noodles .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"rice\", \"polarity\": 4, \"from\": 133, \"to\": 137}]}\n{\"primary_gid\": \"-1\", \"sentence_normalized\": \"each table has a pot of boiling water sunken into its surface , and you get platters of thin sliced meats , various vegetables , and rice and glass noodles .\", \"targets\": [{\"Input.gid\": \"-1\", \"mention\": \"glass noodles\", \"polarity\": 4, \"from\": 142, \"to\": 155}]}\n"
  },
  {
    "path": "NewsSentiment/converter_huggingface.py",
    "content": "\"\"\"\nThis file converts the dataset files (3 splits) into the format we'll use on\nHuggingface Hub, i.e., where examples with k targets are expanded to k examples, each\nhaving 1 target.\n\"\"\"\n\nimport pathlib\nimport jsonlines\nfrom loguru import logger\n\n\ndef convert_polarity(polarity):\n    if polarity == 2.0:\n        return -1\n    elif polarity == 4.0:\n        return 0\n    elif polarity == 6.0:\n        return 1\n    else:\n        raise ValueError\n\n\ndef convert_target(obj, target):\n    converted_obj = {\n        \"mention\": target[\"mention\"],\n        \"polarity\": convert_polarity(target[\"polarity\"]),\n        \"from\": target[\"from\"],\n        \"to\": target[\"to\"],\n        \"sentence\": obj[\"sentence_normalized\"],\n        \"id\": target[\"Input.gid\"],\n    }\n\n    return converted_obj\n\n\ndef convert_obj(obj):\n    targets = obj[\"targets\"]\n    converted_objs = []\n\n    for target in targets:\n        converted_objs.append(convert_target(obj, target))\n\n    return converted_objs\n\n\ndef convert(path):\n    files = [p for p in pathlib.Path(path).iterdir() if p.is_file()]\n\n    for file in files:\n        converted_lines = []\n        counter = 0\n        with jsonlines.open(file) as reader:\n            for obj in reader:\n                converted_lines.extend(convert_obj(obj))\n                counter += 1\n        logger.info(\n            \"converted {} lines to {} examples in {}\",\n            counter,\n            len(converted_lines),\n            file,\n        )\n\n        with jsonlines.open(str(file) + \"converted\", mode=\"w\") as writer:\n            writer.write_all(converted_lines)\n\n\nif __name__ == \"__main__\":\n    convert(\"experiments/default/datasets/newsmtsc-mt\")\n    convert(\"experiments/default/datasets/newsmtsc-rw\")\n"
  },
  {
    "path": "NewsSentiment/createoverview.py",
    "content": "import argparse\nimport json\nfrom collections import defaultdict\n\nfrom diskdict import DiskDict\n\nimport jsonlines\nimport pandas as pd\n\nfrom NewsSentiment.fxlogger import get_logger\n\nlogger = get_logger()\n\n\ndef rename_flatten(dictionary, key_prefix):\n    new_dict = {}\n\n    for k, v in dictionary.items():\n        new_k = key_prefix + \"-\" + k\n        new_dict[new_k] = v\n\n    return new_dict\n\n\ndef without_keys(d, keys):\n    return {x: d[x] for x in d if x not in keys}\n\n\ndef non_scalar_to_str(d):\n    new_d = {}\n    for k, v in d.items():\n        if type(v) in [list, dict]:\n            new_v = json.dumps(v)\n        else:\n            new_v = v\n        new_d[k] = new_v\n    return new_d\n\n\nCOL_NAME_TMP_GROUP = \"_tmp_named_id_\"\n\n\ndef _find_run_ids(completed_tasks: dict):\n    \"\"\"\n    First check the maximum number of run ids, then ensures that each experiment has\n    that many.\n    :param completed_tasks:\n    :return:\n    \"\"\"\n    run_ids = set()\n    for named_id, result in completed_tasks.items():\n        vals = without_keys(result, [\"details\"])\n        run_id = vals[\"run_id\"]\n        run_ids.add(run_id)\n        del vals[\"run_id\"]\n        del vals[\"experiment_named_id\"]\n        del vals[\"experiment_id\"]\n        named_experiment_id_wo_run_id = json.dumps(vals)\n        result[COL_NAME_TMP_GROUP] = named_experiment_id_wo_run_id\n    num_runs_per_experiment = len(run_ids)\n    logger.info(\"found %s run_ids: %s\", num_runs_per_experiment, run_ids)\n\n    # check that each experiment has as many run ids\n    named_id2run_ids = defaultdict(list)\n    for named_id, result in completed_tasks.items():\n        vals = without_keys(result, [\"details\"])\n        named_experiment_id_wo_run_id = result[\"_tmp_named_id_\"]\n        run_id = vals[\"run_id\"]\n        named_id2run_ids[named_experiment_id_wo_run_id].append(run_id)\n\n    count_too_few_runs = 0\n    for named_id, run_ids in named_id2run_ids.items():\n        if len(run_ids) != num_runs_per_experiment:\n            logger.debug(\"%s runs for %s\", len(run_ids), named_id)\n            count_too_few_runs += 1\n    if count_too_few_runs == 0:\n        logger.info(\n            \"GOOD: num experiments with too few runs: %s of %s\",\n            count_too_few_runs,\n            len(named_id2run_ids),\n        )\n    else:\n        logger.warning(\n            \"num experiments with too few runs: %s of %s\",\n            count_too_few_runs,\n            len(named_id2run_ids),\n        )\n\n    return num_runs_per_experiment, completed_tasks\n\n\ndef _aggregate_and_mean(df: pd.DataFrame):\n    df = df.copy(deep=True)\n    col_names_original_order = list(df.columns)\n    df_aggr = df.groupby(COL_NAME_TMP_GROUP).mean()\n\n    # from https://stackoverflow.com/a/35401886\n    # this creates a df that contains aggregated values (from df_aggr) and also\n    # all other columns (non-aggregated)\n    aggr_col_names = list(df_aggr.columns)\n    df.drop(aggr_col_names, axis=1, inplace=True)\n    df.drop_duplicates(subset=COL_NAME_TMP_GROUP, keep=\"last\", inplace=True)\n    df = df.merge(\n        right=df_aggr, right_index=True, left_on=COL_NAME_TMP_GROUP, how=\"right\"\n    )\n\n    # reorder the dataframe to have the established order of columsn\n    # taken from: https://stackoverflow.com/a/13148611\n    df = df[col_names_original_order]\n\n    # delete temp col\n    del df[COL_NAME_TMP_GROUP]\n\n    return df\n\n\ndef _dfs_to_excel(pathname, name2df):\n    writer = pd.ExcelWriter(pathname, engine=\"xlsxwriter\")\n    for name, df in name2df.items():\n        if df is None:\n            logger.info(\"skipping df because empty: %s\", name)\n            continue\n\n        df.to_excel(writer, sheet_name=name, startrow=0, startcol=0)\n    writer.save()\n\n\ndef shelve2xlsx(opt, ignore_graceful_exit_experiments):\n    completed_tasks = DiskDict(opt.results_path)\n    logger.info(\n        \"found {} results in file {}\".format(len(completed_tasks), opt.results_path)\n    )\n    # get max run id\n    num_runs_per_experiment, completed_tasks = _find_run_ids(completed_tasks)\n\n    flattened_results = {}\n\n    for named_id, result in completed_tasks.items():\n        if result[\"rc\"] == 99 and ignore_graceful_exit_experiments:\n            logger.info(\"found graceful exit (99), not adding to file: %s\", named_id)\n            continue\n        elif result[\"rc\"] == 0:\n            test_stats = rename_flatten(result[\"details\"][\"test_stats\"], \"test_stats\")\n            dev_stats = rename_flatten(result[\"details\"][\"dev_stats\"], \"dev_stats\")\n\n            flattened_result = {\n                **without_keys(result, [\"details\"]),\n                **dev_stats,\n                **test_stats,\n            }\n        else:\n            flattened_result = {**without_keys(result, [\"details\"])}\n\n        scalared_flattened_result = non_scalar_to_str(flattened_result)\n        flattened_results[named_id] = scalared_flattened_result\n\n    df = pd.DataFrame(data=flattened_results.values())\n\n    if num_runs_per_experiment >= 2:\n        df_aggr = _aggregate_and_mean(df)\n    else:\n        df_aggr = None\n    del df[COL_NAME_TMP_GROUP]\n\n    _dfs_to_excel(opt.results_path + \".xlsx\", {\"raw\": df, \"aggr\": df_aggr})\n\n\ndef jsonl2xlsx(opt):\n    labels = {2: \"positive\", 1: \"neutral\", 0: \"negative\"}\n\n    with jsonlines.open(opt.results_path, \"r\") as reader:\n        lines = []\n        for line in reader:\n            if line[\"true_label\"] != line[\"pred_label\"]:\n                line[\"true_label\"] = labels[line[\"true_label\"]]\n                line[\"pred_label\"] = labels[line[\"pred_label\"]]\n\n                lines.append(line)\n\n        df = pd.DataFrame(data=lines)\n        df.to_excel(opt.results_path + \".xlsx\")\n\n\nif __name__ == \"__main__\":\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\n        \"--results_path\",\n        type=str,\n        default=\"results/mtscall_stance0\",\n    )\n    parser.add_argument(\"--mode\", type=str, default=\"shelve\")\n    opt = parser.parse_args()\n\n    if opt.mode == \"shelve\":\n        shelve2xlsx(opt, ignore_graceful_exit_experiments=False)\n    elif opt.mode == \"jsonl\":\n        jsonl2xlsx(opt)\n"
  },
  {
    "path": "NewsSentiment/customexceptions.py",
    "content": "class TooLongTextException(Exception):\n    pass\n\n\nclass TargetNotFoundException(Exception):\n    pass\n"
  },
  {
    "path": "NewsSentiment/dataset.py",
    "content": "import random\nfrom collections import Counter\nfrom typing import (\n    List,\n    Iterable,\n    Set,\n    Union,\n    Dict,\n    overload,\n    Sequence,\n    Mapping,\n    Literal,\n    Tuple,\n    Optional,\n)\n\nimport jsonlines\nimport networkx as nx\nimport numpy as np\nimport spacy\nimport torch\nfrom imblearn.over_sampling import RandomOverSampler\nfrom torch.utils.data import Dataset\nfrom tqdm import tqdm\nfrom transformers import (\n    BertTokenizer,\n    RobertaTokenizer,\n    XLNetTokenizer,\n    AlbertTokenizer,\n)\nfrom math import ceil\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\nfrom NewsSentiment.customexceptions import TooLongTextException, TargetNotFoundException\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.fxlogger import get_logger\n\n# get logger\nfrom NewsSentiment.knowledge.bingliuopinion.bingliuopinion import (\n    get_bingliu_polarities_as_tensor,\n    get_num_bingliu_polarities,\n)\nfrom NewsSentiment.knowledge.mpqasubjectivity.mpqasubjectivity import (\n    get_mpqa_subjectivity_polarities_as_tensor,\n    get_num_mpqa_subjectivity_polarities,\n)\nfrom NewsSentiment.knowledge.nrcemolex.nrcemolex import (\n    get_nrc_emotions_as_tensor,\n    get_num_nrc_emotions,\n)\nfrom NewsSentiment.knowledge.zeros.zerosknowledge import (\n    get_num_zero_dimensions,\n    get_zeros_as_tensor,\n)\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\nlogger = get_logger()\n\n\nclass RandomOversampler(torch.utils.data.sampler.Sampler):\n    def __init__(self, dataset: Dataset, random_seed=None):\n        x = []\n        y = []\n        for ind, example in enumerate(dataset):\n            x.append(ind)\n            y.append(example[\"polarity\"])\n\n        x_arr = np.asarray(x).reshape((len(x), 1))\n        y_arr = np.asarray(y).ravel()\n\n        ros = RandomOverSampler(random_state=random_seed)\n        x_sampled, y_sampled = ros.fit_resample(x_arr, y_arr)\n        self.sampled_indexes = x_sampled.ravel().tolist()\n        sampled_labels = y_sampled.tolist()\n\n        assert len(self.sampled_indexes) == len(sampled_labels)\n\n        random.shuffle(self.sampled_indexes)\n\n        get_logger().info(\n            f\"oversampled to {len(self.sampled_indexes)} samples. label distribution: \"\n            f\"{Counter(sampled_labels)}\"\n        )\n\n    def __len__(self):\n        return len(self.sampled_indexes)\n\n    def __iter__(self):\n        return iter(self.sampled_indexes)\n\n\nclass FXEasyTokenizer:\n    NLP = None\n    NLP_DEP_PARSER_LABELS = None\n    NUM_CATEGORIES_OF_SELECTED_KNOWLEDGE_SOURCES = 0\n    __PROCESSED_KNOWLEDGE_SOURCES = set()\n\n    def __init__(\n        self,\n        tokenizers_name_and_obj: dict,\n        max_seq_len: int,\n        knowledge_sources: Iterable[str],\n        is_use_natural_target_phrase_for_spc: bool,\n    ):\n        self._get_labels()\n        self.tokenizers_name_and_obj = tokenizers_name_and_obj\n        self.max_seq_len = max_seq_len\n        self.knowledge_sources = knowledge_sources\n        self.is_use_natural_target_phrase_for_spc = is_use_natural_target_phrase_for_spc\n\n    @classmethod\n    def _get_labels(cls):\n        if cls.NLP_DEP_PARSER_LABELS is not None:\n            return\n        try:\n            cls.NLP = spacy.load(\"en_core_web_sm\")\n        except OSError:\n            spacy.cli.download(\"en_core_web_sm\")\n            cls.NLP = spacy.load(\"en_core_web_sm\")\n\n        # get list of parser's labels\n        parser_index = cls.NLP.pipe_names.index(\"parser\")\n        cls.NLP_DEP_PARSER_LABELS = list(cls.NLP.pipeline[parser_index][1].labels)\n\n    @staticmethod\n    @overload\n    def create_entire_text(\n        text_left: str,\n        target_phrase: str,\n        text_right: str,\n        is_return_modified_text_left: Literal[True],\n    ) -> Tuple[str, str]:\n        ...\n\n    @staticmethod\n    @overload\n    def create_entire_text(\n        text_left: str,\n        target_phrase: str,\n        text_right: str,\n        is_return_modified_text_left: Literal[False],\n    ) -> str:\n        ...\n\n    @staticmethod\n    def create_entire_text(\n        text_left: str,\n        target_phrase: str,\n        text_right: str,\n        is_return_modified_text_left: bool,\n    ) -> Union[Tuple[str, str], str]:\n        \"\"\"\n        Create the entire text from the three prepared text segment. Will modify\n        text_left (append a whitespace \" \") if it is empty, which is necessary for\n        target mask creation.\n        :param is_return_modified_text_left:\n        :param text_left:\n        :param target_phrase:\n        :param text_right:\n        :return:\n        \"\"\"\n        # input text must have basic tokenization, i.e., each token is separated by ' '\n        if len(text_left) > 0:\n            assert text_left[-1] == \" \", f\"left is not prepared: '{text_left[-1]}'\"\n        else:\n            # we need to have a non-empty left sequence, otherwise BERT's tokenizer\n            # will raise an exception\n            text_left = \" \"\n        if len(text_right) > 0:\n            assert text_right[0] == \" \", f\"right is not prepared: '{text_right[0]}'\"\n\n        # produce entire text string\n        text = text_left + target_phrase + text_right\n\n        if is_return_modified_text_left:\n            return text, text_left\n        else:\n            return text\n\n    @staticmethod\n    def prepare_left_segment(text_left: str):\n        \"\"\"\n        Prepares the left text segment. See FXDataset:task_to_dataset_item for more\n        information. Removes any leading newlines.\n        :param text_left:\n        :return:\n        \"\"\"\n        text_left = text_left.lstrip(\"\\n\")\n        if len(text_left) > 0 and text_left[-1] != \" \":\n            text_left += \" \"\n        return text_left\n\n    @staticmethod\n    def prepare_target_mention(target_mention: str):\n        \"\"\"\n        Removes any leading newlines.\n        :param target_mention:\n        :return:\n        \"\"\"\n        return target_mention.lstrip(\"\\n\")\n\n    @staticmethod\n    def prepare_right_segment(text_right: str):\n        \"\"\"\n        Prepares the right text segment. See FXDataset:task_to_dataset_item for more\n        information.\n        :param text_right:\n        :return:\n        \"\"\"\n        if len(text_right) > 0 and text_right[0] != \" \":\n            text_right = \" \" + text_right\n        return text_right\n\n    def _create_word_to_wordpiece_mapping(\n        self, tokenizer, words: List, for_text_with_special_tokens, offset\n    ):\n        batch_output = self._batch_create_word_to_wordpiece_mapping(\n            tokenizer, [words], for_text_with_special_tokens, [offset]\n        )\n        return tuple(output[0] for output in batch_output)\n\n    def _batch_create_word_to_wordpiece_mapping(\n        self,\n        tokenizer,\n        words_per_target: List[List],\n        for_text_with_special_tokens,\n        offsets,\n    ):\n        if not for_text_with_special_tokens:\n            raise NotImplementedError()\n\n        target_words = [\n            (\n                \" \".join(target[:word_index]) + \" \",  # left\n                word,  # target\n                \"\",  # right\n            )\n            for target in words_per_target\n            for word_index, word in enumerate(target)\n        ]\n\n        # produce target masks\n        target_masks = self._batch_create_target_mask(\n            tokenizer=tokenizer,\n            targets=target_words,\n            for_text_with_special_tokens=for_text_with_special_tokens,\n            is_raise_exception_if_target_after_max_seq_len=False,\n        )\n\n        # split back into targets\n        _indexer = 0\n        target_masks_per_target = [\n            target_masks[_indexer : (_indexer := _indexer + len(wpt))]\n            for wpt in words_per_target\n        ]\n\n        # remove \"toolong\" (word is after the max seq len)\n        valid_target_masks_per_target = []\n        valid_tokens = []\n        for target, tokens in zip(target_masks_per_target, words_per_target):\n            indexer = target.index(\"toolong\") if \"toolong\" in target else None\n            valid_target_masks_per_target.append(target[:indexer])\n            valid_tokens.append(tokens[:indexer])\n\n        # convert to tensors\n        mappings = []\n\n        for target, offset in zip(valid_target_masks_per_target, offsets):\n            target_tensor = torch.LongTensor(target)\n\n            word_indices_multiplier = torch.tensor(\n                range(offset, offset + len(target_tensor))\n            )\n            target_tensor = target_tensor.mul(word_indices_multiplier.unsqueeze(-1))\n\n            if type(tokenizer) == RobertaTokenizer:\n                if target_tensor.prod(0).sum(0) > 0:\n                    logger.debug(\n                        \"overlap when mapping tokens to wordpiece (allow overwriting because\"\n                        \" Roberta is used)\"\n                    )\n            else:\n                assert target_tensor.prod(0).sum(0) == 0\n\n            target_tensor = target_tensor.sum(0)\n\n            assert target_tensor.size(0) <= self.max_seq_len\n\n            mappings.append(target_tensor)\n\n        return mappings, valid_tokens\n\n    def _calculate_dep_matrix(self, text_tokens, text_tokens_as_str):\n        _check_len_doc = len(text_tokens)\n        assert _check_len_doc == len(\n            text_tokens_as_str\n        ), f\"{_check_len_doc} vs {len(text_tokens_as_str)}: {text_tokens} vs {text_tokens_as_str}\"\n\n        # for the dependency matrix\n        dependency_tensor = torch.zeros(\n            len(text_tokens_as_str), len(text_tokens_as_str), dtype=torch.long\n        )\n\n        for token_index, token in enumerate(text_tokens):\n            if token.is_space:\n                # text_tokens_as_str does not contain whitespace tokens, so we skip them\n                # here, too\n                continue\n            assert (\n                token.text == text_tokens_as_str[token_index]\n            ), f\"'{token.text}' vs. '{text_tokens_as_str[token_index]}'\"\n\n            # to build the dependency relation matrix\n            # get the token's head and type of relation\n            head_of_token = token.head\n            try:\n                index_in_token_list_of_head_of_token = text_tokens.index(head_of_token)\n            except ValueError as ve:\n                # if the head cannot be found in the (truncated to wordpiece equivalent\n                # max seq len) list of text_tokens, this means that the current token's\n                # head is not part of the wordpiece sequence. we print an error and\n                # not change the current word's vector (will be all 0's)\n                logger.warning(ve)\n                continue\n\n            relation_to_head = token.dep_\n            # offset the relation by 1 so that the root relation (which is 0) is\n            # non-zero\n            index_of_relation_to_head = (\n                self.NLP_DEP_PARSER_LABELS.index(relation_to_head) + 1\n            )\n            # insert to dependency tensor\n            dependency_tensor[\n                token_index, index_in_token_list_of_head_of_token\n            ] = index_of_relation_to_head\n\n        return dependency_tensor\n\n    def _calculate_dep_distance(self, text_tokens, text_left_len, target):\n        threshold_for_target_token = 8\n\n        # by using spacys tokenization also on the target (instead of a simple\n        # whitespace split as in https://github.com/StevePhan101/LCFS-BERT/\n        # we ensure that the same tokenization as was used for the text is applied for\n        # the target\n        nlp_target = self.NLP(target)\n        # target_terms_lowercased = [a.lower() for a in target.split()]\n        target_terms_lowercased = [a.text.lower() for a in nlp_target]\n\n        # Load spacy's dependency tree into a networkx graph\n        edges = []\n        cnt = 0\n        found_start_of_target = False\n        target_term_ids = [0] * len(target_terms_lowercased)\n        len_previously_processed_tokens = 0\n        for token in text_tokens:\n            # Record the position of aspect terms\n            lowercased_token = token.lower_\n            token_startchar_indoc = token.idx\n            token_endchar_indoc = token_startchar_indoc + len(token.text_with_ws)\n\n            if (\n                cnt < len(target_terms_lowercased)\n                and lowercased_token == target_terms_lowercased[cnt]\n            ):\n                # if both conditions above are satisfied, we probably have (part of)\n                # the target in the current token. however, to be slightly more\n                # confident about this, also ensure that the previous tokens have\n                # approximately the same length as text_left_len. or skip that check\n                # if we already found the start of the target\n                if (\n                    found_start_of_target\n                    or abs(text_left_len - len_previously_processed_tokens)\n                    < threshold_for_target_token\n                ):\n                    found_start_of_target = True\n                    target_term_ids[cnt] = token.i\n                    cnt += 1\n                else:\n                    pass\n\n            len_previously_processed_tokens += len(token.text_with_ws)\n\n            # for lcfs absa\n            for child in token.children:\n                edges.append(\n                    (\n                        \"{}_{}\".format(token.lower_, token.i),\n                        \"{}_{}\".format(child.lower_, child.i),\n                    )\n                )\n\n        if not found_start_of_target:\n            raise TargetNotFoundException(\n                f\"no target found: {text_tokens}, {text_left_len}, {target}\"\n            )\n\n        # create the graph\n        graph = nx.Graph(edges)\n\n        dist = [0.0] * len(text_tokens)\n        for i, word in enumerate(text_tokens):\n            source = \"{}_{}\".format(word.lower_, word.i)\n            sum = 0\n            for term_id, term in zip(target_term_ids, target_terms_lowercased):\n                target = \"{}_{}\".format(term, term_id)\n                try:\n                    sum += nx.shortest_path_length(graph, source=source, target=target)\n                except:\n                    sum += len(text_tokens)  # No connection between source and target\n            dist[i] = sum / len(target_terms_lowercased)\n        return dist\n\n    def _create_target_mask(\n        self,\n        tokenizer,\n        text_left: str,\n        target: str,\n        text_right: str,\n        for_text_with_special_tokens: bool,\n        is_raise_exception_if_target_after_max_seq_len: bool = True,\n    ):\n        \"\"\"\n        Creates a target mask for a single target in a text that comprises left, target,\n        and right. Specifically, the target mask has the same length as the sequence of\n        the entire text including special tokens, and contains 1's for each position k\n        where in the entire text sequence (including special tokens) the token at\n        position k is part of the target phrase.\n        Simplified example (this does not consider any LM specific tokenization\n        characteristics, e.g., most LMs' tokenizers do not tokenize single tokens but\n        produce sub-tokens (e.g., BERT using the WordPiece tokenizer).\n        Text:                                    Mr. <target>Smith</target> is great .\n        Text indexes (with special tokens):  CLS 12           50            18 15    19 END\n        Target mask:                          0  0             1             0  0    0   0\n        :param tokenizer:\n        :param text_left:\n        :param target:\n        :param text_right:\n        :param text_pair: if not None, will be appended to the input sequence as the second pair\n        :return:\n        \"\"\"\n        return self._batch_create_target_mask(\n            tokenizer,\n            ((text_left, target, text_right),),\n            for_text_with_special_tokens,\n            is_raise_exception_if_target_after_max_seq_len,\n        )[0]\n\n    def _batch_create_target_mask(\n        self,\n        tokenizer,\n        targets,\n        for_text_with_special_tokens: bool,\n        is_raise_exception_if_target_after_max_seq_len: bool = True,\n    ):\n        if not for_text_with_special_tokens:\n            raise NotImplementedError()\n\n        lefts = []\n        rights = []\n        full_texts = []\n        target_phrases = []\n        for target in targets:\n            ft, l = self.create_entire_text(*target, is_return_modified_text_left=True)\n            lefts.append(l)\n            full_texts.append(ft)\n            target_phrases.append(target[1])\n            rights.append(target[2])\n\n        encodings = self._encode_for_target_mask(\n            tokenizer, lefts, target_phrases, rights, full_texts\n        )\n\n        return [\n            self._create_target_mask_on_encoding(\n                tokenizer, *encoding, is_raise_exception_if_target_after_max_seq_len\n            )\n            for encoding in zip(*encodings)\n        ]\n\n    def _encode_for_target_mask(\n        self, tokenizer, text_lefts, targets, text_rights, full_texts\n    ):\n        # get token ids, cf. https://huggingface.co/transformers/glossary.html\n        text_left_ids_with_special_tokens = tokenizer(\n            text_lefts, add_special_tokens=True\n        )[\"input_ids\"]\n        text_right_ids = tokenizer(text_rights, add_special_tokens=False)[\"input_ids\"]\n        text_ids_with_special_tokens = tokenizer(full_texts, add_special_tokens=True)[\n            \"input_ids\"\n        ]\n        target_phrase_ids_with_special_tokens = tokenizer(\n            targets, add_special_tokens=True\n        )[\"input_ids\"]\n\n        return (\n            text_left_ids_with_special_tokens,\n            target_phrase_ids_with_special_tokens,\n            text_right_ids,\n            text_ids_with_special_tokens,\n        )\n\n    def _create_target_mask_on_encoding(\n        self,\n        tokenizer,\n        text_left_ids_with_special_tokens,\n        target_phrase_ids_with_special_tokens,\n        text_right_ids,\n        text_ids_with_special_tokens,\n        is_raise_exception_if_target_after_max_seq_len,\n    ):\n        len_text_left_ids_with_special_tokens = len(text_left_ids_with_special_tokens)\n        len_text_right_ids = len(text_right_ids)\n        len_text_id_with_special_tokens = len(text_ids_with_special_tokens)\n        len_target_ids_with_special_tokens = len(target_phrase_ids_with_special_tokens)\n\n        token_obj_class = type(tokenizer)\n        if token_obj_class in [BertTokenizer, RobertaTokenizer, AlbertTokenizer]:\n            # these tokenizers create 1 special token at the end that should not be\n            num_special_tokens_at_start = 1\n            num_special_tokens_at_end = 1\n        elif token_obj_class == XLNetTokenizer:\n            num_special_tokens_at_start = 0\n            num_special_tokens_at_end = 2\n        else:\n            raise ValueError\n        # determine numbers of special tokens in the target\n        num_special_tokens_in_target = (\n            num_special_tokens_at_start + num_special_tokens_at_end\n        )\n        # get the number of token ids of the target, excluding special tokens\n        # we do this, because\n        num_effective_length_target_in_text = (\n            len_target_ids_with_special_tokens - num_special_tokens_in_target\n        )\n        # get the position of the first non-special token of the target phrase in the\n        # sequence of tokens representing the entire text, which includes special tokens\n        tp_seq_in_text_seq_pos_start = (\n            len_text_left_ids_with_special_tokens - num_special_tokens_at_end\n        )\n        # likewise, get the position of the last non-special token of the target phrase\n        # in the sequences of tokens representing the entire text, which includes\n        # special tokens\n        tp_seq_in_text_seq_pos_end = (\n            tp_seq_in_text_seq_pos_start + num_effective_length_target_in_text\n        )\n        # get the length of the token sequence representing the target phrase (again,\n        # only actual content tokens, no special tokens)\n        tp_seq_in_text_seq_len = (\n            tp_seq_in_text_seq_pos_end - tp_seq_in_text_seq_pos_start\n        )\n        assert (\n            tp_seq_in_text_seq_len > 0\n        ), f\"tp_seq_in_text_seq_len: {tp_seq_in_text_seq_len}\"\n\n        # if the end position of the target is greater than the maximum sequence length,\n        # we raise an Exception, since it won't make sense to train with or evaluate on\n        # this example since the target will be out of bounds\n        if tp_seq_in_text_seq_pos_end > self.max_seq_len:\n            if is_raise_exception_if_target_after_max_seq_len:\n                raise TooLongTextException()\n            else:\n                # e.g., if invoked for creating the target mapping\n                return \"toolong\"\n\n        # create target mask: all 0 except for occurrence of target\n        target_mask_seq = [0] * self.max_seq_len\n        target_mask_seq[tp_seq_in_text_seq_pos_start:tp_seq_in_text_seq_pos_end] = [\n            1\n        ] * tp_seq_in_text_seq_len\n\n        # perform checks\n        count_nonzero_elements_in_target_mask_seq = sum(\n            [1 if elem != 0 else 0 for elem in target_mask_seq]\n        )\n\n        # roberta: 1 special token at beginning, 1 at end\n        # bert: 1 beginning, 1 at end\n        # xlnet: 0 beginning, 2 at end\n        # len_text_left_ids_with_special_tokens contains the right amount of both\n        # special tokens at the beginning and end of the sequence\n        calculated_len = (\n            len_text_left_ids_with_special_tokens\n            + num_effective_length_target_in_text\n            + len_text_right_ids\n        )\n\n        if token_obj_class == RobertaTokenizer:\n            # Roberta has more complex tokenization behavior, e.g., >>> tokenizer(\"the friendly staff welcomes\")['input_ids']\n            # [0, 627, 5192, 813, 16795, 2]\n            # >>> tokenizer(\"welcomes\")['input_ids']\n            # [0, 605, 523, 32696, 2]\n            # >>> tokenizer(\"welcomes you\")['input_ids']\n            # [0, 605, 523, 32696, 47, 2]\n            # -> so we skip this check here\n            pass\n        else:\n            assert (\n                len_text_id_with_special_tokens == calculated_len\n            ), f\"{len_text_id_with_special_tokens} == {calculated_len}\"\n        assert (\n            count_nonzero_elements_in_target_mask_seq\n            == num_effective_length_target_in_text\n        )\n\n        return target_mask_seq\n\n    def _create_knowledge_source_tensor(\n        self, text_tokens_as_str: List, offset: int, mapping, mode: str\n    ):\n        if mode == \"nrc_emotions\":\n            num_categories = get_num_nrc_emotions()\n        elif mode == \"mpqa_subjectivity\":\n            num_categories = get_num_mpqa_subjectivity_polarities()\n        elif mode == \"bingliu_opinion\":\n            num_categories = get_num_bingliu_polarities()\n        elif mode == \"liwc\":\n            from knowledge.liwc.liwc import get_num_liwc_categories\n\n            num_categories = get_num_liwc_categories()\n        elif mode == \"zeros\":\n            num_categories = get_num_zero_dimensions()\n        else:\n            raise NotImplementedError\n\n        emotions_for_sequence = torch.zeros(\n            self.max_seq_len, num_categories, dtype=torch.long\n        )\n        for word_index, word in enumerate(text_tokens_as_str, start=offset):\n            positions_of_current_word_in_input_sequence = (\n                self._map_token_index_to_wordpiece_index(mapping, word_index)\n            )\n            if mode == \"nrc_emotions\":\n                emotion_tensor = get_nrc_emotions_as_tensor(word)\n            elif mode == \"mpqa_subjectivity\":\n                emotion_tensor = get_mpqa_subjectivity_polarities_as_tensor(word)\n            elif mode == \"bingliu_opinion\":\n                emotion_tensor = get_bingliu_polarities_as_tensor(word)\n            elif mode == \"liwc\":\n                from knowledge.liwc.liwc import get_liwc_categories_as_tensor\n\n                emotion_tensor = get_liwc_categories_as_tensor(word)\n            elif mode == \"zeros\":\n                emotion_tensor = get_zeros_as_tensor(word)\n            else:\n                raise NotImplementedError\n\n            for position_in_seq in positions_of_current_word_in_input_sequence:\n                emotions_for_sequence[position_in_seq, :] = emotion_tensor\n        return emotions_for_sequence\n\n    def _create_mapping_from_tokenbased_to_wordpiece_based(self, text, tok_obj):\n        batch_output = self._batch_create_mapping_from_tokenbased_to_wordpiece_based(\n            (text,), tok_obj\n        )\n        return tuple(output[0] for output in batch_output)\n\n    def _batch_create_mapping_from_tokenbased_to_wordpiece_based(self, texts, tok_obj):\n        offset = 10\n        # for spacy, we need to remove leading spaces as they will yield a single\n        # token\n        text_without_leading_space = [text.strip() for text in texts]\n        nlp_text_per_target = self.NLP.pipe(text_without_leading_space)\n\n        # get only non-single-space tokens, see\n        # https://github.com/explosion/spaCy/issues/1707\n        text_tokens, text_tokens_as_str = zip(\n            *(\n                zip(*((token, token.text) for token in nlp_text if not token.is_space))\n                for nlp_text in nlp_text_per_target\n            )\n        )\n        # in case there is a word at position k that is longer than the max seq len\n        # when converted to wordpiece indexes, _create_word_to_wordpiece_mapping\n        # returns all words up to including k-1\n        mapping, text_tokens_as_str = self._batch_create_word_to_wordpiece_mapping(\n            tok_obj,\n            text_tokens_as_str,\n            for_text_with_special_tokens=True,\n            offsets=[offset] * len(texts),\n        )\n        # ..., correspondingly, truncate text_tokens to same length\n        text_tokens = [\n            tt[: len(ttas)] for tt, ttas in zip(text_tokens, text_tokens_as_str)\n        ]\n        return mapping, [offset] * len(texts), text_tokens_as_str, text_tokens\n\n    def _convert_non_null_to_one(self, lst):\n        lst_one = []\n        for item in lst:\n            if item == 0:\n                lst_one.append(0)\n            else:\n                lst_one.append(1)\n        return lst_one\n\n    def _map_token_index_to_wordpiece_index(self, a, b):\n        is_equal_tensor = a == b\n        is_equal_tensor = torch.nonzero(is_equal_tensor, as_tuple=False)\n        is_equal_tensor = is_equal_tensor.flatten()\n        return is_equal_tensor.tolist()\n\n    def _create_dependency_tensor(\n        self,\n        text_tokens,\n        text_tokens_as_str,\n        mapping_token2wordpiece,\n        mapping_token2wordpiece_offset,\n    ):\n        # create the dependency matrix\n        dependency_tensor_of_tokens = self._calculate_dep_matrix(\n            text_tokens, text_tokens_as_str\n        )\n        # create empty wordpiece based tensors\n        dependency_tensor_of_wordpieces = torch.zeros(\n            self.max_seq_len, self.max_seq_len, dtype=torch.float\n        )\n\n        for word_index_withoffset, word in enumerate(\n            text_tokens_as_str, start=mapping_token2wordpiece_offset\n        ):\n            word_index = word_index_withoffset - mapping_token2wordpiece_offset\n            dependency_column = dependency_tensor_of_tokens[word_index].tolist()\n            dependency_column_ones = self._convert_non_null_to_one(dependency_column)\n            _check_num_heads = sum(dependency_column_ones)\n            assert _check_num_heads in [\n                0,\n                1,\n            ], (\n                f\"expected only zero or one heads, found {_check_num_heads} for word \"\n                f\"{word} in {text_tokens_as_str}\"\n            )\n            if _check_num_heads == 0:\n                # this can happen if the head is in the part of the sentence that was\n                # truncated due to max seq len\n                logger.warning(\n                    \"head of word %s is not part of the wordpiece sequence\", word\n                )\n                continue\n\n            head_index = dependency_column_ones.index(1)\n            head_index_withoffset = head_index + mapping_token2wordpiece_offset\n            dependency_type = dependency_column[head_index]\n            assert dependency_type != 0\n\n            positions_of_current_word_in_input_sequence = (\n                self._map_token_index_to_wordpiece_index(\n                    mapping_token2wordpiece, word_index_withoffset\n                )\n            )\n            positions_of_current_head_in_input_sequence = (\n                self._map_token_index_to_wordpiece_index(\n                    mapping_token2wordpiece, head_index_withoffset\n                )\n            )\n\n            for position_word in positions_of_current_word_in_input_sequence:\n                for position_head in positions_of_current_head_in_input_sequence:\n                    dependency_tensor_of_wordpieces[\n                        position_word, position_head\n                    ] = dependency_type\n\n        return dependency_tensor_of_wordpieces\n\n    def _create_dependency_tree_hop_distances_of_tokens_to_target(\n        self,\n        text_tokens,\n        text_left_len,\n        target_phrase,\n        text_tokens_as_str,\n        mapping_token2wordpiece,\n        mapping_token2wordpiece_offset,\n    ):\n        \"\"\"\n        finds for each token in the sentence, or rather each token's wordpiece(s) the distance in the\n        syntax tree to the target phrase. returns a list of size k where k is the maxseqlen; the list\n        contains the distances for each wordpiece.\n        :param text_tokens:\n        :param text_left_len:\n        :param target_phrase:\n        :param text_tokens_as_str:\n        :param mapping_token2wordpiece:\n        :param mapping_token2wordpiece_offset:\n        :return:\n        \"\"\"\n        # Find distance in dependency parsing tree\n        num_chars_counted = sum([len(token) for token in text_tokens_as_str])\n        dist = self._calculate_dep_distance(text_tokens, text_left_len, target_phrase)\n\n        # create empty wordpiece based tensors\n        syntax_hop_distance_to_target = torch.zeros(self.max_seq_len, dtype=torch.long)\n\n        # convert:\n        # syntax_hop_distance_to_target and dependency_tensor_of_wordpieces is wordpiece\n        # based. dist and dependency_tensor_of_tokens is token based. map from each to\n        # the wordpiece variant\n        for word_index, word in enumerate(\n            text_tokens_as_str, start=mapping_token2wordpiece_offset\n        ):\n            word_index_without_offset = word_index - mapping_token2wordpiece_offset\n\n            positions_of_current_word_in_input_sequence = (\n                self._map_token_index_to_wordpiece_index(\n                    mapping_token2wordpiece, word_index\n                )\n            )\n\n            depdistance_of_current_word_in_input_sequence = dist[\n                word_index_without_offset\n            ]\n\n            for position in positions_of_current_word_in_input_sequence:\n                syntax_hop_distance_to_target[\n                    position\n                ] = depdistance_of_current_word_in_input_sequence\n\n        return syntax_hop_distance_to_target\n\n    def create_model_input_seqs(\n        self,\n        text_left: str,\n        target_phrase: str,\n        text_right: str,\n        coreferential_targets_for_target_mask: Optional[Iterable[dict]],\n    ) -> Mapping[str, Mapping[str, Union[torch.Tensor, bool]]]:\n        \"\"\"\n        Creates input sequences for a given target. Prior components have processed the jsonl\n        so that coreferential_targets_for_target_mask will contain a list of coreferential\n        mentions of the target if and only if coref_mode == \"in_targetmask\". In that case,\n        will produce an individual target mask for each coref mention and merge them to\n        the target mask of the preferred mention.\n        \"\"\"\n        batch_result = self.batch_create_model_input_seqs(\n            ((text_left, target_phrase, text_right),),\n            coreferential_targets_for_target_mask=(\n                coreferential_targets_for_target_mask,\n            ),\n        )\n        return {\n            tok_name: {\n                seq_name: seq_result[0] for seq_name, seq_result in tok_result.items()\n            }\n            for tok_name, tok_result in batch_result.items()\n        }\n\n    @overload\n    def batch_create_model_input_seqs(\n        self,\n        targets: ...,\n        coreferential_targets_for_target_mask: ...,\n    ) -> Mapping[str, Mapping[str, Union[torch.Tensor, Tuple[bool], bool]]]:\n        ...\n\n    @overload\n    def batch_create_model_input_seqs(\n        self,\n        targets: ...,\n        coreferential_targets_for_target_mask: ...,\n    ) -> Mapping[str, Mapping[str, Union[torch.Tensor, bool]]]:\n        ...\n\n    def batch_create_model_input_seqs(\n        self,\n        targets: Sequence[Tuple[str, str, str]],\n        coreferential_targets_for_target_mask: Optional[\n            Sequence[Optional[Iterable[dict]]]\n        ],\n    ) -> Mapping[str, Mapping[str, Union[torch.Tensor, Tuple[bool], bool]]]:\n        \"\"\"\n        Creates input sequences for given targets. Prior components have processed the jsonl\n        so that coreferential_targets_for_target_mask will contain a list of coreferential\n        mentions of the targets if and only if coref_mode == \"in_targetmask\". In that case,\n        will produce an individual target mask for each coref mention and merge them to\n        the target mask of the preferred mention.\n\n        NEW\n        Multiple target inputs. Output will be a tuple of batches with the\n        created sequences being of shape [batch_size,seq_length]. To output a single\n        target without batch output and with tensors of shape [seq_length],\n        set single_target_output = True.\n        \"\"\"\n        num_targets = len(targets)\n\n        if not coreferential_targets_for_target_mask:\n            coreferential_targets_for_target_mask = [None] * num_targets\n        elif num_targets != len(coreferential_targets_for_target_mask):\n            raise TypeError(\n                \"Number of coreferential_targets_for_target_mask must match number of targets.\"\n            )\n\n        lefts = []\n        target_phrases = []\n        adjusted_target_phrases = []\n        full_texts = []\n\n        for target in targets:\n            assert all(isinstance(arg, str) for arg in target), \"Wrong input types.\"\n\n            left, target_phrase, _ = target\n\n            lefts.append(left)\n\n            target_phrases.append(target_phrase)\n\n            adjusted_target_phrases.append(\n                f\"What do you think of {target_phrase}?\"\n                if self.is_use_natural_target_phrase_for_spc\n                else target_phrase\n            )\n\n            full_texts.append(\n                self.create_entire_text(*target, is_return_modified_text_left=False)\n            )\n\n        out: Mapping[str, Mapping[str, Union[torch.Tensor, bool]]] = {}\n\n        for tok_name, tok_obj in self.tokenizers_name_and_obj.items():\n            logger.debug(f\"{tok_name}\")\n\n            # text\n            text_ids_with_special_tokens_per_target = tok_obj(\n                text=full_texts,\n                max_length=self.max_seq_len,\n                padding=\"max_length\",\n                add_special_tokens=True,\n                truncation=\"longest_first\",\n            )[\"input_ids\"]\n            text_then_target_ids_with_special_tokens_dict_per_target = (\n                tok_obj.batch_encode_plus(\n                    zip(full_texts, adjusted_target_phrases),\n                    max_length=self.max_seq_len,\n                    padding=\"max_length\",\n                    add_special_tokens=True,\n                    truncation=\"longest_first\",\n                )\n            )\n            text_then_target_ids_with_special_tokens_dict_per_target = (\n                text_then_target_ids_with_special_tokens_dict_per_target.data\n            )\n            text_then_target_ids_with_special_tokens_per_target = (\n                text_then_target_ids_with_special_tokens_dict_per_target[\"input_ids\"]\n            )\n            if type(tok_obj) == RobertaTokenizer:\n                # roberta doesnt have segments, so we produce fake segment ids\n                # here, and later simply dont pass them\n                text_then_target_ids_with_special_tokens_segment_ids_per_target = [\n                    [0 for _ in target_ids]\n                    for target_ids in text_then_target_ids_with_special_tokens_per_target\n                ]\n            else:\n                text_then_target_ids_with_special_tokens_segment_ids_per_target = (\n                    text_then_target_ids_with_special_tokens_dict_per_target[\n                        \"token_type_ids\"\n                    ]\n                )\n            # target\n            target_ids_with_special_tokens_per_target = tok_obj(\n                target_phrases,\n                max_length=self.max_seq_len,\n                padding=\"max_length\",\n                add_special_tokens=True,\n                truncation=\"longest_first\",\n            )[\"input_ids\"]\n\n            # create target masks\n            target_mask_seq_for_text_with_special_tokens_per_target = (\n                self._batch_create_target_mask(\n                    tok_obj, targets, for_text_with_special_tokens=True\n                )\n            )\n            # create target mask for coreferential targets of given target\n            coref_target_masks_per_target = (\n                self._batch_create_coreferential_target_masks(\n                    tok_obj, coreferential_targets_for_target_mask\n                )\n            )\n            # merge them into the preferred target mask\n            merged_target_mask_per_target = tuple(\n                self._merge_coref_target_masks_into_preferred_target_mask(\n                    target_mask,\n                    coref_target_masks,\n                )\n                for target_mask, coref_target_masks in zip(\n                    target_mask_seq_for_text_with_special_tokens_per_target,\n                    coref_target_masks_per_target,\n                )\n            )\n            target_mask_seq_for_text_with_special_tokens_per_target = (\n                merged_target_mask_per_target\n            )\n\n            # create also text ids without max length to see if the one that will be\n            # used was truncated\n            text_ids_with_special_tokens_no_max_length_per_target = tok_obj(\n                full_texts, add_special_tokens=True\n            )[\"input_ids\"]\n            text_num_truncated_tokens_per_target = tuple(\n                len(noml) - len(ml)\n                for noml, ml in zip(\n                    text_ids_with_special_tokens_no_max_length_per_target,\n                    text_ids_with_special_tokens_per_target,\n                )\n            )\n\n            # iterate tokens of full text and look up in dicts\n            # create mapping from token-based indexes to wordpiece-based indexes\n            # the function will also remove any tokens for which the word piece index\n            # would be after max seq len\n            # under certain circumstances, e.g., when using albert as well as the target\n            # phrase is close to what would be cut off (but is not at this point), it can happen\n            # that at a later point in time, i.e., _create_dependency_tree_hop_distances_of_tokens_to_target\n            # or more specifically _calculate_dep_distance, the target cannot be found in the list of\n            # tokens anymore, because this list of now cut off. thus, i changed the assert in\n            # _calculate_dep_distance to throwing an exception that is catched later on\n            (\n                mapping_token2wordpiece_per_target,\n                mapping_token2wordpiece_offset_per_target,\n                text_tokens_as_str_per_target,\n                text_tokens_per_target,\n            ) = self._batch_create_mapping_from_tokenbased_to_wordpiece_based(\n                full_texts, tok_obj\n            )\n\n            text_stacked_knowledge_source_info_per_target = []\n            text_dependency_tree_hop_distances_per_target = []\n            text_dependency_matrix_per_target = []\n\n            for (\n                target_phrase,\n                left,\n                mapping_token2wordpiece,\n                mapping_token2wordpiece_offset,\n                text_tokens_as_str,\n                text_tokens,\n            ) in zip(\n                target_phrases,\n                lefts,\n                mapping_token2wordpiece_per_target,\n                mapping_token2wordpiece_offset_per_target,\n                text_tokens_as_str_per_target,\n                text_tokens_per_target,\n            ):\n                # create additional knowledge source tensors\n                # stack only those knowledge sources that were requested by arguments\n                selected_tensors_knowledge_sources_text = []\n                for source in self.knowledge_sources:\n                    text_tensor = self._create_knowledge_source_tensor(\n                        text_tokens_as_str,\n                        mapping_token2wordpiece_offset,\n                        mapping_token2wordpiece,\n                        source,\n                    )\n                    selected_tensors_knowledge_sources_text.append(text_tensor)\n                text_stacked_knowledge_source_info_per_target.append(\n                    torch.cat(tuple(selected_tensors_knowledge_sources_text), dim=1)\n                    if self.knowledge_sources\n                    else None\n                )\n\n                # syntax hop distance\n                text_dependency_tree_hop_distances_per_target.append(\n                    self._create_dependency_tree_hop_distances_of_tokens_to_target(\n                        text_tokens,\n                        len(left),\n                        target_phrase,\n                        text_tokens_as_str,\n                        mapping_token2wordpiece,\n                        mapping_token2wordpiece_offset,\n                    )\n                )\n\n                text_dependency_matrix_per_target.append(\n                    self._create_dependency_tensor(\n                        text_tokens,\n                        text_tokens_as_str,\n                        mapping_token2wordpiece,\n                        mapping_token2wordpiece_offset,\n                    )\n                )\n\n            # create item with indexes and masks\n            result = {\n                FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS: torch.LongTensor(\n                    text_ids_with_special_tokens_per_target\n                ),\n                FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK: torch.FloatTensor(\n                    target_mask_seq_for_text_with_special_tokens_per_target\n                ),\n                FIELD_IS_OVERFLOW: tuple(\n                    text_num > 0 for text_num in text_num_truncated_tokens_per_target\n                ),\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS: torch.LongTensor(\n                    text_then_target_ids_with_special_tokens_per_target\n                ),\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS: torch.LongTensor(\n                    text_then_target_ids_with_special_tokens_segment_ids_per_target\n                ),\n                FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS: torch.LongTensor(\n                    target_ids_with_special_tokens_per_target\n                ),\n                FIELD_SYNTAX_HOP_DISTANCE_TO_TARGET: torch.stack(\n                    text_dependency_tree_hop_distances_per_target\n                ),\n                FIELD_SYNTAX_DEPENDENCY_MATRIX: torch.stack(\n                    text_dependency_matrix_per_target\n                ),\n            }\n\n            # add knowledge source if requested\n            if self.knowledge_sources:\n                result[\n                    FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES\n                ] = torch.stack(text_stacked_knowledge_source_info_per_target)\n\n            # add tokenizer result to output\n            out[tok_name] = result\n\n        return out\n\n    def _create_coreferential_target_masks(\n        self, tok_obj, coreferential_targets_for_target_mask: Optional[Iterable[dict]]\n    ):\n        return self._batch_create_coreferential_target_masks(\n            tok_obj, (coreferential_targets_for_target_mask,)\n        )[0]\n\n    def _batch_create_coreferential_target_masks(\n        self,\n        tok_obj,\n        coreferential_targets_for_target_mask_per_target: Sequence[\n            Optional[Iterable[dict]]\n        ],\n    ):\n        target_masks_per_target = []\n        for coreferential_targets in coreferential_targets_for_target_mask_per_target:\n            target_mask = []\n            if coreferential_targets:\n                coref_targets = [\n                    (\n                        self.prepare_left_segment(coref_target[\"text_left\"]),\n                        self.prepare_target_mention(coref_target[\"mention\"]),\n                        \"\",\n                    )\n                    for coref_target in coreferential_targets\n                ]\n                target_mask.append(\n                    self._batch_create_target_mask(\n                        tok_obj, coref_targets, for_text_with_special_tokens=True\n                    )\n                )\n            target_masks_per_target.append(target_mask)\n        return target_masks_per_target\n\n    def _merge_coref_target_masks_into_preferred_target_mask(\n        self, target_mask_seq_for_text_with_special_tokens, coref_target_masks\n    ):\n        if coref_target_masks is None or len(coref_target_masks) == 0:\n            return target_mask_seq_for_text_with_special_tokens\n\n        # target_mask_seq_for_text_with_special_tokens is a list of scalars, coref tms a list of lists\n        # turn both into a list of lists and append them\n        all_target_masks = [\n            target_mask_seq_for_text_with_special_tokens\n        ] + coref_target_masks\n        assert len(all_target_masks) == 1 + len(coref_target_masks)\n        num_scalars = len(target_mask_seq_for_text_with_special_tokens)\n        # ensure all same length\n        for lst in all_target_masks:\n            assert len(lst) == num_scalars\n        # create merged lst\n        merged_target_mask = [0] * num_scalars\n        for index in range(num_scalars):\n            merged_value = 0\n            for lst in all_target_masks:\n                lst_cur_value = lst[index]\n                assert lst_cur_value in [0, 1]\n                merged_value += lst_cur_value\n            merged_value = min(1, merged_value)\n            merged_target_mask[index] = merged_value\n\n        return merged_target_mask\n\n\nclass FXDataset(Dataset):\n    __PARAMS2INDEX = {}\n    NUM_MAX_TARGETS_PER_ITEM = 2\n    SINGLE_TARGETS = False\n\n    def __init__(\n        self,\n        filepath,\n        data_format: str,\n        tokenizer: FXEasyTokenizer,\n        named_polarity_to_class_number,\n        class_number_to_named_polarity,\n        sorted_expected_label_names,\n        single_targets: bool,\n        coref_mode: str,\n        devmode=False,\n        ignore_parsing_errors=False,\n    ):\n        self.class_label2class_number = named_polarity_to_class_number\n        self.class_number2class_label = class_number_to_named_polarity\n        self.sorted_expected_label_names = sorted_expected_label_names\n        self.tokenizer = tokenizer\n        self.data = []\n        self.data_format = data_format\n        self.count_sequence_overflow = Counter()\n        FXDataset.SINGLE_TARGETS = single_targets\n\n        if FXDataset.SINGLE_TARGETS:\n            # single mode is enabled, so there will be only 1 target per item\n            FXDataset.NUM_MAX_TARGETS_PER_ITEM = 1\n\n        logger.info(\"reading dataset file {}\".format(filepath))\n\n        tasks = []\n        with jsonlines.open(filepath, \"r\") as reader:\n            for task in reader:\n                task[\"sentence_normalized\"] = self.__prepare_text_field(\n                    task[\"sentence_normalized\"]\n                )\n                for target in task[\"targets\"]:\n                    target[\"mention\"] = self.__prepare_text_field(target[\"mention\"])\n                    further_mentions = []\n                    for further_mention in target.get(\"further_mentions\", []):\n                        further_mention[\"mention\"] = self.__prepare_text_field(\n                            further_mention[\"mention\"]\n                        )\n                        further_mentions.append(further_mention)\n                    target[\"further_mentions\"] = further_mentions\n                tasks.append(task)\n\n        if devmode:\n            k = 5\n            logger.warning(\"DEV MODE IS ENABLED\")\n            logger.info(\"devmode=True: truncating dataset to {} lines\".format(k))\n            tasks = tasks[:k]\n\n        self.label_counter = Counter()\n        with tqdm(total=len(tasks)) as pbar:\n            for task in tasks:\n                # create model items from this jsonl row (in case of single_targets\n                # enabled, a row with k targets will return k model items)\n                model_items = self.task_to_dataset_item(\n                    task, coref_mode, ignore_parsing_errors\n                )\n                for converted_item, count_labels in model_items:\n                    if converted_item is None:\n                        # this will happen if an example has 0 targets -> ignore\n                        self.label_counter[\"ignored_example\"] += 1\n                    else:\n                        self.label_counter += count_labels\n                        self.data.append(converted_item)\n                pbar.update(1)\n        logger.info(\"label distribution: {}\".format(self.label_counter))\n\n    def __prepare_text_field(self, text: str):\n        \"\"\"\n        Replaces \"invalid\" characters with something else of the same length (same\n        length is important so that the offsets in the dataset are still valid)\n        :param text:\n        :return:\n        \"\"\"\n        return text.replace(\"\\xa0\", \" \").replace(\"��\", \"  \")\n\n    def __create_target_text_components(\n        self,\n        target_start_char,\n        target_end_char,\n        text,\n        check_mention,\n        ignore_parsing_errors,\n    ):\n        target_check_mention = text[target_start_char:target_end_char]\n        text_left = text[:target_start_char]\n        text_right = text[target_end_char:]\n        # perform target mention check\n        if ignore_parsing_errors:\n            if check_mention != target_check_mention:\n                logger.warning(\n                    f\"indexes do not match: '{check_mention}' vs '{target_check_mention}' \"\n                    f\"({text_left}; {text_right}; {target_start_char}; {target_end_char})\"\n                )\n        else:\n            assert check_mention == target_check_mention, (\n                f\"indexes do not match: '{check_mention}' vs '{target_check_mention}' \"\n                f\"({text_left}; {text_right}; {target_start_char}; {target_end_char})\"\n            )\n\n        return text_left, text_right\n\n    def __parse_dataset_row(self, task, ignore_parsing_errors):\n        if self.data_format == \"newsmtsc\":\n            _text = task[\"sentence_normalized\"]\n            primary_mtsc_gid = task[\"primary_gid\"]\n            if not FXDataset.SINGLE_TARGETS:\n                # if single_targets mode is not enabled, ensure each item has at most\n                # FXDataset.NUM_MAX_TARGETS_PER_ITEM targets\n                # assert 1 <= len(task[\"targets\"]) <= FXDataset.NUM_MAX_TARGETS_PER_ITEM\n                pass\n            else:\n                # if single_targets mode is enabled, FXDataset.NUM_MAX_TARGETS_PER_ITEM\n                # was set to 1, so we cannot perform the check at this point. and also\n                # do not need to ensure because later we will expand the items so that\n                # resulting items each will only have 1 target\n                pass\n\n            # perform validity check of target mention\n            # also, add text_left and text_right to each target\n            for target in task[\"targets\"]:\n                target_ae_gid = target[\"Input.gid\"]\n                target_start_char = target[\"from\"]\n                target_end_char = target[\"to\"]\n                target_mention = target[\"mention\"]\n                target_polarity = target[\"polarity\"]\n\n                text_left, text_right = self.__create_target_text_components(\n                    target_start_char,\n                    target_end_char,\n                    _text,\n                    target_mention,\n                    ignore_parsing_errors,\n                )\n\n                # add target-specific text_left and text_right\n                target[\"text_left\"] = text_left\n                target[\"text_right\"] = text_right\n\n            targets = task[\"targets\"]\n            return primary_mtsc_gid, _text, targets\n        else:\n            raise ValueError(f\"data format unknown: {self.data_format}\")\n\n    def _create_target_inputs(\n        self,\n        text_left: str,\n        target_mention: str,\n        text_right: str,\n        target_gid: str,\n        polarity: float,\n        count_labels: Counter,\n        coreferential_targets_for_target_mask: Iterable[dict],\n        is_fillup: bool,\n    ):\n        # always convert polarity to float\n        polarity = float(polarity)\n\n        # earlier, we assumed basic tokanization, e.g., that \"Mr. Smith's statement\n        # is stupid.\" was already tokenized into \"Mr. Smith 's statement is stupid .\"\n        # however, since both encode and encode_plus internally perform tokenization\n        # when invoked with a str object, we do not need to assume that the input is\n        # already tokenized.\n        # here is how we handle the input text and target phrase\n        # 1) we ensure that there is a whitespace between left and target. if there\n        #    is no whitespace, we add a whitespace to the end of left\n        # 2) we do the same as in (1) for target and right, and if necessary add a\n        #    whitespace to the beginning of right\n        # by doing these two operations, we ensure that any target-dependent mapping\n        # e.g., the target mask, can be mapped 1:1 to the the input text. for\n        # example, \"<target>Mr. Smith</target>'s statement is stupid.\" will be\n        # converted into \"Mr. Smith 's statement ...\" this way, the LM's encode or\n        # encode_plus function will (after internal tokenization) yield a list of\n        # input indexes that we can unambiguously map to the target mask that we\n        # produce ourselves, e.g., in FXEasyTokenizer:_create_target_mask. said\n        # differently, by adding the whitespace, we ensure that \"Mr. Smith\" will be\n        # mapped to its own indexes, whereas if we passed \"Mr. Smith's\", this might\n        # yield different indexes, e.g., if \"Smith's\" is part of the LM's\n        # tokenizer's vocabulary. for more information, see NA-633 and NA-643.\n        text_left = FXEasyTokenizer.prepare_left_segment(text_left)\n        target_mention = FXEasyTokenizer.prepare_target_mention(target_mention)\n        text_right = FXEasyTokenizer.prepare_right_segment(text_right)\n        text = FXEasyTokenizer.create_entire_text(\n            text_left,\n            target_mention,\n            text_right,\n            is_return_modified_text_left=False,\n        )\n\n        # text to indexes\n        try:\n            inputs_of_target = self.tokenizer.create_model_input_seqs(\n                text_left,\n                target_mention,\n                text_right,\n                coreferential_targets_for_target_mask,\n            )\n        except TooLongTextException:\n            logger.error(\n                \"text is too long for target mask creation for target_gid=%s, ignoring target\",\n                target_gid,\n            )\n            return None\n        except TargetNotFoundException as tnfe:\n            logger.error(\n                \"target was not found after preprocessing when calculating \"\n                \"distance hop for target_gid=%s, ignoring target (error msg: %s)\",\n                target_gid,\n                str(tnfe),\n            )\n            return None\n\n        # count overflow\n        for tokenizer_name in self.tokenizer.tokenizers_name_and_obj.keys():\n            if inputs_of_target[tokenizer_name][\"is_overflow\"]:\n                self.count_sequence_overflow[tokenizer_name] += 1\n                self.count_sequence_overflow[\"all\"] += 1\n\n        # add polarity\n        inputs_of_target[\"polarity\"] = SentimentClasses.polarity2normalized_polarity(\n            polarity\n        )\n        inputs_of_target[\"label\"] = SentimentClasses.polarity2label(polarity)\n        # update stats\n        count_labels[inputs_of_target[\"label\"]] += 1\n\n        # add reference information\n        inputs_of_target[\"target_gid\"] = target_gid\n\n        # add original text and target (we can use that to create a mistake table)\n        inputs_of_target[\"orig_text\"] = text\n        inputs_of_target[\"orig_target\"] = target_mention\n        inputs_of_target[\"orig_polarity\"] = polarity\n\n        # add whether fill up target (fake) or real\n        inputs_of_target[\"is_fillup\"] = is_fillup\n\n        return inputs_of_target\n\n    def _create_fillup_target(self):\n        return self._create_target_inputs(\n            text_left=\" \",\n            target_mention=\"fillup\",\n            text_right=\" \",\n            target_gid=\"fillup\",\n            polarity=SentimentClasses.FILLUP_POLARITY_VALUE,\n            count_labels=Counter(),\n            coreferential_targets_for_target_mask=[],\n            is_fillup=True,\n        )\n\n    def _get_as_list(self, lst_inputs_of_targets: List[dict], key: str):\n        \"\"\"\n        selects the value under the key in each\n        list element of lst_inputs_of_targets. returns these values as a new list\n        :param lst_inputs_of_targets:\n        :param key:\n        :return:\n        \"\"\"\n        new_list = []\n        for inputs_of_targets in lst_inputs_of_targets:\n            new_list.append(inputs_of_targets[key])\n        return new_list\n\n    def _get_values_as_lists_in_dict(\n        self, lst_inputs_of_targets: List[dict], keys: Iterable[str]\n    ):\n        d = {}\n        for key in keys:\n            d[key] = self._get_as_list(lst_inputs_of_targets, key)\n        return d\n\n    def _convert_multi_targets_in_single_item_to_single_target_in_multi_items(\n        self, example_id, text, targets\n    ):\n        \"\"\"\n        Converts a single item with k targets into k items with 1 target each\n        :param example_id:\n        :param text:\n        :param targets:\n        :return: list of tuples (example_id, text, targets)\n        \"\"\"\n        single_items = []\n        for target in targets:\n            single_example_id = target[\"Input.gid\"]\n            single_text = text\n            single_targets = [target]\n            single_item = (single_example_id, single_text, single_targets)\n            single_items.append(single_item)\n        return single_items\n\n    def _convert_multi_targets_in_single_item_to_k_targets_in_multi_items(\n        self, example_id, text, targets\n    ):\n        \"\"\"\n        Converts a single item with m targets into ceil(m/k) items with k items. If a\n        resulting item would have less than k targets, its existing targets are repeated\n        so that each item will have exactly k targets (in this case with duplicate\n        targets).\n        :param example_id:\n        :param text:\n        :param targets:\n        :return:\n        \"\"\"\n        shuffled_targets = targets.copy()\n        random.shuffle(shuffled_targets)\n        num_targets_per_item = FXDataset.NUM_MAX_TARGETS_PER_ITEM\n        logger.debug(shuffled_targets)\n\n        items = []\n        count_processed_targets = 0\n        for i in range(0, len(shuffled_targets), num_targets_per_item):\n            cur_targets = shuffled_targets[i : i + num_targets_per_item]\n            if len(cur_targets) < num_targets_per_item:\n                logger.debug(\"too few targets\")\n                break\n            assert len(cur_targets) == num_targets_per_item\n            virtual_example_id = example_id + \"_\" + str(i)\n            items.append((virtual_example_id, text, cur_targets))\n            count_processed_targets += len(cur_targets)\n\n        # process remaining targets\n        logger.debug(\"processing remaining targets\")\n        if count_processed_targets < len(shuffled_targets):\n            remaining_targets = shuffled_targets[count_processed_targets:]\n            assert len(remaining_targets) < num_targets_per_item\n\n            # duplicate targets until we have enough targets\n            # create intermediate list to not skew random selection because of adding\n            # the duplicates immediately\n            tmp_targets = []\n            while len(remaining_targets) + len(tmp_targets) < num_targets_per_item:\n                tmp_targets.append(random.choice(remaining_targets))\n                logger.debug(\n                    f\"{len(remaining_targets)}, {len(tmp_targets)}, {num_targets_per_item}\"\n                )\n            remaining_targets.extend(tmp_targets)\n            assert len(remaining_targets) == num_targets_per_item\n            virtual_example_id = example_id + \"_last\"\n            items.append((virtual_example_id, text, remaining_targets))\n\n        # validation\n        count_targets = 0\n        seen_targets = []\n        for item in items:\n            targets = item[2]\n            count_targets += len(targets)\n            for target in targets:\n                seen_targets.append(target)\n        assert count_targets % num_targets_per_item == 0\n        # seen targets must either be of same length as shuffled target, or - in case of\n        # added duplicate targets - larger\n        assert len(seen_targets) >= len(\n            shuffled_targets\n        ), f\"{len(seen_targets)} vs. {len(shuffled_targets)}\"\n\n        return items\n\n    def _create_item_for_model(self, example_id, text, targets):\n        lst_inputs_of_targets = []\n        count_labels = Counter()\n\n        for target in targets:\n            text_left = target[\"text_left\"]\n            text_right = target[\"text_right\"]\n            target_mention = target[\"mention\"]\n            polarity = target[\"polarity\"]\n            target_gid = target[\"Input.gid\"]\n            coreferential_targets_for_target_mask = target.get(\n                \"coreferential_targets_for_target_mask\", []\n            )\n\n            inputs_of_target = self._create_target_inputs(\n                text_left=text_left,\n                target_mention=target_mention,\n                text_right=text_right,\n                target_gid=target_gid,\n                polarity=polarity,\n                count_labels=count_labels,\n                coreferential_targets_for_target_mask=coreferential_targets_for_target_mask,\n                is_fillup=False,\n            )\n            if inputs_of_target is None:\n                # this will happen if a target mask could not be created because the\n                # text_left is too long. -> ignore this target\n                pass\n            else:\n                lst_inputs_of_targets.append(inputs_of_target)\n        num_actual_targets = len(lst_inputs_of_targets)\n\n        if num_actual_targets == 0:\n            logger.error(\n                \"ignoring example (gid=%s) because it has 0 targets\", example_id\n            )\n            return None, None\n\n        # due to torch's requirements in dataloader, we need fill up remaining targets\n        # with fake targets\n        while len(lst_inputs_of_targets) < FXDataset.NUM_MAX_TARGETS_PER_ITEM:\n            lst_inputs_of_targets.append(self._create_fillup_target())\n\n        # lastly, merge inputs to one tensor over all targets\n        # this also removes some fields, e.g., list of strs. should we need the removed\n        # information later, we could simply add a new field below to \"converted_item\"\n        stacked_targets, skipped_keys = self._stack_target_inputs(lst_inputs_of_targets)\n\n        # create item dict\n        # originally, we also had original targets here, but they get scrambled up and\n        # there is no StrTensor to easily preserve their order\n        converted_item = {\n            \"text\": text,\n            \"num_targets\": num_actual_targets,\n            \"primary_gid\": example_id,\n        }\n\n        # merge stacked_targets dict into item\n        # first, though, ensure no overlap by key\n        assert len(set(converted_item.keys()).intersection(stacked_targets.keys())) == 0\n        # now merge\n        converted_item = {**converted_item, **stacked_targets}\n\n        return converted_item, count_labels\n\n    def create_virtual_target_from_target_mention(self, target, mention, text):\n        mention_from = mention[\"from\"]\n        mention_to = mention[\"to\"]\n        mention_text = mention[\"mention\"]\n\n        mention_gid = target[\"Input.gid\"] + \"__\" + mention_text\n        mention_polarity = target[\"polarity\"]\n\n        text_left, text_right = self.__create_target_text_components(\n            mention_from, mention_to, text, mention_text, False\n        )\n\n        return {\n            \"Input.gid\": mention_gid,\n            \"from\": mention_from,\n            \"to\": mention_to,\n            \"mention\": mention_text,\n            \"polarity\": mention_polarity,\n            \"text_left\": text_left,\n            \"text_right\": text_right,\n        }\n\n    def _expand_coref_mentions_of_targets_to_multiple_targets(\n        self, targets: Iterable, text: str\n    ):\n        expanded_targets = []\n        for target in targets:\n            expanded_targets.append(target)\n\n            further_mentions = target.get(\"further_mentions\", [])\n            for further_mention in further_mentions:\n                virtual_target = self.create_virtual_target_from_target_mention(\n                    target, further_mention, text\n                )\n                expanded_targets.append(virtual_target)\n\n        return expanded_targets\n\n    def task_to_dataset_item(self, task, coref_mode: str, ignore_parsing_errors):\n        # parse current dataset row (=task)\n        example_id, text, targets = self.__parse_dataset_row(\n            task, ignore_parsing_errors\n        )\n\n        # if the coref mode (only during training though) is additional_examples, repeat them here\n        if coref_mode == \"additional_examples\":\n            expanded_targets = (\n                self._expand_coref_mentions_of_targets_to_multiple_targets(\n                    targets, text\n                )\n            )\n        elif coref_mode == \"in_targetmask\":\n            expanded_targets = targets\n            for target in expanded_targets:\n                further_mentions = target.get(\"further_mentions\", [])\n                targets_for_target_mask = []\n                for further_mention in further_mentions:\n                    virtual_target = self.create_virtual_target_from_target_mention(\n                        target, further_mention, text\n                    )\n                    targets_for_target_mask.append(virtual_target)\n                target[\n                    \"coreferential_targets_for_target_mask\"\n                ] = targets_for_target_mask\n        else:\n            # if coref mode is ignore, nothing to do here\n            expanded_targets = targets\n\n        # if single_targets mode is enabled, we want to have only one target for each\n        # sentence, thus expand sentences\n        if FXDataset.SINGLE_TARGETS:\n            items = self._convert_multi_targets_in_single_item_to_single_target_in_multi_items(\n                example_id, text, expanded_targets\n            )\n        else:\n            items = (\n                self._convert_multi_targets_in_single_item_to_k_targets_in_multi_items(\n                    example_id, text, expanded_targets\n                )\n            )\n\n        # iterate (virtual) items of this actual row in the jsonl and create model items\n        model_items = []\n        for example_id, text, targets in items:\n            res = self._create_item_for_model(example_id, text, targets)\n            model_items.append(res)\n\n        # return\n        return model_items\n\n    def __getitem__(self, index):\n        return self.data[index]\n\n    def __len__(self):\n        return len(self.data)\n\n    @staticmethod\n    def set_params2index(params2index: dict):\n        if len(FXDataset.__PARAMS2INDEX) > 0:\n            # verify the new one is same\n            assert FXDataset.__PARAMS2INDEX == params2index\n        else:\n            FXDataset.__PARAMS2INDEX = params2index\n\n    @staticmethod\n    def get_input_by_params(inputs: List, weight_name: str, field_name: str):\n        \"\"\"\n        If FXDataset.SINGLE_TARGETS is True, include the target dimension (currently 2nd\n        dimension in tensor (dims are: batch, target, indexes or other values). If\n        False, remove the target dimension.\n        :param inputs:\n        :param weight_name:\n        :param field_name:\n        :param include_target_dimension:\n        :return:\n        \"\"\"\n        param_id = (weight_name, field_name)\n        seq = inputs[FXDataset.__PARAMS2INDEX[param_id]]\n        if not FXDataset.SINGLE_TARGETS:\n            return seq\n        else:\n            assert seq.shape[1] == 1, \"there are more than one targets\"\n            return seq.squeeze(dim=1)\n\n    @staticmethod\n    def get_all_inputs_for_model(inputs: List, model_class: FXBaseModel):\n        selected_inputs = []\n        for weight_name, field_name in model_class.get_input_field_ids():\n            selected_inputs.append(\n                FXDataset.get_input_by_params(inputs, weight_name, field_name)\n            )\n        return inputs\n\n    def _stack_target_inputs(self, lst_inputs_of_targets: List[dict]) -> dict:\n        \"\"\"\n        stacks each field to one Tensor\n        :param lst_inputs_of_targets:\n        :return:\n        \"\"\"\n        # ensure correct number of targets\n        assert len(lst_inputs_of_targets) == self.NUM_MAX_TARGETS_PER_ITEM\n        # ensure each target has same keys\n        all_keys = list(lst_inputs_of_targets[0].keys())\n        for inputs_of_target in lst_inputs_of_targets:\n            assert set(all_keys) == inputs_of_target.keys()\n        # for each key, merge all targets\n        merged_targets = {}\n\n        # to collect keys that were skipped\n        skipped_keys = []\n\n        # keys that not \"scalars\", e.g., polarity, but dicts, e.g., \"bert-base-uncased\",\n        # which itself holds multiple vectors, require special handling\n        special_keys = list(self.tokenizer.tokenizers_name_and_obj.keys())\n        # iterate keys\n        for key in all_keys:\n            if key in special_keys:\n                merged_targets[key] = self._stack_special_field(\n                    key, lst_inputs_of_targets\n                )\n            else:\n                inputs_over_targets_of_key = []\n                for inputs_of_target in lst_inputs_of_targets:\n                    inputs_over_targets_of_key.append(inputs_of_target[key])\n\n                # merge targets' inputs to one tensor\n                stacked_inputs_over_targets_of_key = self._stack_or_create_tensor(\n                    inputs_over_targets_of_key\n                )\n                # add stacked tensor to dict\n                if stacked_inputs_over_targets_of_key is not None:\n                    merged_targets[key] = stacked_inputs_over_targets_of_key\n                else:\n                    # if None, dont add\n                    logger.debug(\"skipping key: %s\", key)\n                    skipped_keys.append(key)\n\n        return merged_targets, skipped_keys\n\n    def _stack_special_field(self, key: str, lst_inputs_of_targets: List[dict]):\n        # ensure each target has same sub keys for current selected key\n        all_sub_keys = list(lst_inputs_of_targets[0][key].keys())\n        for inputs_of_target in lst_inputs_of_targets:\n            assert set(all_sub_keys) == inputs_of_target[key].keys()\n\n        # for each sub key, merge all targets\n        merged_targets = {}\n\n        for sub_key in all_sub_keys:\n            inputs_over_targets_of_sub_key = []\n            for inputs_of_target in lst_inputs_of_targets:\n                # select\n                inputs = inputs_of_target[key][sub_key]\n                inputs_over_targets_of_sub_key.append(inputs)\n            # merge targets' inputs to one tensor\n            stacked_inputs_over_targets_of_sub_key = self._stack_or_create_tensor(\n                inputs_over_targets_of_sub_key\n            )\n            # add stacked tensor to dict\n            if stacked_inputs_over_targets_of_sub_key is not None:\n                merged_targets[sub_key] = stacked_inputs_over_targets_of_sub_key\n            else:\n                # if None, dont add\n                logger.debug(\"skipping key: %s\", sub_key)\n\n        return merged_targets\n\n    def _stack_or_create_tensor(self, lst_values: List):\n        \"\"\"\n        Given a list of values, checks if all are of same type and creates a single\n        Tensor from the values (either by stacking or by creation)\n        :param lst_values:\n        :return:\n        \"\"\"\n        # assert all same type\n        first_type = type(lst_values[0])\n        for val in lst_values:\n            assert first_type == type(val), f\"{first_type} vs {type(val)}\"\n\n        # stack list of tensors to one tensor\n        if first_type == bool:\n            # if bool, create a new tensor\n            stacked_inputs_over_targets_of_sub_key = torch.BoolTensor(lst_values)\n        elif first_type == int:\n            # we need to have Long here, otherwise will run into an error during loss\n            # calculation, where Long is expected\n            stacked_inputs_over_targets_of_sub_key = torch.LongTensor(lst_values)\n        elif first_type == float:\n            stacked_inputs_over_targets_of_sub_key = torch.FloatTensor(lst_values)\n        elif first_type == str:\n            stacked_inputs_over_targets_of_sub_key = None\n        elif torch.is_tensor(lst_values[0]):\n            # if Tensor of subtype, stack\n            stacked_inputs_over_targets_of_sub_key = torch.stack(lst_values)\n        else:\n            raise NotImplementedError(f\"no merging for type: {first_type}\")\n\n        return stacked_inputs_over_targets_of_sub_key\n"
  },
  {
    "path": "NewsSentiment/diskdict.py",
    "content": "from pathlib import Path\nimport pickle\nfrom typing import Union\n\nfrom NewsSentiment.fxlogger import get_logger\n\nlogger = get_logger()\n\n\nclass DiskDict(dict):\n    def __init__(self, sync_path: Union[Path, str]):\n        if type(sync_path) == str:\n            sync_path = Path(sync_path)\n        self.path = sync_path\n\n        if self.path.exists():\n            with open(self.path, \"rb\") as file:\n                tmp_dct = pickle.load(file)\n                super().update(tmp_dct)\n                logger.info(\n                    \"loaded DiskDict with %s items from %s\", len(tmp_dct), self.path\n                )\n\n    def sync_to_disk(self):\n        with open(self.path, \"wb\") as file:\n            tmp_dct = super().copy()\n            pickle.dump(tmp_dct, file)\n            # print(f\"saved DiskDict with {len(tmp_dct)} items to {self.path}\")\n"
  },
  {
    "path": "NewsSentiment/download.py",
    "content": "\"\"\"\nDownload a specific version of a finetuned model and place it in pretrained_models.\n\"\"\"\nimport os\nimport string\n\nimport torch\n\nfrom NewsSentiment.fxlogger import get_logger\n\n\nclass Download:\n\n    def __init__(\n        self, own_model_name, version=\"default\", force=False, list_versions=False\n    ):\n        from NewsSentiment.models.FXBaseModel import model_includes_pretrained\n        from NewsSentiment.train import OWN_MODELNAME2CLASS\n\n        logger = get_logger()\n        own_model_name = own_model_name\n        if version == \"default\":\n            version = None\n        try:\n            model_cls = OWN_MODELNAME2CLASS[own_model_name]\n        except KeyError:\n            logger.error(f'Model \"{own_model_name}\" is unknown.')\n            exit(2)\n        if not model_includes_pretrained(model_cls):\n            logger.error(\n                f'Model \"{own_model_name}\" does not ship any pretrained models for download.'\n            )\n            exit(2)\n        if list_versions:\n            self.list_versions(model_cls, own_model_name)\n        else:\n            self.download(model_cls, version, force)\n\n    @staticmethod\n    def list_versions(model_cls, own_model_name=\"\"):\n        default = model_cls.get_pretrained_default_version()\n        versions = model_cls.get_pretrained_versions()\n        if own_model_name:\n            own_model_name = f' \"{own_model_name}\"'\n        print(f\"Model{own_model_name} provides following pretrained versions:\")\n        for version, source in versions.items():\n            default_str = \"\"\n            if version == default:\n                default_str = \" (default)\"\n            print(f'\"{version}\"{default_str}: {source}')\n\n    @classmethod\n    def download(cls, model_cls, version=None, force=False, skip_if_exists=True):\n        source = model_cls.get_pretrained_source(version)\n        path = cls.model_path(model_cls, version)\n        if not force and os.path.isfile(path):\n            if skip_if_exists:\n                return\n            print(\"Model file already exists. Use --force to overwrite.\")\n            exit(2)\n        print(f\"Downloading to {path}:\")\n        os.makedirs(os.path.dirname(path), exist_ok=True)\n        torch.hub.download_url_to_file(source, path)\n        return path\n\n    @staticmethod\n    def model_filename(model_cls, version=None):\n        version = version or model_cls.get_pretrained_default_version()\n        source_filename = os.path.basename(model_cls.get_pretrained_source(version))\n        name = f\"{source_filename}_{version}\"\n        allowed = set(f\".-_ {string.ascii_letters}{string.digits}\")\n        filename = \"\".join(char for char in name if char in allowed)\n        return filename.replace(\".\", \"-\").replace(\" \", \"_\")\n\n    @classmethod\n    def model_path(cls, model_cls, version=None):\n        return os.path.join(torch.hub.get_dir(),\n                            \"pretrained_models\",\n                            \"state_dicts\",\n                            cls.model_filename(model_cls, version))\n\n    @staticmethod\n    def add_subparser(subparser):\n        \"\"\"Download models for NewsSentiment\"\"\"\n        subparser.add_argument(\"--own_model_name\", default=\"grutsc\", type=str)\n        subparser.add_argument(\n            \"--version\",\n            default=None,\n            type=str,\n            help=\"version of the model to download, use --force to overwrite a version which was already downloaded\",\n        )\n        subparser.add_argument(\n            \"--force\",\n            action=\"store_true\",\n            help=\"force the download of a model and overwrite potential previous versions\",\n        )\n        subparser.add_argument(\n            \"--list_versions\",\n            action=\"store_true\",\n            help=\"List all pretrained model versions which a model provides\",\n        )\n        return subparser\n\n    @classmethod\n    def run_from_parser(cls, args_namespace):\n        args = vars(args_namespace)\n        return cls(**args)\n\n"
  },
  {
    "path": "NewsSentiment/earlystopping.py",
    "content": "# taken from https://github.com/Bjarten/early-stopping-pytorch\n# Copyright by Bjarten\n# License: MIT\n\nfrom NewsSentiment.fxlogger import get_logger\n\n\nclass EarlyStopping:\n    \"\"\"Early stops the training if validation loss doesn't improve after a given patience.\"\"\"\n\n    def __init__(self, patience=2, delta=0.01):\n        \"\"\"\n        Args:\n            patience (int): How long to wait after last time validation loss improved.\n                            Default: 2\n            verbose (bool): If True, prints a message for each validation loss improvement.\n                            Default: False\n            delta (float): Minimum change in the monitored quantity to qualify as an improvement.\n                            Default: 0\n        \"\"\"\n        self.patience = patience\n        self.counter = 0\n        self.best_score = None\n        self.early_stop = False\n        self.delta = delta\n        self.logger = get_logger()\n        self.flag_has_score_increased_since_last_check = False\n\n    def __call__(self, dev_score):\n        if self.best_score is None:\n            self.best_score = dev_score\n            self.logger.debug(f'computed first dev-set score {dev_score:.6f}).')\n            self.flag_has_score_increased_since_last_check = True\n        elif dev_score < self.best_score + self.delta:\n            self.counter += 1\n            self.logger.debug(\n                f'patience counter: {self.counter} out of {self.patience} (cur-score: {dev_score}, best-score:'\n                f' {self.best_score})')\n            self.flag_has_score_increased_since_last_check = False\n            if self.counter >= self.patience:\n                self.early_stop = True\n        else:\n            self.best_score = dev_score\n            self.counter = 0\n            self.logger.debug(f'dev-set score increased ({self.best_score:.6f} --> {dev_score:.6f}).')\n            self.flag_has_score_increased_since_last_check = True\n"
  },
  {
    "path": "NewsSentiment/evaluator.py",
    "content": "from collections import Counter\nfrom statistics import mean\n\nimport jsonlines\nimport numpy as np\nfrom sklearn import metrics\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.fxlogger import get_logger\nimport torch\n\n\nclass Evaluator:\n    def __init__(\n        self,\n        sorted_expected_label_values,\n        polarity_associations,\n        snem_name,\n        is_return_confidence,\n    ):\n        self.logger = get_logger()\n        self.polarity_associations = polarity_associations\n        self.pos_label_value = polarity_associations[\"positive\"]\n        self.neg_label_value = polarity_associations[\"negative\"]\n        self.sorted_expected_label_values = sorted_expected_label_values\n        self.pos_label_index = self.sorted_expected_label_values.index(\n            self.pos_label_value\n        )\n        self.neg_label_index = self.sorted_expected_label_values.index(\n            self.neg_label_value\n        )\n        self.snem_name = snem_name\n        self.is_return_confidence = is_return_confidence\n\n    def mean_from_all_statistics(self, all_test_stats):\n        # for Counters, we do not take the mean\n        mean_test_stats = {}\n        number_stats = len(all_test_stats)\n\n        for key in all_test_stats[0]:\n            value_type = type(all_test_stats[0][key])\n\n            if value_type in [float, np.float64, np.float32]:\n                aggr_val = 0.0\n                for test_stat in all_test_stats:\n                    aggr_val += test_stat[key]\n\n                mean_test_stats[key] = aggr_val / number_stats\n\n            elif value_type == Counter:\n                aggr_val = Counter()\n                for test_stat in all_test_stats:\n                    aggr_val += test_stat[key]\n                mean_test_stats[key] = aggr_val\n\n        return mean_test_stats\n\n    def calc_statistics(self, y_true, y_pred, y_pred_confidence):\n        \"\"\"\n        Calculates performance statistics by comparing k-dimensional Tensors y_true and\n        y_pred. Both y_true and y_pred's shape have to be(batchsize, maxtargetsperexample)\n        :param y_true:\n        :param y_pred:\n        :return:\n        \"\"\"\n        assert y_true.shape == y_pred.shape, \"different shapes\"\n        assert y_true.shape[1] == FXDataset.NUM_MAX_TARGETS_PER_ITEM\n\n        # for now, the following doesn't keep track of which prediction or true answer\n        # belongs to which examples. for other measures, this might be necessary, though\n        # in that case, the code would have to be changed, e.g., by keeping the original\n        # dimensions. for now, we just unpack the Tensors to so that the former\n        # evaluation logic will work on them. practically, this treats each non-fillup\n        # target as an example\n        y_true = y_true.view(-1)\n        y_pred = y_pred.view(-1)\n        if y_pred_confidence is not None:\n            y_pred_confidence = y_pred_confidence.view(-1)\n\n        # in both tensors, keep only those scalars that are non-fill in y_true\n        non_fillup_mask = y_true != SentimentClasses.FILLUP_POLARITY_VALUE\n        y_true = y_true[non_fillup_mask]\n        y_pred = y_pred[non_fillup_mask]\n        if y_pred_confidence is not None:\n            y_pred_confidence = y_pred_confidence[non_fillup_mask].tolist()\n\n        # this is just the previous, single-target evaluation logic\n        y_true_list = y_true.tolist()\n        y_pred_list = y_pred.tolist()\n        y_true_count = Counter(y_true_list)\n        y_pred_count = Counter(y_pred_list)\n        confidence_info = {}\n\n        # perform confidence evaluation if vector was given\n        if y_pred_confidence is not None:\n            # compare where equal for confidence evaluation\n            is_correct_list = []\n            for index in range(len(y_true_list)):\n                y_true_item = y_true_list[index]\n                y_pred_item = y_pred_list[index]\n                if y_true_item == y_pred_item:\n                    is_correct_list.append(1)\n                else:\n                    is_correct_list.append(0)\n            # now we have a list whether the prediction is correct (1) or not (0)\n            # let's compare it with the confidence\n\n            # regression metrics\n            mse = metrics.mean_squared_error(is_correct_list, y_pred_confidence)\n            r2_score = metrics.r2_score(is_correct_list, y_pred_confidence)\n\n            # convert to classification problem (uses 0.5 threshold)\n            y_pred_confidence_classification = (\n                torch.FloatTensor(y_pred_confidence) > 0.5\n            ).tolist()\n\n            f1_macro_conf = metrics.f1_score(\n                is_correct_list, y_pred_confidence_classification, average=\"macro\"\n            )\n            accuracy_conf = metrics.accuracy_score(\n                is_correct_list, y_pred_confidence_classification\n            )\n            f1_of_classes = metrics.f1_score(\n                is_correct_list, y_pred_confidence_classification, average=None\n            ).tolist()\n\n            confidence_info = {\n                \"f1m\": f1_macro_conf,\n                \"acc\": accuracy_conf,\n                \"f1_classes\": f1_of_classes,\n                \"mse\": mse,\n                \"r2score\": r2_score,\n                \"y_pred_confidence_classification\": y_pred_confidence_classification,\n                \"y_pred_confidence\": y_pred_confidence,\n                \"y_true_confidence\": is_correct_list,\n            }\n\n        f1_macro = metrics.f1_score(\n            y_true, y_pred, labels=self.sorted_expected_label_values, average=\"macro\"\n        )\n        f1_of_classes = metrics.f1_score(\n            y_true, y_pred, labels=self.sorted_expected_label_values, average=None\n        )\n        f1_posneg = (\n            f1_of_classes[self.pos_label_index] + f1_of_classes[self.neg_label_index]\n        ) / 2.0\n        confusion_matrix = metrics.confusion_matrix(\n            y_true, y_pred, labels=self.sorted_expected_label_values\n        )\n        recalls_of_classes = metrics.recall_score(\n            y_true, y_pred, labels=self.sorted_expected_label_values, average=None\n        )\n        recall_avg = mean(recalls_of_classes)\n        recall_macro = metrics.recall_score(\n            y_true, y_pred, labels=self.sorted_expected_label_values, average=\"macro\"\n        )\n        precision_macro = metrics.precision_score(\n            y_true, y_pred, labels=self.sorted_expected_label_values, average=\"macro\"\n        )\n        accuracy = metrics.accuracy_score(y_true, y_pred)\n\n        results = {\n            \"f1_macro\": f1_macro,\n            \"confusion_matrix\": confusion_matrix,\n            \"recalls_of_classes\": recalls_of_classes,\n            \"recall_avg\": recall_avg,\n            \"recall_macro\": recall_macro,\n            \"precision_macro\": precision_macro,\n            \"accuracy\": accuracy,\n            \"f1_posneg\": f1_posneg,\n            \"y_true_count\": y_true_count,\n            \"y_pred_count\": y_pred_count,\n        }\n        if y_pred_confidence is not None:\n            results[\"confidence_info\"] = confidence_info\n\n        return results\n\n    def print_stats(self, stats, description):\n        self.logger.info(description)\n        self.logger.info(\"{}: {})\".format(self.snem_name, stats[self.snem_name]))\n        self.logger.info(\n            \"y_true distribution: {}\".format(sorted(stats[\"y_true_count\"].items()))\n        )\n        self.logger.info(\n            \"y_pred distribution: {}\".format(sorted(stats[\"y_pred_count\"].items()))\n        )\n        self.logger.info(\n            \"> recall_avg: {:.4f}, f1_posneg: {:.4f}, acc: {:.4f}, f1_macro: {:.4f}\".format(\n                stats[\"recall_avg\"],\n                stats[\"f1_posneg\"],\n                stats[\"accuracy\"],\n                stats[\"f1_macro\"],\n            )\n        )\n\n    def write_error_table(self, y_true, y_pred, texts_list, filepath):\n        y_true_list = y_true.tolist()\n        y_pred_list = y_pred.tolist()\n\n        with jsonlines.open(filepath, \"w\") as writer:\n            for true_label, pred_label, text in zip(\n                y_true_list, y_pred_list, texts_list\n            ):\n                writer.write(\n                    {\"true_label\": true_label, \"pred_label\": pred_label, \"text\": text}\n                )\n"
  },
  {
    "path": "NewsSentiment/experiments/default/datasets/newsmtsc-mt/dev.jsonl",
    "content": "{\"primary_gid\": \"allsides_6250_2689_12_Barack Obama_73_78\", \"sentence_normalized\": \"Both the Gallup and Rasmussen tracking surveys have also found boosts in Obama's job approval rating.\", \"targets\": [{\"Input.gid\": \"allsides_6250_2689_12_President Barack Obama_73_78\", \"from\": 73, \"to\": 78, \"mention\": \"Obama\", \"polarity\": 6.0}, {\"Input.gid\": \"allsides_6250_2689_12_Barack Obama_73_78\", \"from\": 73, \"to\": 78, \"mention\": \"Obama\", \"polarity\": 6.0}]}\n{\"primary_gid\": \"allsides_5099_2155_56_Dr. King_91_95\", \"sentence_normalized\": \"Ms. Winfrey appeared to inadvertently step into the controversy over a quote on the nearby King memorial when she said of the late civil rights leader, “He was, after all, a drum major for justice.”\", \"targets\": [{\"Input.gid\": \"allsides_5099_2155_56_Dr. King_91_95\", \"from\": 91, \"to\": 95, \"mention\": \"King\", \"polarity\": 6.0}, {\"Input.gid\": \"allsides_5099_2155_56_Ms. Winfrey_0_11\", \"from\": 0, \"to\": 11, \"mention\": \"Ms. Winfrey\", \"polarity\": 2.0, \"further_mentions\": [{\"from\": 110, \"to\": 113, \"mention\": \"she\"}]}]}\n{\"primary_gid\": \"polusa_v1_4420410_-1_9_Vanessa Tyson_123_126\", \"sentence_normalized\": \"FAIRFAX LAST YEAR\\n\\\"We will also produce documentary evidence of Ms. Watson revealing to others the fact that Fairfax raped her,\\\" the statement released by Watson’s lawyers said.\", \"targets\": [{\"Input.gid\": \"polusa_v1_4420410_-1_9_Vanessa Tyson_123_126\", \"from\": 123, \"to\": 126, \"mention\": \"her\", \"polarity\": 4.0}, {\"Input.gid\": \"polusa_v1_4420410_-1_9_Meredith Watson_64_74\", \"from\": 64, \"to\": 74, \"mention\": \"Ms. Watson\", \"polarity\": 4.0, \"further_mentions\": [{\"from\": 155, \"to\": 161, \"mention\": \"Watson\"}]}]}\n{\"primary_gid\": \"allsides_4055_1684_3_Duncan_65_71\", \"sentence_normalized\": \"At a briefing in Atlanta, Frieden said that at some point during Duncan's treatment, \\\"there was a breach in protocol, and that breach in protocol resulted in this infection.\\\"\", \"targets\": [{\"Input.gid\": \"allsides_4055_1684_3_Frieden_26_33\", \"from\": 26, \"to\": 33, \"mention\": \"Frieden\", \"polarity\": 4.0}, {\"Input.gid\": \"allsides_4055_1684_3_Duncan_65_71\", \"from\": 65, \"to\": 71, \"mention\": \"Duncan\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"polusa_v1_3966712_-1_37_Murkowski_68_77\", \"sentence_normalized\": \"On Monday, Senate Majority Leader Mitch McConnell (R-Ky.) met with Murkowski and McCain in his office, one after the other.\", \"targets\": [{\"Input.gid\": \"polusa_v1_3966712_-1_37_Murkowski_68_77\", \"from\": 67, \"to\": 76, \"mention\": \"Murkowski\", \"polarity\": 4.0}, {\"Input.gid\": \"polusa_v1_3966712_-1_37_McCain_82_88\", \"from\": 81, \"to\": 87, \"mention\": \"McCain\", \"polarity\": 4.0}]}\n{\"primary_gid\": \"polusa_v1_4299442_-1_6_Ben Bertram of the Charlestown Police Department_12_19\", \"sentence_normalized\": \"Clark said Bertram had not 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Martin, Jr., Morrison Professor of American History and Citizenship Robin Einhorn, Preston Hotchkis Professor in the History of the United States Kristin Hanson, Associate Professor, English Patricia Baquedano-Lopez, Associate Professor of Education Joseph Wolf, Professor Emeritus, Mathematics You-tien Hsing, Professor, Geography Glynda Hull, Professor, Education Richard B. Norgaard, Professor Emeritus of Energy and Resources Ellen L. Simms, Professor of Integrative Biology Katherine Snyder, Associate Professor, Department of English Kathleen Donegan, Associate Professor, Department of English and Associate Dean of Arts and Humanities Trinh T. Minh-ha, Professor of Rhetoric and of Gender & Women’s Studies Suzanne Guerlac, Professor, Department of French Mel Y. Chen, Associate Professor, Department of Gender and Women’s Studies Margaret W. Conkey, Department of Anthropology Darcy Grimaldo Grigsby, Professor, History of Art Mariane C Ferme, Professor, Department of Anthropology Lyn Hejinian, John F Hotchkis Professor of English Michael Watts, Professor Emeritus, Geography Antonio Montalban, Associate Professor, Mathematics Samera Esmeir, Associate Professor, Rhetoric Louise Fortmann, Professor Emerita, Dept of Environmental Science, Policy and Management Joseph Lavery, Assistant Professor, Dept. of English Lynn Huntsinger, Professor, Dept Environmental Science, Policy, and Management Ramona Naddaff, Associate Professor, Rhetoric Daniel Boyarin, Taubman Professor of Talmudic Culture, Near Eastern Studies and Rhetoric Gillian Hart, Professor Emerita, Geography Charles C. 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controversy over a quote on the nearby King memorial when she said of the late civil rights leader, “He was, after all, a drum major for justice.”\", \"id\": \"allsides_5099_2155_56_Ms. Winfrey_0_11\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 123, \"to\": 126, \"sentence\": \"FAIRFAX LAST YEAR\\n\\\"We will also produce documentary evidence of Ms. Watson revealing to others the fact that Fairfax raped her,\\\" the statement released by Watson’s lawyers said.\", \"id\": \"polusa_v1_4420410_-1_9_Vanessa Tyson_123_126\"}\n{\"mention\": \"Ms. Watson\", \"polarity\": 0, \"from\": 64, \"to\": 74, \"sentence\": \"FAIRFAX LAST YEAR\\n\\\"We will also produce documentary evidence of Ms. Watson revealing to others the fact that Fairfax raped her,\\\" the statement released by Watson’s lawyers said.\", \"id\": \"polusa_v1_4420410_-1_9_Meredith Watson_64_74\"}\n{\"mention\": \"Frieden\", \"polarity\": 0, \"from\": 26, \"to\": 33, \"sentence\": \"At a briefing in Atlanta, Frieden said that at some point during Duncan's treatment, \\\"there was a breach in protocol, and that breach in protocol resulted in this infection.\\\"\", \"id\": \"allsides_4055_1684_3_Frieden_26_33\"}\n{\"mention\": \"Duncan\", \"polarity\": 0, \"from\": 65, \"to\": 71, \"sentence\": \"At a briefing in Atlanta, Frieden said that at some point during Duncan's treatment, \\\"there was a breach in protocol, and that breach in protocol resulted in this infection.\\\"\", \"id\": \"allsides_4055_1684_3_Duncan_65_71\"}\n{\"mention\": \"Murkowski\", \"polarity\": 0, \"from\": 67, \"to\": 76, \"sentence\": \"On Monday, Senate Majority Leader Mitch McConnell (R-Ky.) met with Murkowski and McCain in his office, one after the other.\", \"id\": \"polusa_v1_3966712_-1_37_Murkowski_68_77\"}\n{\"mention\": \"McCain\", \"polarity\": 0, \"from\": 81, \"to\": 87, \"sentence\": \"On Monday, Senate Majority Leader Mitch McConnell (R-Ky.) met with Murkowski and McCain in his office, one after the other.\", \"id\": \"polusa_v1_3966712_-1_37_McCain_82_88\"}\n{\"mention\": \"Clark\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Clark said Bertram had not missed the annual event once in his nine years on the force.\", \"id\": \"polusa_v1_4299442_-1_6_Clark_0_6\"}\n{\"mention\": \"Bertram\", \"polarity\": 1, \"from\": 11, \"to\": 18, \"sentence\": \"Clark said Bertram had not missed the annual event once in his nine years on the force.\", \"id\": \"polusa_v1_4299442_-1_6_Ben Bertram of the Charlestown Police Department_12_19\"}\n{\"mention\": \"Haley\", \"polarity\": 0, \"from\": 44, \"to\": 49, \"sentence\": \"U.S. Ambassador to the United Nations Nikki Haley and Secretary of State Rex Tillerson on Sunday appeared to offer differing views on the future of Syrian President Bashar al-Assad.\", \"id\": \"allsides_1183_473_1_Haley_46_51\"}\n{\"mention\": \"Syrian President Bashar al-Assad\", \"polarity\": 0, \"from\": 148, \"to\": 180, \"sentence\": \"U.S. Ambassador to the United Nations Nikki Haley and Secretary of State Rex Tillerson on Sunday appeared to offer differing views on the future of Syrian President Bashar al-Assad.\", \"id\": \"allsides_1183_473_1_Assad_150_182\"}\n{\"mention\": \"Barr\", \"polarity\": -1, \"from\": 16, \"to\": 20, \"sentence\": \"Mueller report: Barr won't commit to sharing full findings, Democrat says Read more\\n“It was nothing more than a sinister effort to undermine our historic election and to sabotage the will of the American people,” Trump said to loud boos.\", \"id\": \"polusa_v1_38999226_-1_8_Barr_17_21\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Mueller report: Barr won't commit to sharing full findings, Democrat says Read more\\n“It was nothing more than a sinister effort to undermine our historic election and to sabotage the will of the American people,” Trump said to loud boos.\", \"id\": \"polusa_v1_38999226_-1_8_Mueller_1_8\"}\n{\"mention\": \"AMY GOODMAN\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"AMY GOODMAN: But last night— YAZAN AL-SAADI: He’s playing a game.\", \"id\": \"allsides_1197_477_133_AMY GOODMAN_0_11\"}\n{\"mention\": \"YAZAN AL-SAADI\", \"polarity\": 0, \"from\": 29, \"to\": 43, \"sentence\": \"AMY GOODMAN: But last night— YAZAN AL-SAADI: He’s playing a game.\", \"id\": \"allsides_1197_477_133_Yazan al-Saadi_29_43\"}\n{\"mention\": \"Manafort\", \"polarity\": 0, \"from\": 5, \"to\": 13, \"sentence\": \"Paul Manafort, Donald Trump, Jared Kushner, Michael Cohen, and Don McGahn.\", \"id\": \"polusa_v1_131720889_-1_2_Manafort_7_15\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 22, \"to\": 27, \"sentence\": \"Paul Manafort, Donald Trump, Jared Kushner, Michael Cohen, and Don McGahn.\", \"id\": \"polusa_v1_131720889_-1_2_President Donald Trump_24_29\"}\n{\"mention\": \"\\\"Hillary Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 16, \"sentence\": \"\\\"Hillary Clinton has turned over the only records nobody wants to see from her,\\\" said spokesman Jason Miller.\", \"id\": \"allsides_1904_775_2_Hillary Clinton's_0_16\"}\n{\"mention\": \"Miller\", \"polarity\": 0, \"from\": 102, \"to\": 108, \"sentence\": \"\\\"Hillary Clinton has turned over the only records nobody wants to see from her,\\\" said spokesman Jason Miller.\", \"id\": \"allsides_1904_775_2_Miller_102_108\"}\n{\"mention\": \"Rumsfeld\", \"polarity\": -1, \"from\": 92, \"to\": 100, \"sentence\": \"In particular, he objects to how Vice President Dick Cheney and Secretary of Defense Donald Rumsfeld reacted to 9/11.\", \"id\": \"allsides_2767_1129_4_Rumsfeld_92_100\"}\n{\"mention\": \"Dick Cheney\", \"polarity\": -1, \"from\": 48, \"to\": 59, \"sentence\": \"In particular, he objects to how Vice President Dick Cheney and Secretary of Defense Donald Rumsfeld reacted to 9/11.\", \"id\": \"allsides_2767_1129_4_the Dick Cheney_48_59\"}\n{\"mention\": \"Bobbitt\", \"polarity\": 0, \"from\": 52, \"to\": 59, \"sentence\": \"While all of the money was supposedly going to help Bobbitt, prosecutors said the majority of the donated funds was allegedly spent, very quickly, by D'Amico and McClure on personal expenses including purchasing a BMW, expensive handbags, vacations and other personal items.\", \"id\": \"polusa_v1_116016587_-1_14_Bobbitt_53_60\"}\n{\"mention\": \"D'Amico\", \"polarity\": -1, \"from\": 150, \"to\": 157, \"sentence\": \"While all of the money was supposedly going to help Bobbitt, prosecutors said the majority of the donated funds was allegedly spent, very quickly, by D'Amico and McClure on personal expenses including purchasing a BMW, expensive handbags, vacations and other personal items.\", \"id\": \"polusa_v1_116016587_-1_14_D'Amico_151_158\"}\n{\"mention\": \"McClure\", \"polarity\": -1, \"from\": 162, \"to\": 169, \"sentence\": \"While all of the money was supposedly going to help Bobbitt, prosecutors said the majority of the donated funds was allegedly spent, very quickly, by D'Amico and McClure on personal expenses including purchasing a BMW, expensive handbags, vacations and other personal items.\", \"id\": \"polusa_v1_116016587_-1_14_Kate McClure_163_170\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 56, \"to\": 59, \"sentence\": \"President Trump is to blame, he said without mentioning him by name.\", \"id\": \"allsides_425_169_8_This Flake_56_59\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"President Trump is to blame, he said without mentioning him by name.\", \"id\": \"allsides_425_169_8_President Trump_0_15\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He leads self-described liberals by 5 points and beats Hillary by 12 points among Democrats who plan to participate in the caucuses for the first time.\", \"id\": \"allsides_2931_1196_25_Sanders_0_2\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 55, \"to\": 62, \"sentence\": \"He leads self-described liberals by 5 points and beats Hillary by 12 points among Democrats who plan to participate in the caucuses for the first time.\", \"id\": \"allsides_2931_1196_25_Hillary_55_62\"}\n{\"mention\": \"Sanders\", \"polarity\": -1, \"from\": 55, \"to\": 62, \"sentence\": \"Before Sunday, Clinton and her team had suggested that Sanders was withholding his health care proposal to avoid the perception that it would raise taxes on the middle class.\", \"id\": \"allsides_2579_1051_31_Bernie Sanders_55_62\"}\n{\"mention\": \"Sanders\", \"polarity\": -1, \"from\": 55, \"to\": 62, \"sentence\": \"Before Sunday, Clinton and her team had suggested that Sanders was withholding his health care proposal to avoid the perception that it would raise taxes on the middle class.\", \"id\": \"allsides_2579_1051_31_Sanders_55_62\"}\n{\"mention\": \"Hunt\", \"polarity\": -1, \"from\": 0, \"to\": 4, \"sentence\": \"Hunt took Tisquantum and around two dozen other kidnapped Wampanoag to Spain, where he tried to sell them into slavery.\", \"id\": \"allsides_2730_1110_11_Hunt_0_4\"}\n{\"mention\": \"Tisquantum\", \"polarity\": 0, \"from\": 10, \"to\": 20, \"sentence\": \"Hunt took Tisquantum and around two dozen other kidnapped Wampanoag to Spain, where he tried to sell them into slavery.\", \"id\": \"allsides_2730_1110_11_Tisquantum_10_20\"}\n{\"mention\": \"President Biya\", \"polarity\": 0, \"from\": 53, \"to\": 67, \"sentence\": \"\\\"Anglophone crisis no longer bi for wuna level, make President Biya start dis shiddon tok weh deh di singam and notin di happen for ground\\\", de pipo tell de commission.\", \"id\": \"polusa_v1_18255377_-1_4_President Biya_54_68\"}\n{\"mention\": \"de\", \"polarity\": 0, \"from\": 154, \"to\": 156, \"sentence\": \"\\\"Anglophone crisis no longer bi for wuna level, make President Biya start dis shiddon tok weh deh di singam and notin di happen for ground\\\", de pipo tell de commission.\", \"id\": \"polusa_v1_18255377_-1_4_De Peter_155_157\"}\n{\"mention\": \"Kraft\", \"polarity\": 0, \"from\": 265, \"to\": 270, \"sentence\": \"Ladies and gentlemen, your next viral kid reporter is Jeffrey Kraft, age 10, with @KSMKidScoop, seen here talking with @ewarrenpic.twitter.com/Oxb7A7buRW — Daniel Newhauser (@dnewhauser) July 31, 2019\\nHere some Twitter users responses to Williamson's revelation to Kraft about her cat:\\nIf @marwilliamson couldn’t save her cat from dying, how is she going to save America from climate change?\", \"id\": \"polusa_v1_4231813_-1_27_Jeffrey Kraft_266_271\"}\n{\"mention\": \"Williamson\", \"polarity\": 0, \"from\": 238, \"to\": 248, \"sentence\": \"Ladies and gentlemen, your next viral kid reporter is Jeffrey Kraft, age 10, with @KSMKidScoop, seen here talking with @ewarrenpic.twitter.com/Oxb7A7buRW — Daniel Newhauser (@dnewhauser) July 31, 2019\\nHere some Twitter users responses to Williamson's revelation to Kraft about her cat:\\nIf @marwilliamson couldn’t save her cat from dying, how is she going to save America from climate change?\", \"id\": \"polusa_v1_4231813_-1_27_Marianne Williamson_239_249\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 24, \"to\": 29, \"sentence\": \"On Comey’s comment that Trump is “unethical” and “untethered to truth and institutional values,” the group countered that, “Comey has proven himself to be all of these things, and then some.”\", \"id\": \"polusa_v1_4487895_-1_11_President Trump_25_30\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 3, \"to\": 8, \"sentence\": \"On Comey’s comment that Trump is “unethical” and “untethered to truth and institutional values,” the group countered that, “Comey has proven himself to be all of these things, and then some.”\", \"id\": \"polusa_v1_4487895_-1_11_James Comey’s_4_9\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 13, \"to\": 15, \"sentence\": \"In doing so, he adds some diversity to his cabinet (Haley is his first female addition to his senior leadership) and also throws a bone to establishment conservatives by adding one of their favorites.\", \"id\": \"allsides_1616_652_5_President-elect Donald Trump_13_15\"}\n{\"mention\": \"Haley\", \"polarity\": 1, \"from\": 52, \"to\": 57, \"sentence\": \"In doing so, he adds some diversity to his cabinet (Haley is his first female addition to his senior leadership) and also throws a bone to establishment conservatives by adding one of their favorites.\", \"id\": \"allsides_1616_652_5_Nikki Haley_52_57\"}\n{\"mention\": \"Kasich\", \"polarity\": -1, \"from\": 168, \"to\": 174, \"sentence\": \"And on the Republican side, nearly a half-dozen candidates are battling for position behind Donald Trump, with the race's governors – Chris Christie, Jeb Bush and John Kasich -- looking for redemption after missing the leaderboard entirely last week.\", \"id\": \"allsides_2510_1022_4_Kasich_168_174\"}\n{\"mention\": \"Christie\", \"polarity\": -1, \"from\": 140, \"to\": 148, \"sentence\": \"And on the Republican side, nearly a half-dozen candidates are battling for position behind Donald Trump, with the race's governors – Chris Christie, Jeb Bush and John Kasich -- looking for redemption after missing the leaderboard entirely last week.\", \"id\": \"allsides_2510_1022_4_Christie_140_148\"}\n{\"mention\": \"Cruz\", \"polarity\": -1, \"from\": 17, \"to\": 21, \"sentence\": \"The problem with Cruz and Kasich aligning to stop Donald Trump\", \"id\": \"allsides_2279_926_0_Cruz_17_21\"}\n{\"mention\": \"Kasich\", \"polarity\": -1, \"from\": 26, \"to\": 32, \"sentence\": \"The problem with Cruz and Kasich aligning to stop Donald Trump\", \"id\": \"allsides_2279_926_0_Kasich_26_32\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 50, \"to\": 62, \"sentence\": \"The problem with Cruz and Kasich aligning to stop Donald Trump\", \"id\": \"allsides_2279_926_0_Donald Trump_50_62\"}\n{\"mention\": \"Conyers\", \"polarity\": -1, \"from\": 22, \"to\": 29, \"sentence\": \"Apparently Franken or Conyers aren’t as bad as Trump because they’re accused of fewer misdeeds and they’re not as high-ranking as the president.\", \"id\": \"polusa_v1_59548365_-1_18_Conyers_22_29\"}\n{\"mention\": \"Franken\", \"polarity\": -1, \"from\": 11, \"to\": 18, \"sentence\": \"Apparently Franken or Conyers aren’t as bad as Trump because they’re accused of fewer misdeeds and they’re not as high-ranking as the president.\", \"id\": \"polusa_v1_59548365_-1_18_Al Franken_11_18\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 47, \"to\": 52, \"sentence\": \"Apparently Franken or Conyers aren’t as bad as Trump because they’re accused of fewer misdeeds and they’re not as high-ranking as the president.\", \"id\": \"polusa_v1_59548365_-1_18_President Trump_47_52\"}\n{\"mention\": \"ERICK ERICKSON\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"ERICK ERICKSON I would vote for Donald Trump over Hillary Clinton.\", \"id\": \"allsides_2567_1045_97_ERICK ERICKSON_0_14\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 1, \"from\": 32, \"to\": 44, \"sentence\": \"ERICK ERICKSON I would vote for Donald Trump over Hillary Clinton.\", \"id\": \"allsides_2567_1045_97_Donald Trump_32_44\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 145, \"to\": 150, \"sentence\": \"Mr. Snowden’s disclosures set off a national debate about the expansion of the N.S.A.’s powers to spy both at home and abroad, and have left the Obama administration trying frantically to mend relations with allies after his revelations about American eavesdropping on foreign leaders.\", \"id\": \"allsides_4752_1997_7_Obama_145_150\"}\n{\"mention\": \"Mr. Snowden\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Mr. Snowden’s disclosures set off a national debate about the expansion of the N.S.A.’s powers to spy both at home and abroad, and have left the Obama administration trying frantically to mend relations with allies after his revelations about American eavesdropping on foreign leaders.\", \"id\": \"allsides_4752_1997_7_Mr. Snowden_0_11\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Obama can do better at State than Susan Rice.\", \"id\": \"allsides_6027_2584_49_Obama_0_5\"}\n{\"mention\": \"Susan Rice\", \"polarity\": -1, \"from\": 34, \"to\": 44, \"sentence\": \"Obama can do better at State than Susan Rice.\", \"id\": \"allsides_6027_2584_49_Susan Rice_34_44\"}\n{\"mention\": \"girlfriend Reeva Steenkamp\", \"polarity\": 0, \"from\": 185, \"to\": 211, \"sentence\": \"The court on Friday upheld an appeal by prosecutors, who challenged Pistorius' original six-year jail sentence saying it was too lenient for his conviction of murder in the shooting of girlfriend Reeva Steenkamp in 2013.\", \"id\": \"polusa_v1_4428357_-1_3_girlfriend Reeva Steenkamp_186_212\"}\n{\"mention\": \"Pistorius'\", \"polarity\": -1, \"from\": 68, \"to\": 78, \"sentence\": \"The court on Friday upheld an appeal by prosecutors, who challenged Pistorius' original six-year jail sentence saying it was too lenient for his conviction of murder in the shooting of girlfriend Reeva Steenkamp in 2013.\", \"id\": \"polusa_v1_4428357_-1_3_Pistorius'_69_79\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 20, \"to\": 25, \"sentence\": \"JUST WATCHED Things Trump has said about Putin Replay More Videos ...\", \"id\": \"polusa_v1_4666756_-1_33_Donald Trump_21_26\"}\n{\"mention\": \"Putin\", \"polarity\": 0, \"from\": 41, \"to\": 46, \"sentence\": \"JUST WATCHED Things Trump has said about Putin Replay More Videos ...\", \"id\": \"polusa_v1_4666756_-1_33_Putin_42_47\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 22, \"to\": 25, \"sentence\": \"KEVIN CIRILLI: So has she ruled it out?\", \"id\": \"polusa_v1_4306959_-1_16_Hillary Clinton_22_25\"}\n{\"mention\": \"KEVIN CIRILLI\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"KEVIN CIRILLI: So has she ruled it out?\", \"id\": \"polusa_v1_4306959_-1_16_Bloomberg News’s Kevin Cirilli_0_13\"}\n{\"mention\": \"Kramer\", \"polarity\": 0, \"from\": 94, \"to\": 100, \"sentence\": \"Simpson made clear that the request for more information was initiated by McCain’s associate, Kramer.\", \"id\": \"polusa_v1_4349674_-1_12_Kramer_95_101\"}\n{\"mention\": \"Simpson\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Simpson made clear that the request for more information was initiated by McCain’s associate, Kramer.\", \"id\": \"polusa_v1_4349674_-1_12_Fusion GPS co-founder Simpson_1_8\"}\n{\"mention\": \"a clearly emotional South African President Jacob Zuma\", \"polarity\": 1, \"from\": 26, \"to\": 80, \"sentence\": \"The news was announced by a clearly emotional South African President Jacob Zuma live on television, who said Mandela had \\\"departed\\\" and was at peace.\", \"id\": \"allsides_4787_2011_3_a clearly emotional South African President Jacob Zuma_26_80\"}\n{\"mention\": \"Mandela\", \"polarity\": 1, \"from\": 110, \"to\": 117, \"sentence\": \"The news was announced by a clearly emotional South African President Jacob Zuma live on television, who said Mandela had \\\"departed\\\" and was at peace.\", \"id\": \"allsides_4787_2011_3_Mandela_110_117\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 18, \"to\": 21, \"sentence\": \"Shalala said that she was willing to work with her Republican colleagues as a freshman.\", \"id\": \"polusa_v1_113909381_-1_18_Ileana Ros-Lehtinen in Florida_19_22\"}\n{\"mention\": \"Shalala\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Shalala said that she was willing to work with her Republican colleagues as a freshman.\", \"id\": \"polusa_v1_113909381_-1_18_Donna Shalala_1_8\"}\n{\"mention\": \"Hollande\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Hollande hit out at Trump as he arrived at the informal summit on the future of the EU in Malta.\", \"id\": \"polusa_v1_4918607_-1_6_French president Francois Hollande_1_9\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 20, \"to\": 25, \"sentence\": \"Hollande hit out at Trump as he arrived at the informal summit on the future of the EU in Malta.\", \"id\": \"polusa_v1_4918607_-1_6_Donald Trump_21_26\"}\n{\"mention\": \"Angela Merkel\", \"polarity\": -1, \"from\": 43, \"to\": 56, \"sentence\": \"\\\"I think he's a bit more of a fighter than Angela Merkel is presenting herself at the moment,\\\" Zimmerman says.\", \"id\": \"polusa_v1_52965749_-1_18_Merkel_44_57\"}\n{\"mention\": \"Zimmerman\", \"polarity\": 0, \"from\": 95, \"to\": 104, \"sentence\": \"\\\"I think he's a bit more of a fighter than Angela Merkel is presenting herself at the moment,\\\" Zimmerman says.\", \"id\": \"polusa_v1_52965749_-1_18_Zimmerman_96_105\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 9, \"to\": 11, \"sentence\": \"\\\"I think he's a bit more of a fighter than Angela Merkel is presenting herself at the moment,\\\" Zimmerman says.\", \"id\": \"polusa_v1_52965749_-1_18_Martin Schulz_10_12\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": 1, \"from\": 21, \"to\": 30, \"sentence\": \"The White House said Mr. Obama and Mrs. Merkel agreed that sanctions “should be clearly linked to Russia’s full implementation” of a Ukrainian peace accord and Russian respect for its neighbor’s sovereignty.\", \"id\": \"allsides_3155_1294_3_Mr. Obama_21_30\"}\n{\"mention\": \"Mrs. Merkel\", \"polarity\": 1, \"from\": 35, \"to\": 46, \"sentence\": \"The White House said Mr. Obama and Mrs. Merkel agreed that sanctions “should be clearly linked to Russia’s full implementation” of a Ukrainian peace accord and Russian respect for its neighbor’s sovereignty.\", \"id\": \"allsides_3155_1294_3_German Chancellor Angela Merkel_35_46\"}\n{\"mention\": \"Chaffetz\", \"polarity\": 0, \"from\": 204, \"to\": 212, \"sentence\": \"\\\"If left unaddressed, Pagliano's conduct in ignoring a lawful congressional subpoena could gravely impair Congress's ability to exercise its core constitutional authorities of oversight and legislation,\\\" Chaffetz wrote.\", \"id\": \"polusa_v1_4987298_-1_7_Chaffetz_205_213\"}\n{\"mention\": \"Pagliano\", \"polarity\": -1, \"from\": 22, \"to\": 30, \"sentence\": \"\\\"If left unaddressed, Pagliano's conduct in ignoring a lawful congressional subpoena could gravely impair Congress's ability to exercise its core constitutional authorities of oversight and legislation,\\\" Chaffetz wrote.\", \"id\": \"polusa_v1_4987298_-1_7_former Clinton IT aide Bryan Pagliano_23_31\"}\n{\"mention\": \"Mueller\", \"polarity\": -1, \"from\": 56, \"to\": 63, \"sentence\": \"It is now harder for Trump to claim that Rosenstein and Mueller are out of control.\", \"id\": \"polusa_v1_79069368_-1_20_Special Counsel Robert Mueller_56_63\"}\n{\"mention\": \"Rosenstein\", \"polarity\": -1, \"from\": 41, \"to\": 51, \"sentence\": \"It is now harder for Trump to claim that Rosenstein and Mueller are out of control.\", \"id\": \"polusa_v1_79069368_-1_20_Deputy Attorney General Rod Rosenstein_41_51\"}\n{\"mention\": \"Cruz\", \"polarity\": -1, \"from\": 61, \"to\": 65, \"sentence\": \"I don’t think it was his strongest debate and neither he nor Cruz looked good in their fight over immigration.\", \"id\": \"allsides_2547_1037_20_Cruz_61_65\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 54, \"to\": 56, \"sentence\": \"I don’t think it was his strongest debate and neither he nor Cruz looked good in their fight over immigration.\", \"id\": \"allsides_2547_1037_20_Rubio_54_56\"}\n{\"mention\": \"Assad\", \"polarity\": -1, \"from\": 300, \"to\": 305, \"sentence\": \"( PHOTOS: John McCain’s life and career) The anti-government rebels have asked the United States to provide the opposition with heavier weaponry, a no-fly zone and airstrikes on both Syrian dictator Bashar Assad’s forces and those of the Lebanese terrorist group Hezbollah, which has pledged to back Assad in the war.\", \"id\": \"allsides_5352_2276_6_Assad_300_305\"}\n{\"mention\": \"John McCain\", \"polarity\": 0, \"from\": 10, \"to\": 21, \"sentence\": \"( PHOTOS: John McCain’s life and career) The anti-government rebels have asked the United States to provide the opposition with heavier weaponry, a no-fly zone and airstrikes on both Syrian dictator Bashar Assad’s forces and those of the Lebanese terrorist group Hezbollah, which has pledged to back Assad in the war.\", \"id\": \"allsides_5352_2276_6_McCain_10_21\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 47, \"to\": 52, \"sentence\": \"Trump added that he was impressed with the way Pence has run Indiana, and that picking him would lock down the state’s electoral votes.\", \"id\": \"allsides_1999_814_29_Mike Pence_48_53\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Trump added that he was impressed with the way Pence has run Indiana, and that picking him would lock down the state’s electoral votes.\", \"id\": \"allsides_1999_814_29_Donald Trump_1_6\"}\n{\"mention\": \"White House Chief of Staff Denis McDonough\", \"polarity\": 0, 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\"to\": 134, \"sentence\": \"In a Friday morning appearance on CNN's \\\"New Day,\\\" Deutch told anchor John Berman that he found the recently released photo of Franken appearing to grab the breasts of a sleeping woman \\\"absolutely revolting.\\\"\", \"id\": \"polusa_v1_4685994_-1_9_Al Franken_128_135\"}\n{\"mention\": \"Warren\", \"polarity\": 0, \"from\": 20, \"to\": 26, \"sentence\": \"The purported Biden-Warren meeting at the Naval Observatory, the vice president’s residence, was reported first by CNN.\", \"id\": \"allsides_2946_1204_7_Warren_20_26\"}\n{\"mention\": \"Biden\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"The purported Biden-Warren meeting at the Naval Observatory, the vice president’s residence, was reported first by CNN.\", \"id\": \"allsides_2946_1204_7_Biden_14_19\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": -1, \"from\": 13, \"to\": 30, \"sentence\": \"Sanders says Wasserman Schultz limited the number of primary debates to protect Clinton.\", \"id\": \"allsides_2136_870_15_Wasserman Schultz_13_30\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 80, \"to\": 87, \"sentence\": \"Sanders says Wasserman Schultz limited the number of primary debates to protect Clinton.\", \"id\": \"allsides_2136_870_15_Democratic presidential front-runner Hillary Clinton_80_87\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 188, \"to\": 203, \"sentence\": \"Kushner used the private account through his first nine months in government service, even as the president continued to criticize his opponent in the 2016 presidential election, Democrat Hillary Clinton, for her use of a private email account for government business.\", \"id\": \"polusa_v1_59600650_-1_2_Hillary Clinton_189_204\"}\n{\"mention\": \"Kushner\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Kushner used the private account through his first nine months in government service, even as the president continued to criticize his opponent in the 2016 presidential election, Democrat Hillary Clinton, for her use of a private email account for government business.\", \"id\": \"polusa_v1_59600650_-1_2_senior adviser Jared Kushner_0_8\"}\n{\"mention\": \"President Barack Obama\", \"polarity\": -1, \"from\": 77, \"to\": 99, \"sentence\": \"Ryan also told Fox that although he’s only 42, he has “more experience” than President Barack Obama did when he began his term.\", \"id\": \"allsides_6324_2718_10_President Barack Obama_77_99\"}\n{\"mention\": \"Ryan\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Ryan also told Fox that although he’s only 42, he has “more experience” than President Barack Obama did when he began his term.\", \"id\": \"allsides_6324_2718_10_Ryan_0_4\"}\n{\"mention\": \"Petersen\", \"polarity\": -1, \"from\": 137, \"to\": 145, \"sentence\": \"After admitting that he had no experience trying a jury trial, civil trial, criminal trial, bench trial or state or federal court trial, Petersen revealed a stunning display of ignorance over fundamental legal facts.\", \"id\": \"allsides_194_79_4_Petersen_137_146\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 21, \"to\": 23, \"sentence\": \"After admitting that he had no experience trying a jury trial, civil trial, criminal trial, bench trial or state or federal court trial, Petersen revealed a stunning display of ignorance over fundamental legal facts.\", \"id\": \"allsides_194_79_4_John Kennedy_21_23\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 120, \"to\": 127, \"sentence\": \"Kendall said the State Department is “uniquely positioned” to respond to requests for additional documents, a sign from Clinton’s camp that they believe she has fully responded to any standing legal requests.\", \"id\": \"allsides_3417_1411_15_Clinton_120_127\"}\n{\"mention\": \"Kendall\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Kendall said the State Department is “uniquely positioned” to respond to requests for additional documents, a sign from Clinton’s camp that they believe she has fully responded to any standing legal requests.\", \"id\": \"allsides_3417_1411_15_Kendall_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 117, \"to\": 124, \"sentence\": \"New texts between FBI lovers Strzok and Page were 'disappointing' and cast a shadow over the integrity of the entire Clinton email probe\\nAnti-Trump text messages between special counsel Lisa Page and FBI Deputy Assistant Director Peter Strzok damaged the integrity of the entire Clinton email probe, Horowitz writes.\", \"id\": \"polusa_v1_4525031_-1_6_Clinton_117_124\"}\n{\"mention\": \"Strzok\", \"polarity\": -1, \"from\": 29, \"to\": 35, \"sentence\": \"New texts between FBI lovers Strzok and Page were 'disappointing' and cast a shadow over the integrity of the entire Clinton email probe\\nAnti-Trump text messages between special counsel Lisa Page and FBI Deputy Assistant Director Peter Strzok damaged the integrity of the entire Clinton email probe, Horowitz writes.\", \"id\": \"polusa_v1_4525031_-1_6_Strzok_29_35\"}\n{\"mention\": \"Wilson\", \"polarity\": 0, \"from\": 124, \"to\": 130, \"sentence\": \"Stephanie Karr, Ferguson city attorney, told the Associated Press that city officials planned to make a statement regarding Wilson's resignation.\", \"id\": \"allsides_3871_1604_2_Wilson_124_130\"}\n{\"mention\": \"Ferguson\", \"polarity\": 0, \"from\": 16, \"to\": 24, \"sentence\": \"Stephanie Karr, Ferguson city attorney, told the Associated Press that city officials planned to make a statement regarding Wilson's resignation.\", \"id\": \"allsides_3871_1604_2_Ferguson_16_24\"}\n{\"mention\": \"Jamie Dimon\", \"polarity\": 1, \"from\": 11, \"to\": 22, \"sentence\": \"Gary Cohn: Jamie Dimon would be 'phenomenal' president\", \"id\": \"polusa_v1_116911747_-1_0_Jamie Dimon_11_22\"}\n{\"mention\": \"Cohn\", \"polarity\": 0, \"from\": 5, \"to\": 9, \"sentence\": \"Gary Cohn: Jamie Dimon would be 'phenomenal' president\", \"id\": \"polusa_v1_116911747_-1_0_Cohn_5_9\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 85, \"to\": 94, \"sentence\": \"He worked for the campaign for 144 days — not 49 days or three and a half months, as Mr. Trump alternately has claimed.\", \"id\": \"polusa_v1_3998403_-1_5_John Podesta_85_94\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He worked for the campaign for 144 days — not 49 days or three and a half months, as Mr. Trump alternately has claimed.\", \"id\": \"polusa_v1_3998403_-1_5_“Manafort_0_2\"}\n{\"mention\": \"Adam Zebley\", \"polarity\": 0, \"from\": 31, \"to\": 42, \"sentence\": \"Mueller makes request for aide Adam Zebley to appear during testimony\", \"id\": \"polusa_v1_55367593_-1_0_Adam Zebley_31_42\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Mueller makes request for aide Adam Zebley to appear during testimony\", \"id\": \"polusa_v1_55367593_-1_0_Mueller_0_7\"}\n{\"mention\": \"Blitzer\", \"polarity\": 0, \"from\": 7, \"to\": 14, \"sentence\": \"Again, Blitzer asked Wilkinson if she was calling for an investigation, which she had just seemed to demand.\", \"id\": \"polusa_v1_131731478_-1_18_Blitzer_8_15\"}\n{\"mention\": \"Wilkinson\", \"polarity\": 0, \"from\": 21, \"to\": 30, \"sentence\": \"Again, Blitzer asked Wilkinson if she was calling for an investigation, which she had just seemed to demand.\", \"id\": \"polusa_v1_131731478_-1_18_Brett Kavanaugh’s attorney Beth Wilkinson_22_31\"}\n{\"mention\": \"Duckworth\", \"polarity\": 0, \"from\": 86, \"to\": 95, \"sentence\": \"He was disappointed\\nPerez enlisted in the military before 9/11 and served until 2004, Duckworth said this week in a letter to the top official at the Chicago district of U.S. Citizenship and Immigration Services.\", \"id\": \"polusa_v1_59482033_-1_8_Tammy Duckworth_86_95\"}\n{\"mention\": \"Perez\", \"polarity\": -1, \"from\": 20, \"to\": 25, \"sentence\": \"He was disappointed\\nPerez enlisted in the military before 9/11 and served until 2004, Duckworth said this week in a letter to the top official at the Chicago district of U.S. Citizenship and Immigration Services.\", \"id\": \"polusa_v1_59482033_-1_8_Perez_20_25\"}\n{\"mention\": \"Kemp\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Kemp is Abrams' Republican opponent in the gubernatorial race.\", \"id\": \"polusa_v1_4203453_-1_9_Brian Kemp's_0_4\"}\n{\"mention\": \"Abrams'\", \"polarity\": 0, \"from\": 8, \"to\": 15, \"sentence\": \"Kemp is Abrams' Republican opponent in the gubernatorial race.\", \"id\": \"polusa_v1_4203453_-1_9_Stacey Abrams_8_15\"}\n{\"mention\": \"Kim Jong Un\", \"polarity\": -1, \"from\": 4, \"to\": 15, \"sentence\": \"How Kim Jong Un and Donald Trump will act remains incredibly hard to predict.\", \"id\": \"polusa_v1_4669738_-1_32_Kim Jong Un_5_16\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 20, \"to\": 32, \"sentence\": \"How Kim Jong Un and Donald Trump will act remains incredibly hard to predict.\", \"id\": \"polusa_v1_4669738_-1_32_US President Donald Trump_21_33\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 7, \"to\": 14, \"sentence\": \"Gibbs: Clinton's use of private emails 'highly unusual'\", \"id\": \"allsides_3521_1454_0_Clinton_7_14\"}\n{\"mention\": \"Gibbs\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Gibbs: Clinton's use of private emails 'highly unusual'\", \"id\": \"allsides_3521_1454_0_Gibbs_0_5\"}\n{\"mention\": \"herself\", \"polarity\": 1, \"from\": 56, \"to\": 63, \"sentence\": \"In her time as U.S. Attorney, Lynch has made a name for herself in a number of high-profile convictions, including a thwarted Al Qaeda-sanctioned plot to attack the New York subway system, and pursuing the head of a Mexican drug cartel for 12 murders.\", \"id\": \"allsides_3940_1637_25_Obama_56_63\"}\n{\"mention\": \"Lynch\", \"polarity\": 1, \"from\": 30, \"to\": 35, \"sentence\": \"In her time as U.S. Attorney, Lynch has made a name for herself in a number of high-profile convictions, including a thwarted Al Qaeda-sanctioned plot to attack the New York subway system, and pursuing the head of a Mexican drug cartel for 12 murders.\", \"id\": \"allsides_3940_1637_25_US Attorney Loretta Lynch_30_35\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 37, \"to\": 42, \"sentence\": \"So, if Mr. Trump is comfortable with Pence, sounds like a good deal.”\", \"id\": \"allsides_1999_814_27_Mike Pence_37_42\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 11, \"to\": 16, \"sentence\": \"So, if Mr. Trump is comfortable with Pence, sounds like a good deal.”\", \"id\": \"allsides_1999_814_27_Donald Trump_11_16\"}\n{\"mention\": \"George H.W. Bush\", \"polarity\": 1, \"from\": 29, \"to\": 45, \"sentence\": \"“To Presidents Jimmy Carter, George H.W. Bush, Bill Clinton, George W. Bush and Barack Obama, Melania and I want to express our deep gratitude for your tremendous assistance,” Trump said in the message.\", \"id\": \"allsides_436_174_5_George H.W. Bush_29_45\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 176, \"to\": 181, \"sentence\": \"“To Presidents Jimmy Carter, George H.W. Bush, Bill Clinton, George W. Bush and Barack Obama, Melania and I want to express our deep gratitude for your tremendous assistance,” Trump said in the message.\", \"id\": \"allsides_436_174_5_current President Donald Trump — sort of_176_181\"}\n{\"mention\": \"President Obama\", \"polarity\": 1, \"from\": 74, \"to\": 89, \"sentence\": \"Kamala Harris, D-Calif., on Thursday said she had \\\"nothing but praise for President Obama.\\\"\", \"id\": \"polusa_v1_4142193_-1_21_former President Barack Obama_74_89\"}\n{\"mention\": \"Kamala Harris, D-Calif\", \"polarity\": 1, \"from\": 0, \"to\": 22, \"sentence\": \"Kamala Harris, D-Calif., on Thursday said she had \\\"nothing but praise for President Obama.\\\"\", \"id\": \"polusa_v1_4142193_-1_21_Kamala Harris, D-Calif_0_22\"}\n{\"mention\": \"Hanson\", \"polarity\": -1, \"from\": 113, \"to\": 119, \"sentence\": \"Attorney-General George Brandis drew applause when he said his government would not ban the burqa, and chastised Hanson for what he described as a \\\"stunt\\\" that offended Australia's Muslim minority.\", \"id\": \"polusa_v1_4655869_-1_4_Hanson_114_120\"}\n{\"mention\": \"Attorney-General George Brandis\", \"polarity\": 1, \"from\": 0, \"to\": 31, \"sentence\": \"Attorney-General George Brandis drew applause when he said his government would not ban the burqa, and chastised Hanson for what he described as a \\\"stunt\\\" that offended Australia's Muslim minority.\", \"id\": \"polusa_v1_4655869_-1_4_Attorney-General George Brandis_1_32\"}\n{\"mention\": \"Ward\", \"polarity\": -1, \"from\": 39, \"to\": 43, \"sentence\": \"On Saturday, hours before McCain died, Ward speculated on Facebook that the McCain family announced the senator was ending medical treatment on Friday to distract from her final push in the primary.\", \"id\": \"polusa_v1_113890069_-1_55_Ward_39_43\"}\n{\"mention\": \"McCain\", \"polarity\": 0, \"from\": 26, \"to\": 32, \"sentence\": \"On Saturday, hours before McCain died, Ward speculated on Facebook that the McCain family announced the senator was ending medical treatment on Friday to distract from her final push in the primary.\", \"id\": \"polusa_v1_113890069_-1_55_John McCain_26_32\"}\n{\"mention\": \"Bannon\", \"polarity\": 0, \"from\": 109, \"to\": 115, \"sentence\": \"Mike Conaway, the Republican running the committee's Russia probe, told reporters Monday evening he expected Bannon to comply with the subpoena demands of the committee and was unaware of any deal to limit the answers he would provide to the panel.\", \"id\": \"polusa_v1_4814544_-1_5_Bannon_109_115\"}\n{\"mention\": \"Mike Conaway, the Republican running the committee's Russia probe\", \"polarity\": 0, \"from\": 0, \"to\": 65, \"sentence\": \"Mike Conaway, the Republican running the committee's Russia probe, told reporters Monday evening he expected Bannon to comply with the subpoena demands of the committee and was unaware of any deal to limit the answers he would provide to the panel.\", \"id\": \"polusa_v1_4814544_-1_5_Mike Conaway, the Republican running the committee's Russia probe_0_65\"}\n{\"mention\": \"Waters\", \"polarity\": 1, \"from\": 54, \"to\": 60, \"sentence\": \"In an interview with Chris Hayes on MSNBC's \\\"All In,\\\" Waters had some harsh words for members of Trump's Cabinet and his associates with alleged ties to Russia.\", \"id\": \"polusa_v1_131715984_-1_5_Maxine Waters on Trump's Cabinet_55_61\"}\n{\"mention\": \"Chris Hayes\", \"polarity\": 0, \"from\": 21, \"to\": 32, \"sentence\": \"In an interview with Chris Hayes on MSNBC's \\\"All In,\\\" Waters had some harsh words for members of Trump's Cabinet and his associates with alleged ties to Russia.\", \"id\": \"polusa_v1_131715984_-1_5_Chris Hayes_22_33\"}\n{\"mention\": \"Zakaria\", \"polarity\": 0, \"from\": 19, \"to\": 26, \"sentence\": \"Speaking Sunday on Zakaria’s “GPS” show on CNN, Dmitry Peskov said ambassador Sergey Kislyak met with “people working in think tanks advising Hillary or advising people working for Hillary.”\", \"id\": \"polusa_v1_4294239_-1_3_Fareed Zakaria_20_27\"}\n{\"mention\": \"ambassador Sergey Kislyak\", \"polarity\": 0, \"from\": 67, \"to\": 92, \"sentence\": \"Speaking Sunday on Zakaria’s “GPS” show on CNN, Dmitry Peskov said ambassador Sergey Kislyak met with “people working in think tanks advising Hillary or advising people working for Hillary.”\", \"id\": \"polusa_v1_4294239_-1_3_ambassador Sergey Kislyak_68_93\"}\n{\"mention\": \"Dmitry Peskov\", \"polarity\": 0, \"from\": 48, \"to\": 61, \"sentence\": \"Speaking Sunday on Zakaria’s “GPS” show on CNN, Dmitry Peskov said ambassador Sergey Kislyak met with “people working in think tanks advising Hillary or advising people working for Hillary.”\", \"id\": \"polusa_v1_4294239_-1_3_Dmitry Peskov_49_62\"}\n{\"mention\": \"TRUMP\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"TRUMP FIRES BROADSIDE AT MICHAEL COHEN, DENIES CLAIM ON MEETING WITH RUSSIAN LAWYER\\nOver the weekend, Davis clarified his claims.\", \"id\": \"polusa_v1_4503577_-1_18_President Trump_1_6\"}\n{\"mention\": \"MICHAEL COHEN\", \"polarity\": -1, \"from\": 25, \"to\": 38, \"sentence\": \"TRUMP FIRES BROADSIDE AT MICHAEL COHEN, DENIES CLAIM ON MEETING WITH RUSSIAN LAWYER\\nOver the weekend, Davis clarified his claims.\", \"id\": \"polusa_v1_4503577_-1_18_“Mr. Cohen_26_39\"}\n{\"mention\": \"Ryan\", \"polarity\": 0, \"from\": 128, \"to\": 132, \"sentence\": \"John Locher/AP\\nChief US District Judge Gloria Navarro declared a mistrial Wednesday in the case against Cliven Bundy; his sons, Ryan and Ammon Bundy; and self-styled Montana militia leader Ryan Payne.\", \"id\": \"polusa_v1_4766164_-1_27_Ryan_129_133\"}\n{\"mention\": \"Cliven Bundy\", \"polarity\": -1, \"from\": 104, \"to\": 116, \"sentence\": \"John Locher/AP\\nChief US District Judge Gloria Navarro declared a mistrial Wednesday in the case against Cliven Bundy; his sons, Ryan and Ammon Bundy; and self-styled Montana militia leader Ryan Payne.\", \"id\": \"polusa_v1_4766164_-1_27_Cliven Bundy_105_117\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 52, \"to\": 59, \"sentence\": \"Todd does not want his audience to know that it was Hillary who colluded with the Russians and a foreigner to meddle in the campaign, so he fires off a whopper about a Republican donor funding Hillary’s Hoax Dossier.\", \"id\": \"polusa_v1_4320320_-1_62_Hillary_53_60\"}\n{\"mention\": \"Todd\", \"polarity\": -1, \"from\": 0, \"to\": 4, \"sentence\": \"Todd does not want his audience to know that it was Hillary who colluded with the Russians and a foreigner to meddle in the campaign, so he fires off a whopper about a Republican donor funding Hillary’s Hoax Dossier.\", \"id\": \"polusa_v1_4320320_-1_62_Todd_1_5\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 69, \"to\": 76, \"sentence\": \"Head of the academy, Bishop Marcelo Sanchez Sorondo, said he invited Sanders to speak because he was the only American presidential candidate who has expressed serious interest in the teachings of Pope Francis, RNS reported.\", \"id\": \"allsides_2306_938_8_Democratic presidential candidate Bernie Sanders_69_76\"}\n{\"mention\": \"Pope Francis\", \"polarity\": 1, \"from\": 197, \"to\": 209, \"sentence\": \"Head of the academy, Bishop Marcelo Sanchez Sorondo, said he invited Sanders to speak because he was the only American presidential candidate who has expressed serious interest in the teachings of Pope Francis, RNS reported.\", \"id\": \"allsides_2306_938_8_Pope Francis_197_209\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 92, \"to\": 104, \"sentence\": \"Cruz shot back: \\\"It's interesting that you added women and children because your candidate, Donald Trump, came out and said he would order our military to kill the women and children, the wives and children, of terrorists, which is a war crime.\\\"\", \"id\": \"allsides_2240_911_26_Donald Trump_92_104\"}\n{\"mention\": \"Cruz\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Cruz shot back: \\\"It's interesting that you added women and children because your candidate, Donald Trump, came out and said he would order our military to kill the women and children, the wives and children, of terrorists, which is a war crime.\\\"\", \"id\": \"allsides_2240_911_26_Cruz_0_4\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump is expected to meet with President Xi Jinping of China at the Group of 20 summit meeting in Argentina in November.\", \"id\": \"polusa_v1_3997105_-1_10_Mr. Trump_0_9\"}\n{\"mention\": \"President Xi Jinping of China\", \"polarity\": 0, \"from\": 35, \"to\": 64, \"sentence\": \"Mr. Trump is expected to meet with President Xi Jinping of China at the Group of 20 summit meeting in Argentina in November.\", \"id\": \"polusa_v1_3997105_-1_10_President Xi Jinping of China_35_64\"}\n{\"mention\": \"CORNISH\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"CORNISH: That's Jason Furman.\", \"id\": \"polusa_v1_52924586_-1_57_NPR's Audie Cornish_0_8\"}\n{\"mention\": \"Jason Furman\", \"polarity\": 0, \"from\": 16, \"to\": 28, \"sentence\": \"CORNISH: That's Jason Furman.\", \"id\": \"polusa_v1_52924586_-1_57_Jason Furman_17_29\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 23, \"to\": 25, \"sentence\": \"His words echoed those he made in a video statement Saturday, in which Netanyahu said the move marked “a great moment for the State of Israel.”\", \"id\": \"polusa_v1_4338440_-1_9_President Donald Trump_24_26\"}\n{\"mention\": \"Netanyahu\", \"polarity\": 1, \"from\": 71, \"to\": 80, \"sentence\": \"His words echoed those he made in a video statement Saturday, in which Netanyahu said the move marked “a great moment for the State of Israel.”\", \"id\": \"polusa_v1_4338440_-1_9_Netanyahu_72_81\"}\n{\"mention\": \"President Trump\", \"polarity\": 1, \"from\": 39, \"to\": 54, \"sentence\": \"Developing now, Tuesday, Jan. 23, 2018\\nPresident Trump praises 'big win' for Republicans as he signs a bill ending the government shutdown while Democrats blast Senate Minority Leader Chuck Schumer\\nBREAKING NEWS: 8.2 magnitude earthquake strikes off Alaska, prompting tsunami warning\\nAttorney General Jeff Sessions vows to find out why five months of text messages between two FBI officials under fire for their anti-Trump views are missing\\nHouse Republicans are pushing for a memo said to contain damning evidence of U.S. government surveillance abuses to be made public soon\\nExclusive: Vice President Mike Pence tells Fox News peace is 'more possible' after he announced the Trump administration would fast-track the move of the U.S. embassy to Jerusalem\\nSupreme Court Justice Ruth Bader Ginsburg stuns the Sundance Film Festival with her own #MeToo story\\nTHE LEAD STORY - 'BIG WIN' FOR REPUBLICANS AS DEMS 'CAVE' AND INFIGHT ON SHUTDOWN: President Trump struck an optimistic tone on Twitter after he signed a bill to reopen the government late Monday night after a three-day federal government shutdown led to Senate Democrats backing off their opposition ...\", \"id\": \"polusa_v1_4579589_-1_5_President Trump_40_55\"}\n{\"mention\": \"Ginsburg\", \"polarity\": 1, \"from\": 790, \"to\": 798, \"sentence\": \"Developing now, Tuesday, Jan. 23, 2018\\nPresident Trump praises 'big win' for Republicans as he signs a bill ending the government shutdown while Democrats blast Senate Minority Leader Chuck Schumer\\nBREAKING NEWS: 8.2 magnitude earthquake strikes off Alaska, prompting tsunami warning\\nAttorney General Jeff Sessions vows to find out why five months of text messages between two FBI officials under fire for their anti-Trump views are missing\\nHouse Republicans are pushing for a memo said to contain damning evidence of U.S. government surveillance abuses to be made public soon\\nExclusive: Vice President Mike Pence tells Fox News peace is 'more possible' after he announced the Trump administration would fast-track the move of the U.S. embassy to Jerusalem\\nSupreme Court Justice Ruth Bader Ginsburg stuns the Sundance Film Festival with her own #MeToo story\\nTHE LEAD STORY - 'BIG WIN' FOR REPUBLICANS AS DEMS 'CAVE' AND INFIGHT ON SHUTDOWN: President Trump struck an optimistic tone on Twitter after he signed a bill to reopen the government late Monday night after a three-day federal government shutdown led to Senate Democrats backing off their opposition ...\", \"id\": \"polusa_v1_4579589_-1_5_U.S. Supreme Court Justice Ruth Bader Ginsburg_791_799\"}\n{\"mention\": \"Steenkamp\", \"polarity\": 0, \"from\": 97, \"to\": 106, \"sentence\": \"Masipa said prosecutors had not proven beyond a reasonable doubt that Pistorius intended to kill Steenkamp.\", \"id\": \"allsides_4156_1731_4_girlfriend Reeva Steenkamp_97_106\"}\n{\"mention\": \"Masipa\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Masipa said prosecutors had not proven beyond a reasonable doubt that Pistorius intended to kill Steenkamp.\", \"id\": \"allsides_4156_1731_4_Judge Thokozile Masipa_0_6\"}\n{\"mention\": \"Powell\", \"polarity\": 0, \"from\": 39, \"to\": 45, \"sentence\": \"However, in nominating the 64-year-old Powell, Trump is breaking with decades of presidential tradition by not retaining the current Fed chair: Barack Obama kept Ben Bernanke, Bill Clinton stayed the course with Alan Greenspan, and Ronald Reagan renominated Paul Volcker.\", \"id\": \"polusa_v1_55289823_-1_13_Powell_40_46\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 47, \"to\": 52, \"sentence\": \"However, in nominating the 64-year-old Powell, Trump is breaking with decades of presidential tradition by not retaining the current Fed chair: Barack Obama kept Ben Bernanke, Bill Clinton stayed the course with Alan Greenspan, and Ronald Reagan renominated Paul Volcker.\", \"id\": \"polusa_v1_55289823_-1_13_Trump_48_53\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 9, \"to\": 14, \"sentence\": \"Bush and Trump on that bus are, in so many ways, the apotheosis of what so many of Hillary Clinton’s supporters are ready to overturn: the musty sleaziness that went out of style in the 1970s; the old bosses who want their secretaries pretty; the cigar-chomping power brokers who think sexual harassment is the woman’s problem; the drooling dimwits who have gotten further than they should have on connections and male privilege.\", \"id\": \"allsides_1742_709_36_Donald Trump:_9_14\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 0, \"to\": 4, \"sentence\": \"Bush and Trump on that bus are, in so many ways, the apotheosis of what so many of Hillary Clinton’s supporters are ready to overturn: the musty sleaziness that went out of style in the 1970s; the old bosses who want their secretaries pretty; the cigar-chomping power brokers who think sexual harassment is the woman’s problem; the drooling dimwits who have gotten further than they should have on connections and 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Mr. Thune also gave more detail about its operations.\", \"id\": \"allsides_2160_879_28_Mr. Thune_31_40\"}\n{\"mention\": \"The company\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"The company’s letter Monday to Mr. Thune also gave more detail about its operations.\", \"id\": \"allsides_2160_879_28_Facebook CEO Mark Zuckerberg_0_11\"}\n{\"mention\": \"Manafort\", \"polarity\": -1, \"from\": 63, \"to\": 71, \"sentence\": \"\\\"All of these charges boil down to one simple issue: that Paul Manafort lied,\\\" Asonye said.\", \"id\": \"polusa_v1_4634013_-1_15_Manafort_64_72\"}\n{\"mention\": \"Asonye\", \"polarity\": 0, \"from\": 79, \"to\": 85, \"sentence\": \"\\\"All of these charges boil down to one simple issue: that Paul Manafort lied,\\\" Asonye said.\", \"id\": \"polusa_v1_4634013_-1_15_Assistant U.S. Attorney Uzo Asonye_80_86\"}\n{\"mention\": \"Mueller\", \"polarity\": -1, \"from\": 54, \"to\": 61, \"sentence\": \"But Comey, himself, said he found it 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Zia\", \"polarity\": 0, \"from\": 1560, \"to\": 1568, \"sentence\": \"A timeline of major political and other events in Pakistan's history:\\n__Aug. 14, 1947: Pakistan emerges as a sovereign state after getting independence when the departing British left India and split the subcontinent;\\n__Sept. 11, 1948: Pakistan's founder Mohammad Ali Jinnah dies;\\n__Oct. 16, 1951: Pakistan first prime minister, Liaquat Ali Khan, is assassinated in a gun attack at a rally in the city of Rawalpind, triggering political instability;\\n__Oct. 7, 1958: President Iskander Mirza abolishes the constitution and declares martial law; Gen. Muhammad Ayub Khan, then army chief becomes administrator;\\n__Oct. 27, 1958: Ayub forces the president to step down; Mirza is sent to exile in Britain where he later dies; Ayub declared himself president;\\n__March 25, 1969: After months of rioting in West and East Pakistan, Khan hands over power to army chief Gen. Agha Mohammed Yahya Khan;\\n__Dec. 7, 1970: East Pakistan-based Awami League wins general elections; Yahya Khan delays transfer of power, triggering widespread rioting in East Pakistan; civil war breaks out;\\n__Dec. 16, 1971: Pakistan troops surrender in East Pakistan after Indian armed intervention in the civil war; East Pakistan becomes independent Bangladesh;\\n__Dec. 20, 1971: Yahya Khan resigns, Zulfikar Ali Bhutto becomes president; a parliamentary system of government is adopted and Bhutto becomes prime minister;\\n__July 5, 1977: Army chief Gen. Ziaul Haq seizes power;\\n__April 4, 1979: Bhutto is hanged after the Supreme Court upholds death sentence on charges of conspiracy to murder and Gen. Zia rejects a mercy petition; Bhutto's daughter, Benazir Bhutto, takes up her father's legacy;\\n__Aug. 17, 1988: Gen. Zia dies in a mysterious plane crash;\\n__Nov. 16, 1988: Benazir Bhutto becomes Pakistan's first woman prime minister;\\n__Aug. 6, 1990: Benazir Bhutto's government is dismissed amid charges of corruption and mismanagement;\\n__Oct. 24, 1990: Parliamentary elections are held and Nawaz Sharif becomes prime minister;\\n__April 19, 1993: President Ghulam Ishaq Khan dismisses Sharif government on corruption charges but the Supreme Court reinstates Sharif; Sharif and Khan fail to reconcile and end conflict so the then-army chief Gen. Waheed Kakar forces both to resign;\\n__Oct. 6, 1993: Bhutto is voted back into power after mass demonstrations lead to the early dismissal of her 1990 successor, Sharif;\\n__Nov. 5, 1996: Bhutto's government is again dismissed amid renewed charges of corruption and incompetence raised by her party's leader, Farooq Leghari;\\n__Feb. 3, 1997: Elections bring Sharif back to power; Bhutto goes into self-exile to avoid prosecution on corruption allegations;\\n__Oct. 12, 1999: Army chief Gen. Pervez Musharraf ousts Sharif's government in a bloodless coup after Sharif fails in his attempt to sack the army chief.\", \"id\": \"polusa_v1_4537616_-1_4_Gen. Zia_1560_1568\"}\n{\"mention\": \"Zulfikar Ali Bhutto\", \"polarity\": 0, \"from\": 1262, \"to\": 1281, \"sentence\": \"A timeline of major political and other events in Pakistan's history:\\n__Aug. 14, 1947: Pakistan emerges as a sovereign state after getting independence when the departing British left India and split the subcontinent;\\n__Sept. 11, 1948: Pakistan's founder Mohammad Ali Jinnah dies;\\n__Oct. 16, 1951: Pakistan first prime minister, Liaquat Ali Khan, is assassinated in a gun attack at a rally in the city of Rawalpind, triggering political instability;\\n__Oct. 7, 1958: President Iskander Mirza abolishes the constitution and declares martial law; Gen. Muhammad Ayub Khan, then army chief becomes administrator;\\n__Oct. 27, 1958: Ayub forces the president to step down; Mirza is sent to exile in Britain where he later dies; Ayub declared himself president;\\n__March 25, 1969: After months of rioting in West and East Pakistan, Khan hands over power to army chief Gen. Agha Mohammed Yahya Khan;\\n__Dec. 7, 1970: East Pakistan-based Awami League wins general elections; Yahya Khan delays transfer of power, triggering widespread rioting in East Pakistan; civil war breaks out;\\n__Dec. 16, 1971: Pakistan troops surrender in East Pakistan after Indian armed intervention in the civil war; East Pakistan becomes independent Bangladesh;\\n__Dec. 20, 1971: Yahya Khan resigns, Zulfikar Ali Bhutto becomes president; a parliamentary system of government is adopted and Bhutto becomes prime minister;\\n__July 5, 1977: Army chief Gen. Ziaul Haq seizes power;\\n__April 4, 1979: Bhutto is hanged after the Supreme Court upholds death sentence on charges of conspiracy to murder and Gen. Zia rejects a mercy petition; Bhutto's daughter, Benazir Bhutto, takes up her father's legacy;\\n__Aug. 17, 1988: Gen. Zia dies in a mysterious plane crash;\\n__Nov. 16, 1988: Benazir Bhutto becomes Pakistan's first woman prime minister;\\n__Aug. 6, 1990: Benazir Bhutto's government is dismissed amid charges of corruption and mismanagement;\\n__Oct. 24, 1990: Parliamentary elections are held and Nawaz Sharif becomes prime minister;\\n__April 19, 1993: President Ghulam Ishaq Khan dismisses Sharif government on corruption charges but the Supreme Court reinstates Sharif; Sharif and Khan fail to reconcile and end conflict so the then-army chief Gen. Waheed Kakar forces both to resign;\\n__Oct. 6, 1993: Bhutto is voted back into power after mass demonstrations lead to the early dismissal of her 1990 successor, Sharif;\\n__Nov. 5, 1996: Bhutto's government is again dismissed amid renewed charges of corruption and incompetence raised by her party's leader, Farooq Leghari;\\n__Feb. 3, 1997: Elections bring Sharif back to power; Bhutto goes into self-exile to avoid prosecution on corruption allegations;\\n__Oct. 12, 1999: Army chief Gen. Pervez Musharraf ousts Sharif's government in a bloodless coup after Sharif fails in his attempt to sack the army chief.\", \"id\": \"polusa_v1_4537616_-1_4_Zulfikar Ali Bhutto_1262_1281\"}\n{\"mention\": \"Bibi\", \"polarity\": 1, \"from\": 315, \"to\": 319, \"sentence\": \"For Asia Bibi of Pakistan, 19th June 2018 marks nine years imprisonment for being Christian!https://t.co/aIeYn311hs#ACNireland #AidtotheChurchinNeed pic.twitter.com/9mwpECmRwZ — ACN Ireland (@ireland_acn) June 11, 2018\\nWilson Chowdhry, chairman of British Pakistani Christian Association (BPCA) said last week that Bibi has been the victim of intense persecution for comparing Christ’s sacrifice with the prophet.\", \"id\": \"polusa_v1_4345669_-1_11_Bibi_316_320\"}\n{\"mention\": \"Christ\", \"polarity\": 1, \"from\": 377, \"to\": 383, \"sentence\": \"For Asia Bibi of Pakistan, 19th June 2018 marks nine years imprisonment for being Christian!https://t.co/aIeYn311hs#ACNireland #AidtotheChurchinNeed pic.twitter.com/9mwpECmRwZ — ACN Ireland (@ireland_acn) June 11, 2018\\nWilson Chowdhry, chairman of British Pakistani Christian Association (BPCA) said last week that Bibi has been the victim of intense persecution for comparing Christ’s sacrifice with the prophet.\", \"id\": \"polusa_v1_4345669_-1_11_Christ_378_384\"}\n{\"mention\": \"Gillian\", \"polarity\": 0, \"from\": 85, \"to\": 92, \"sentence\": \"When Adam is mistaken for a transgender man by an ethereal 23-year-old lesbian named Gillian (Bobbi Salvör Menuez), he embraces the false identity, posing as a trans man as they date.\", \"id\": \"polusa_v1_131731738_-1_6_Gillian_85_92\"}\n{\"mention\": \"Adam\", \"polarity\": 0, \"from\": 5, \"to\": 9, \"sentence\": \"When Adam is mistaken for a transgender man by an ethereal 23-year-old lesbian named Gillian (Bobbi Salvör Menuez), he embraces the false identity, posing as a trans man as they date.\", \"id\": \"polusa_v1_131731738_-1_6_Adam_5_9\"}\n{\"mention\": \"Omar\", \"polarity\": 0, \"from\": 163, \"to\": 167, \"sentence\": \"Loomer said she was told by the platform that her account violated its rules against hateful conduct after she sent a tweet criticizing Minnesota Rep.-elect Ilhan Omar (D-Minn.) and her Muslim faith.\", \"id\": \"polusa_v1_55242497_-1_5_Rep.-elect Ilhan Omar_164_168\"}\n{\"mention\": \"Loomer\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Loomer said she was told by the platform that her account violated its rules against hateful conduct after she sent a tweet criticizing Minnesota Rep.-elect Ilhan Omar (D-Minn.) and her Muslim faith.\", \"id\": \"polusa_v1_55242497_-1_5_Laura Loomer_0_7\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 23, \"to\": 26, \"sentence\": \"“Nelson admitting that she added to Moore’s alleged signature is the final nail in the coffin.\", \"id\": \"polusa_v1_131721477_-1_13_Joshua Caplan_23_26\"}\n{\"mention\": \"Moore\", \"polarity\": -1, \"from\": 36, \"to\": 41, \"sentence\": \"“Nelson admitting that she added to Moore’s alleged signature is the final nail in the coffin.\", \"id\": \"polusa_v1_131721477_-1_13_Moore_36_41\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 3, \"to\": 5, \"sentence\": \"As he considers who to surround himself with, Trump is calling on President Obama for counsel.\", \"id\": \"allsides_1561_630_7_retired Marine General John Kelly_3_5\"}\n{\"mention\": \"President Obama\", \"polarity\": 1, \"from\": 66, \"to\": 81, \"sentence\": \"As he considers who to surround himself with, Trump is calling on President Obama for counsel.\", \"id\": \"allsides_1561_630_7_Obama_66_81\"}\n{\"mention\": \"Clifford\", \"polarity\": 0, \"from\": 37, \"to\": 45, \"sentence\": \"The Journal previously reported that Clifford had been weighing an appearance on ABC’s “Good Morning America” last fall to discuss Trump.\", \"id\": \"allsides_93_37_15_Clifford_37_45\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 131, \"to\": 136, \"sentence\": \"The Journal previously reported that Clifford had been weighing an appearance on ABC’s “Good Morning America” last fall to discuss Trump.\", \"id\": \"allsides_93_37_15_\\\"President Trump_131_136\"}\n{\"mention\": \"Hagel\", \"polarity\": 1, \"from\": 49, \"to\": 54, \"sentence\": \"But in remarks at the White House, Obama praised Hagel as \\\"an exemplary defense secretary\\\" and steady hand for strategy and budget.\", \"id\": \"allsides_3890_1612_14_Hagel_49_54\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 35, \"to\": 40, \"sentence\": \"But in remarks at the White House, Obama praised Hagel as \\\"an exemplary defense secretary\\\" and steady hand for strategy and budget.\", \"id\": \"allsides_3890_1612_14_President Obama_35_40\"}\n{\"mention\": \"Gervais\", \"polarity\": 0, \"from\": 216, \"to\": 223, \"sentence\": \"“It may reflect any combination of genuine innumeracy [lack of math skills], incomprehension of an oddly phrased item, participant inattentiveness or jesting, sampling error, or a genuine flaw in the ... technique,” Gervais and Najle write in the paper.\", \"id\": \"allsides_1166_466_62_Gervais_216_223\"}\n{\"mention\": \"Najle\", \"polarity\": 0, \"from\": 228, \"to\": 233, \"sentence\": \"“It may reflect any combination of genuine innumeracy [lack of math skills], incomprehension of an oddly phrased item, participant inattentiveness or jesting, sampling error, or a genuine flaw in the ... technique,” Gervais and Najle write in the paper.\", \"id\": \"allsides_1166_466_62_Najle_228_233\"}\n{\"mention\": \"Jason Miller, a CNN contributor and former senior communications adviser for the Trump campaign\", \"polarity\": 0, \"from\": 0, \"to\": 95, \"sentence\": \"Jason Miller, a CNN contributor and former senior communications adviser for the Trump campaign, argued Clinton's surprising loss was due to her lack of a strong message.\", \"id\": \"polusa_v1_4748560_-1_3_Miller_0_96\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 104, \"to\": 111, \"sentence\": \"Jason Miller, a CNN contributor and former senior communications adviser for the Trump campaign, argued Clinton's surprising loss was due to her lack of a strong message.\", \"id\": \"polusa_v1_4748560_-1_3_Former Clinton_105_112\"}\n{\"mention\": \"ASHCROFT\", \"polarity\": 0, \"from\": 151, \"to\": 159, \"sentence\": \"TRUMP to rollback some of Obama’s Cuba policies -- FIRST IN PLAYBOOK: Kellyanne complains about West Wing colleagues -- REMEMBERING Zbig Brzezinski -- ASHCROFT hired by Qatar -- KATY TUR profile – B’DAY: Zeleny\\nDriving the Day\\nGood Saturday morning.\", \"id\": \"polusa_v1_79069296_-1_1_ASHCROFT_153_161\"}\n{\"mention\": \"KATY TUR\", \"polarity\": 0, \"from\": 178, \"to\": 186, \"sentence\": \"TRUMP to rollback some of Obama’s Cuba policies -- FIRST IN PLAYBOOK: Kellyanne complains about West Wing colleagues -- REMEMBERING Zbig Brzezinski -- ASHCROFT hired by Qatar -- KATY TUR profile – B’DAY: Zeleny\\nDriving the Day\\nGood Saturday morning.\", \"id\": \"polusa_v1_79069296_-1_1_KATY TUR_180_188\"}\n{\"mention\": \"Reid\", \"polarity\": 0, \"from\": 31, \"to\": 35, \"sentence\": \"Sandoval Leads List to Replace Reid in Senate\", \"id\": \"allsides_3420_1412_1_Reid_31_35\"}\n{\"mention\": \"Sandoval\", \"polarity\": 1, \"from\": 0, \"to\": 8, \"sentence\": \"Sandoval Leads List to Replace Reid in Senate\", \"id\": \"allsides_3420_1412_1_Sandoval_0_8\"}\n{\"mention\": \"Hulse\", \"polarity\": 0, \"from\": 3, \"to\": 8, \"sentence\": \"In Hulse’ telling, McConnell and Don McGahn, Trump’s now je\", \"id\": \"polusa_v1_38958147_-1_29_Carl Hulse_4_9\"}\n{\"mention\": \"McConnell\", \"polarity\": 0, \"from\": 19, \"to\": 28, \"sentence\": \"In Hulse’ telling, McConnell and Don McGahn, Trump’s now je\", \"id\": \"polusa_v1_38958147_-1_29_Senate majority leader Mitch McConnell_20_29\"}\n{\"mention\": \"White House press secretary Josh Earnest\", \"polarity\": 0, \"from\": 0, \"to\": 40, \"sentence\": \"White House press secretary Josh Earnest said the president decided that Mr. Clancy “has demonstrated that he was willing to conduct a candid, clear-eyed assessment of the shortcoming of that agency and to look at needed reforms and implement them.”\", \"id\": \"allsides_3570_1473_2_White House press secretary Josh Earnest_0_40\"}\n{\"mention\": \"Mr. Clancy “\", \"polarity\": 1, \"from\": 73, \"to\": 85, \"sentence\": \"White House press secretary Josh Earnest said the president decided that Mr. Clancy “has demonstrated that he was willing to conduct a candid, clear-eyed assessment of the shortcoming of that agency and to look at needed reforms and implement them.”\", \"id\": \"allsides_3570_1473_2_Joe Clancy_73_85\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 345, \"to\": 350, \"sentence\": \"“I think what we are going to see in the speech, Joe, is all of the language in the speech kind of fading left about transformation and transparency and checks and balances, but, frankly, I think the substance of the speech is going to be holding his ground,” Hayden told MSNBC’s “Morning Joe” host Joe Scarborough based on news reports of what Obama will unveil on Friday.\", \"id\": \"allsides_4658_1951_2_Obama_345_350\"}\n{\"mention\": \"Hayden\", \"polarity\": 0, \"from\": 260, \"to\": 266, \"sentence\": \"“I think what we are going to see in the speech, Joe, is all of the language in the speech kind of fading left about transformation and transparency and checks and balances, but, frankly, I think the substance of the speech is going to be holding his ground,” Hayden told MSNBC’s “Morning Joe” host Joe Scarborough based on news reports of what Obama will unveil on Friday.\", \"id\": \"allsides_4658_1951_2_Hayden_260_266\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Sanders wants to reinstate Glass-Steagall, the Depression-era banking legislation President Bill Clinton repealed that prevented big banks from engaging in both investment and commercial activities.\", \"id\": \"allsides_2579_1051_71_Bernie Sanders_0_7\"}\n{\"mention\": \"President Bill Clinton\", \"polarity\": 0, \"from\": 82, \"to\": 104, \"sentence\": \"Sanders wants to reinstate Glass-Steagall, the Depression-era banking legislation President Bill Clinton repealed that prevented big banks from engaging in both investment and commercial activities.\", \"id\": \"allsides_2579_1051_71_Hillary Clinton_82_104\"}\n{\"mention\": \"Kaine\", \"polarity\": -1, \"from\": 95, \"to\": 100, \"sentence\": \"Pence, speaking much more slowly and authoritatively, looked directly at the camera (something Kaine never did) and reiterated basic points about Hillary’s tax-and-spend policies and feckless foreign policy.\", \"id\": \"allsides_1750_712_7_Kaine_95_100\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Pence, speaking much more slowly and authoritatively, looked directly at the camera (something Kaine never did) and reiterated basic points about Hillary’s tax-and-spend policies and feckless foreign policy.\", \"id\": \"allsides_1750_712_7_Mike Pence_0_5\"}\n{\"mention\": \"White House press secretary Josh Earnest\", \"polarity\": 0, \"from\": 83, \"to\": 123, \"sentence\": \"SEE ALSO: Mitt Romney on Clinton Foundation uranium story: ‘It looks like bribery’ White House press secretary Josh Earnest insisted that President Obama is not troubled by reports that the Clinton Foundation accepted $2.35 million from a businessman involved in Russia’s uranium deals that required approval from the U.S. State Department as well as other countries.\", \"id\": \"allsides_3315_1366_4_White House press secretary Josh Earnest_83_123\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 25, \"to\": 32, \"sentence\": \"SEE ALSO: Mitt Romney on Clinton Foundation uranium story: ‘It looks like bribery’ White House press secretary Josh Earnest insisted that President Obama is not troubled by reports that the Clinton Foundation accepted $2.35 million from a businessman involved in Russia’s uranium deals that required approval from the U.S. State Department as well as other countries.\", \"id\": \"allsides_3315_1366_4_Clinton_25_32\"}\n{\"mention\": \"Paul Manafort\", \"polarity\": -1, \"from\": 39, \"to\": 52, \"sentence\": \"After Robert Mueller’s prosecutors and Paul Manafort meet in court on Friday, there is a chance the former Trump campaign chairman could leave in handcuffs.\", \"id\": \"polusa_v1_115965707_-1_1_Manafort_41_54\"}\n{\"mention\": \"Robert Mueller’s\", \"polarity\": 0, \"from\": 6, \"to\": 22, \"sentence\": \"After Robert Mueller’s prosecutors and Paul Manafort meet in court on Friday, there is a chance the former Trump campaign chairman could leave in handcuffs.\", \"id\": \"polusa_v1_115965707_-1_1_Robert Mueller’s_8_24\"}\n{\"mention\": \"Barr\", \"polarity\": 0, \"from\": 44, \"to\": 48, \"sentence\": \"But Rosenstein, FBI Director Chris Wray and Barr have each explicitly disputed that description.\", \"id\": \"polusa_v1_116013695_-1_17_Attorney General William Barr_44_48\"}\n{\"mention\": \"Rosenstein\", \"polarity\": 0, \"from\": 4, \"to\": 14, \"sentence\": \"But Rosenstein, FBI Director Chris Wray and Barr have each explicitly disputed that description.\", \"id\": \"polusa_v1_116013695_-1_17_Rosenstein_4_14\"}\n{\"mention\": \"LaPierre\", \"polarity\": 1, \"from\": 0, \"to\": 8, \"sentence\": \"LaPierre said, Mr. Hutchinson would be the best representative for the NRA.\", \"id\": \"allsides_5903_2529_15_LaPierre_0_8\"}\n{\"mention\": \"Mr. Hutchinson\", \"polarity\": 1, \"from\": 15, \"to\": 29, \"sentence\": \"LaPierre said, Mr. Hutchinson would be the best representative for the NRA.\", \"id\": \"allsides_5903_2529_15_Asa Hutchinson_15_29\"}\n{\"mention\": \"Democrat Antonio Villaraigosa\", \"polarity\": 1, \"from\": 129, \"to\": 158, \"sentence\": \"Meaning Cox would have no chance in November against Newsom. pic.twitter.com/lyEPFWW0D0 — Phil Willon (@philwillon) May 29, 2018\\nDemocrat Antonio Villaraigosa kicked off the final week of the gubernatorial campaign with a drive from Los Angeles to Fresno, where he nabbed the endorsement of Fresno Police Chief Jerry Dyer, visited a boxing program for troubled youth and planned to end the day at a Teamsters union hall.\", \"id\": \"polusa_v1_55089237_-1_5_Democrat Antonio Villaraigosa_129_158\"}\n{\"mention\": \"Meaning Cox\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"Meaning Cox would have no chance in November against Newsom. pic.twitter.com/lyEPFWW0D0 — Phil Willon (@philwillon) May 29, 2018\\nDemocrat Antonio Villaraigosa kicked off the final week of the gubernatorial campaign with a drive from Los Angeles to Fresno, where he nabbed the endorsement of Fresno Police Chief Jerry Dyer, visited a boxing program for troubled youth and planned to end the day at a Teamsters union hall.\", \"id\": \"polusa_v1_55089237_-1_5_GOP’s John Cox_0_11\"}\n{\"mention\": \"Mr. Clapper\", \"polarity\": 1, \"from\": 0, \"to\": 11, \"sentence\": \"Mr. Clapper and General Alexander got a warm reception from the chairman of the House Intelligence Committee, Representative Mike Rogers, Republican of Michigan, who defended the N.S.A.’s methods and said he had been adequately briefed about its activities.\", \"id\": \"allsides_4903_2063_30_Mr. Clapper_0_11\"}\n{\"mention\": \"General Alexander\", \"polarity\": 1, \"from\": 16, \"to\": 33, \"sentence\": \"Mr. Clapper and General Alexander got a warm reception from the chairman of the House Intelligence Committee, Representative Mike Rogers, Republican of Michigan, who defended the N.S.A.’s methods and said he had been adequately briefed about its activities.\", \"id\": \"allsides_4903_2063_30_General Alexander_16_33\"}\n{\"mention\": \"Slager\", \"polarity\": -1, \"from\": 23, \"to\": 29, \"sentence\": \"The ruling comes after Slager changed his story of the shooting a number of times.\", \"id\": \"allsides_225_91_3_former police officer Michael Slager of second-degree murder_23_29\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 38, \"to\": 41, \"sentence\": \"The ruling comes after Slager changed his story of the shooting a number of times.\", \"id\": \"allsides_225_91_3_Scott_38_41\"}\n{\"mention\": \"Yanukovych\", \"polarity\": 0, \"from\": 103, \"to\": 113, \"sentence\": \"Kremlin spokesman Dmitry Peskov made the envoy announcement after Putin and Ukrainian President Viktor Yanukovych talked over the phone, state-run news agency RIA Novosti reported, according to Reuters.\", \"id\": \"allsides_4546_1901_3_Yanukovych_103_113\"}\n{\"mention\": \"Putin\", \"polarity\": 0, \"from\": 66, \"to\": 71, \"sentence\": \"Kremlin spokesman Dmitry Peskov made the envoy announcement after Putin and Ukrainian President Viktor Yanukovych talked over the phone, state-run news agency RIA Novosti reported, according to Reuters.\", \"id\": \"allsides_4546_1901_3_Russian President Vladimir Putin_66_71\"}\n"
  },
  {
    "path": "NewsSentiment/experiments/default/datasets/newsmtsc-mt-hf/test.jsonl",
    "content": "{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 25, \"to\": 32, \"sentence\": \"Colin Powell: Everything Hillary Touches She Screws Up With Hubris\", \"id\": \"allsides_1811_738_0_Hillary_25_32\"}\n{\"mention\": \"Powell\", \"polarity\": 0, \"from\": 6, \"to\": 12, \"sentence\": \"Colin Powell: Everything Hillary Touches She Screws Up With Hubris\", \"id\": \"allsides_1811_738_0_former Secretary of State Colin Powell_6_12\"}\n{\"mention\": \"Campos\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Campos is out of the hospital, but is expected to have surgery at a later date to remove a bullet, Hickey told CNN's Wolf Blitzer.\", \"id\": \"polusa_v1_4939835_-1_5_Jesus Campos_0_7\"}\n{\"mention\": \"Hickey\", \"polarity\": 0, \"from\": 99, \"to\": 105, \"sentence\": \"Campos is out of the hospital, but is expected to have surgery at a later date to remove a bullet, Hickey told CNN's Wolf Blitzer.\", \"id\": \"polusa_v1_4939835_-1_5_Hickey_100_106\"}\n{\"mention\": \"Murkowski\", \"polarity\": 0, \"from\": 5, \"to\": 14, \"sentence\": \"Lisa Murkowski (R-Alaska), who in July joined Collins and McCain in rejecting a repeal bill from Senate leadership, has not announced her position.\", \"id\": \"allsides_547_218_21_Murkowski_5_14\"}\n{\"mention\": \"Collins\", \"polarity\": 0, \"from\": 46, \"to\": 53, \"sentence\": \"Lisa Murkowski (R-Alaska), who in July joined Collins and McCain in rejecting a repeal bill from Senate leadership, has not announced her position.\", \"id\": \"allsides_547_218_21_Collins_46_53\"}\n{\"mention\": \"Farage\", \"polarity\": 0, \"from\": 44, \"to\": 50, \"sentence\": \"As well as praising Le Pen in recent weeks, Farage had also declared in a TV interview on Sunday morning that the 48-year-old had “lost weight” and was “looking pretty fit”.\", \"id\": \"polusa_v1_39076960_-1_9_Nigel Farage_45_51\"}\n{\"mention\": \"Le Pen\", \"polarity\": 1, \"from\": 20, \"to\": 26, \"sentence\": \"As well as praising Le Pen in recent weeks, Farage had also declared in a TV interview on Sunday morning that the 48-year-old had “lost weight” and was “looking pretty fit”.\", \"id\": \"polusa_v1_39076960_-1_9_Marine Le Pen_21_27\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 157, \"to\": 160, \"sentence\": \"“The doctor talked to us for a minute and said over the past 15 years he had seen about 7 or 8 children her age with identical symptoms and more than likely she had a tick,” Lewis posted.\", \"id\": \"polusa_v1_4661663_-1_11_Evelyn_158_161\"}\n{\"mention\": \"Lewis\", \"polarity\": 0, \"from\": 174, \"to\": 179, \"sentence\": \"“The doctor talked to us for a minute and said over the past 15 years he had seen about 7 or 8 children her age with identical symptoms and more than likely she had a tick,” Lewis posted.\", \"id\": \"polusa_v1_4661663_-1_11_Lewis_175_180\"}\n{\"mention\": \"Alexis\", \"polarity\": 0, \"from\": 28, \"to\": 34, \"sentence\": \"After leaving the Reserves, Alexis worked as a waiter and delivery driver at the Happy Bowl Thai restaurant in White Settlement, a suburb of Fort Worth, said Afton Bradley, a former co-worker.\", \"id\": \"allsides_5043_2127_36_Alexis_28_34\"}\n{\"mention\": \"Afton Bradley, a former co-worker\", \"polarity\": 0, \"from\": 158, \"to\": 191, \"sentence\": \"After leaving the Reserves, Alexis worked as a waiter and delivery driver at the Happy Bowl Thai restaurant in White Settlement, a suburb of Fort Worth, said Afton Bradley, a former co-worker.\", \"id\": \"allsides_5043_2127_36_Mr. Bradley_158_191\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 43, \"to\": 48, \"sentence\": \"“We want Putin’s help on North Korea,” Mr. Trump said.\", \"id\": \"allsides_366_148_15_Mr. Trump_43_48\"}\n{\"mention\": \"Putin\", \"polarity\": 1, \"from\": 9, \"to\": 14, \"sentence\": \"“We want Putin’s help on North Korea,” Mr. Trump said.\", \"id\": \"allsides_366_148_15_President Vladimir V. Putin of Russia_9_14\"}\n{\"mention\": \"Wheeler\", \"polarity\": -1, \"from\": 147, \"to\": 154, \"sentence\": \"In April, Jeff Turrentine, the Culture & Politics columnist at The National Resources Defense Council's magazine onEarth, wrote: \\\"If you're hoping Wheeler could represent some sort of departure from Pruitt's (literal) scorched-earth agenda, he wouldn't.\\\"\", \"id\": \"polusa_v1_113872497_-1_17_acting EPA chief Andrew Wheeler_148_155\"}\n{\"mention\": \"Pruitt\", \"polarity\": -1, \"from\": 199, \"to\": 205, \"sentence\": \"In April, Jeff Turrentine, the Culture & Politics columnist at The National Resources Defense Council's magazine onEarth, wrote: \\\"If you're hoping Wheeler could represent some sort of departure from Pruitt's (literal) scorched-earth agenda, he wouldn't.\\\"\", \"id\": \"polusa_v1_113872497_-1_17_Scott Pruitt_200_206\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Mrs. Clinton was referencing comments by House Majority Leader Kevin McCarthy and other Republicans, who have suggested the Benghazi committee is designed to drive down her poll numbers and raise more questions about her use of a private email account while secretary of state.\", \"id\": \"allsides_2810_1147_10_Clinton_0_12\"}\n{\"mention\": \"secretary of state\", \"polarity\": -1, \"from\": 258, \"to\": 276, \"sentence\": \"Mrs. Clinton was referencing comments by House Majority Leader Kevin McCarthy and other Republicans, who have suggested the Benghazi committee is designed to drive down her poll numbers and raise more questions about her use of a private email account while secretary of state.\", \"id\": \"allsides_2810_1147_10_Mr. Gowdy_258_276\"}\n{\"mention\": \"Mr. Hagel\", \"polarity\": -1, \"from\": 52, \"to\": 61, \"sentence\": \"While a member of the Senate from Nebraska in 1998, Mr. Hagel criticized the nomination of James Hormel to be ambassador to Luxembourg because he was “openly, aggressively gay.”\", \"id\": \"allsides_5855_2508_6_Mr. Hagel_52_61\"}\n{\"mention\": \"James Hormel\", \"polarity\": -1, \"from\": 91, \"to\": 103, \"sentence\": \"While a member of the Senate from Nebraska in 1998, Mr. Hagel criticized the nomination of James Hormel to be ambassador to Luxembourg because he was “openly, aggressively gay.”\", \"id\": \"allsides_5855_2508_6_James Hormel_91_103\"}\n{\"mention\": \"Monday Justice Ginsburg\", \"polarity\": 0, \"from\": 3, \"to\": 26, \"sentence\": \"On Monday Justice Ginsburg doubled down, calling Mr. Trump “a faker,” who “has no consistency about him.”\", \"id\": \"allsides_2003_816_5_Justice Ruth Bader Ginsburg_3_26\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 49, \"to\": 58, \"sentence\": \"On Monday Justice Ginsburg doubled down, calling Mr. Trump “a faker,” who “has no consistency about him.”\", \"id\": \"allsides_2003_816_5_Donald Trump_49_58\"}\n{\"mention\": \"Martha Raddatz\", \"polarity\": 0, \"from\": 65, \"to\": 79, \"sentence\": 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\"id\": \"polusa_v1_38914194_-1_16_Bheki Cele_47_49\"}\n{\"mention\": \"AMY GOODMAN\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"AMY GOODMAN: For more, we are going to Lebanon, where we’re joined by Yazan al-Saadi, Syrian-Canadian writer, researcher based in Beirut.\", \"id\": \"allsides_1197_477_24_AMY GOODMAN_0_11\"}\n{\"mention\": \"Yazan al-Saadi\", \"polarity\": 0, \"from\": 70, \"to\": 84, \"sentence\": \"AMY GOODMAN: For more, we are going to Lebanon, where we’re joined by Yazan al-Saadi, Syrian-Canadian writer, researcher based in Beirut.\", \"id\": \"allsides_1197_477_24_Yazan al-Saadi_70_84\"}\n{\"mention\": \"Doan Thi Huong\", \"polarity\": 0, \"from\": 27, \"to\": 41, \"sentence\": \"Indonesian Siti Aisyah and Doan Thi Huong of Vietnam appeared subdued as the group moved around.\", \"id\": \"polusa_v1_39043030_-1_5_Doan Thi Huong_28_42\"}\n{\"mention\": \"Siti Aisyah\", \"polarity\": 0, \"from\": 11, \"to\": 22, \"sentence\": \"Indonesian Siti Aisyah and 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\"sentence\": \"And Rubio, although he said Wednesday that the Cornyn plan “dramatically improves the bill,” is working on a package that others in the Gang of Eight hope could emerge as an alternative.\", \"id\": \"allsides_5298_2250_9_Lindsey Graham (R-S.C.)_20_22\"}\n{\"mention\": \"Cruz\", \"polarity\": -1, \"from\": 149, \"to\": 153, \"sentence\": \"When Rubio refers to commercials making fun of his boots, or admits he “did not do well” in the debate, or contrasts himself to a petulant Trump and Cruz by saying, “Don’t worry—I’m not leaving the stage no matter what you ask me,” he’s hard to hate.\", \"id\": \"allsides_2465_1002_16_Cruz_149_153\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 139, \"to\": 144, \"sentence\": \"When Rubio refers to commercials making fun of his boots, or admits he “did not do well” in the debate, or contrasts himself to a petulant Trump and Cruz by saying, “Don’t worry—I’m not leaving the stage no matter what you ask me,” he’s hard to hate.\", \"id\": \"allsides_2465_1002_16_Donald Trump_139_144\"}\n{\"mention\": \"Ms. Machado\", \"polarity\": -1, \"from\": 45, \"to\": 56, \"sentence\": \"Regardless of how much Hillary Clinton wants Ms. Machado to be the poster child for misused women, she doesn’t fit the narrative.\", \"id\": \"allsides_1765_719_38_Alicia Machado_47_58\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 23, \"to\": 38, \"sentence\": \"Regardless of how much Hillary Clinton wants Ms. Machado to be the poster child for misused women, she doesn’t fit the narrative.\", \"id\": \"allsides_1765_719_38_Hillary Clinton_25_40\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 26, \"to\": 28, \"sentence\": \"“Also Sessions now admits he may have discussed candidate Trump’s positions with the Russians during the elections, which directly contradicts what Sessions said in his statement in March,” Goodman added.\", \"id\": \"polusa_v1_39111156_-1_32_The Democratic senator Patrick Leahy_27_29\"}\n{\"mention\": \"Goodman\", \"polarity\": 0, \"from\": 190, \"to\": 197, \"sentence\": \"“Also Sessions now admits he may have discussed candidate Trump’s positions with the Russians during the elections, which directly contradicts what Sessions said in his statement in March,” Goodman added.\", \"id\": \"polusa_v1_39111156_-1_32_Goodman_191_198\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 17, \"to\": 22, \"sentence\": \"He is jealous of Trump!\\\"\", \"id\": \"allsides_2462_1001_28_Donald Trump_17_22\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He is jealous of Trump!\\\"\", \"id\": \"allsides_2462_1001_28_@ahernandez85a Romney_0_2\"}\n{\"mention\": \"McCabe\", \"polarity\": -1, \"from\": 34, \"to\": 40, \"sentence\": \"Criticism of FBI from Republicans\\nMcCabe has come under fire in recent days from Republicans amid the release of anti-Trump text messages sent between FBI agent Peter Strzok, who was removed from Justice Department special counsel Robert Mueller's team when the messages were discovered, and FBI lawyer Lisa Page.\", \"id\": \"polusa_v1_4778653_-1_27_McCabe_35_41\"}\n{\"mention\": \"anti-Trump\", \"polarity\": -1, \"from\": 113, \"to\": 123, \"sentence\": \"Criticism of FBI from Republicans\\nMcCabe has come under fire in recent days from Republicans amid the release of anti-Trump text messages sent between FBI agent Peter Strzok, who was removed from Justice Department special counsel Robert Mueller's team when the messages were discovered, and FBI lawyer Lisa Page.\", \"id\": \"polusa_v1_4778653_-1_27_anti-Trump_114_124\"}\n{\"mention\": \"Soros\", \"polarity\": -1, \"from\": 6, \"to\": 11, \"sentence\": \"‘Stop Soros’ – Hungary Will Levy Tax on Pro-Mass Migration Groups to Fund Border Protection Force and Impose Restraining Orders on Campaigners Who Organise and Support Illegal Immigration https://t.co/w74k7V07hq — Jack Montgomery ن (@JackBMontgomery) January 19, 2018\\n“We will not remain silent and watch the execution of the Soros Plan: if need be, we will make use of stronger legal tools,” continued Orbán, highlighting the “Stop Soros” legislative package his government presented to parliament last week, which could see open borders NGOs assisting illegal migration taxed to provide funds for border protection.\", \"id\": \"polusa_v1_4326557_-1_10_Soros_7_12\"}\n{\"mention\": \"Orbán\", \"polarity\": 0, \"from\": 403, \"to\": 408, \"sentence\": \"‘Stop Soros’ – Hungary Will Levy Tax on Pro-Mass Migration Groups to Fund Border Protection Force and Impose Restraining Orders on Campaigners Who Organise and Support Illegal Immigration https://t.co/w74k7V07hq — Jack Montgomery ن (@JackBMontgomery) January 19, 2018\\n“We will not remain silent and watch the execution of the Soros Plan: if need be, we will make use of stronger legal tools,” continued Orbán, highlighting the “Stop Soros” legislative package his government presented to parliament last week, which could see open borders NGOs assisting illegal migration taxed to provide funds for border protection.\", \"id\": \"polusa_v1_4326557_-1_10_Orbán_404_409\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 0, \"from\": 16, \"to\": 23, \"sentence\": \"In other words, Gorsuch was more likely to vote like Scalia than Hardiman.\", \"id\": \"polusa_v1_52959796_-1_105_Gorsuch_16_23\"}\n{\"mention\": \"Scalia\", \"polarity\": 0, \"from\": 53, \"to\": 59, \"sentence\": \"In other words, Gorsuch was more likely to vote like Scalia than Hardiman.\", \"id\": \"polusa_v1_52959796_-1_105_Justice Scalia who died last February_53_59\"}\n{\"mention\": \"President Trump\", \"polarity\": 0, \"from\": 56, \"to\": 71, \"sentence\": \"Here’s what he told us:\\nWhen Lesley Stahl sat down with President Trump on “60 Minutes,” they were in the same room.\", \"id\": \"polusa_v1_4074853_-1_10_President Trump_56_71\"}\n{\"mention\": \"Lesley Stahl\", \"polarity\": 0, \"from\": 29, \"to\": 41, \"sentence\": \"Here’s what he told us:\\nWhen Lesley Stahl sat down with President Trump on “60 Minutes,” they were in the same room.\", \"id\": \"polusa_v1_4074853_-1_10_Lesley Stahl_29_41\"}\n{\"mention\": \"Christensen\", \"polarity\": -1, \"from\": 19, \"to\": 30, \"sentence\": \"Prosecutors allege Christensen took advantage of Zhang's small stature and lack of English fluency after seeing her by a bus stop, pulling up and successfully talking her into his car.\", \"id\": \"polusa_v1_113865843_-1_21_Christensen_20_31\"}\n{\"mention\": \"Zhang\", \"polarity\": 0, \"from\": 49, \"to\": 54, \"sentence\": \"Prosecutors allege Christensen took advantage of Zhang's small stature and lack of English fluency after seeing her by a bus stop, pulling up and successfully talking her into his car.\", \"id\": \"polusa_v1_113865843_-1_21_26-year-old Yingying Zhang_50_55\"}\n{\"mention\": \"Burns\", \"polarity\": 0, \"from\": 230, \"to\": 235, \"sentence\": \"More newsletters\\n\\\"A portion of MNG's pension plan assets were successfully managed by Alden, for which MNG's pension plans were not charged and paid no management or performance fees, resulting in less expense to the plans,\\\" said Burns.\", \"id\": \"polusa_v1_4123910_-1_26_Burns_230_235\"}\n{\"mention\": \"Alden\", \"polarity\": 1, \"from\": 86, \"to\": 91, \"sentence\": \"More newsletters\\n\\\"A portion of MNG's pension plan assets were successfully managed by Alden, for which MNG's pension plans were not charged and paid no management or performance fees, resulting in less expense to the plans,\\\" said Burns.\", \"id\": \"polusa_v1_4123910_-1_26_Alden_86_91\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 193, \"to\": 198, \"sentence\": \"Although we don’t know what was really going on at that moment, the image garnered plenty of commentary from armchair body-language experts on the internet:\\nAP Photo: Angela Merkel puts Donald Trump in timeout for throwing his toys at the dinner table pic.twitter.com/JWfNVEH3SE — jordan (@JordanUhl) June 9, 2018\\nAngela Merkel's office has released this photo taken today at the G7, which tells you a lot about how things went. pic.twitter.com/IXX6K3ayys — David Mack (@davidmackau) June 9, 2018\\nCheck out Japanese Jim Halpert in between Abe and Merkel.\", \"id\": \"polusa_v1_3909404_-1_9_Donald Trump's_194_199\"}\n{\"mention\": \"Abe\", \"polarity\": 0, \"from\": 539, \"to\": 542, \"sentence\": \"Although we don’t know what was really going on at that moment, the image garnered plenty of commentary from armchair body-language experts on the internet:\\nAP Photo: Angela Merkel puts Donald Trump in timeout for throwing his toys at the dinner table pic.twitter.com/JWfNVEH3SE — jordan (@JordanUhl) June 9, 2018\\nAngela Merkel's office has released this photo taken today at the G7, which tells you a lot about how things went. pic.twitter.com/IXX6K3ayys — David Mack (@davidmackau) June 9, 2018\\nCheck out Japanese Jim Halpert in between Abe and Merkel.\", \"id\": 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trying to push a false narrative about President Trump's administration to make up for their own failings.\", \"id\": \"polusa_v1_4428379_-1_2_Nancy Pelosi_86_98\"}\n{\"mention\": \"Spicer\", \"polarity\": 0, \"from\": 40, \"to\": 46, \"sentence\": \"Former White House Press Secretary Sean Spicer said on Wednesday that House Speaker Nancy Pelosi and the Democratic Party are trying to push a false narrative about President Trump's administration to make up for their own failings.\", \"id\": \"polusa_v1_4428379_-1_2_Spicer_42_48\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 41, \"to\": 56, \"sentence\": \"Philippe Reines, former spokesperson for Hillary Clinton, expressed hope that Bill Clinton's wife would make another run for the presidency.\", \"id\": \"polusa_v1_4306959_-1_1_Clinton_43_58\"}\n{\"mention\": \"Philippe Reines\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Philippe Reines, former spokesperson for Hillary Clinton, expressed hope that Bill Clinton's wife would make another run for the presidency.\", \"id\": \"polusa_v1_4306959_-1_1_Philippe Reines_2_17\"}\n{\"mention\": \"Cruz\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Cruz responded: > Look, Drudge Report over the years has done a good job highlighting the excesses of the left and the excesses of liberalism, and about the past month the Drudge Report has basically become the attack site for the Donald Trump campaign.\", \"id\": \"allsides_2320_943_6_Ted Cruz_0_4\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 231, \"to\": 243, \"sentence\": \"Cruz responded: > Look, Drudge Report over the years has done a good job highlighting the excesses of the left and the excesses of liberalism, and about the past month the Drudge Report has basically become the attack site for the Donald Trump campaign.\", \"id\": \"allsides_2320_943_6_Donald Trump_231_243\"}\n{\"mention\": \"Palm Beach County State Attorney David Aronberg\", \"polarity\": 0, \"from\": 114, \"to\": 161, \"sentence\": \"The decision not to press charges against Corey Lewandowski is scheduled to be announced on Thursday afternoon by Palm Beach County State Attorney David Aronberg.\", \"id\": \"allsides_2314_941_2_Palm Beach County State Attorney David Aronberg_114_161\"}\n{\"mention\": \"Corey Lewandowski\", \"polarity\": -1, \"from\": 42, \"to\": 59, \"sentence\": \"The decision not to press charges against Corey Lewandowski is scheduled to be announced on Thursday afternoon by Palm Beach County State Attorney David Aronberg.\", \"id\": \"allsides_2314_941_2_Corey Lewandowski_42_59\"}\n{\"mention\": \"’m\", \"polarity\": 1, \"from\": 100, \"to\": 102, \"sentence\": \"Sean Rayford/Getty Images, FILE\\nHe told ABC News’ Senior Washington Reporter Devin Dwyer in June, “I’m going to distinguish myself as a candidate, who was the first in the family to go to college, a father of two kids paying off student loan debt, which he says is just under $100,000.”\", \"id\": \"polusa_v1_115843421_-1_20_’m_101_103\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 32, \"to\": 34, \"sentence\": \"Sean Rayford/Getty Images, FILE\\nHe told ABC News’ Senior Washington Reporter Devin Dwyer in June, “I’m going to distinguish myself as a candidate, who was the first in the family to go to college, a father of two kids paying off student loan debt, which he says is just under $100,000.”\", \"id\": \"polusa_v1_115843421_-1_20_Eric Swalwell_33_35\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 115, \"to\": 118, \"sentence\": \"The military removed President Mohamed Mursi, a senior Brotherhood official, on July 3 after mass protests against his rule.\", \"id\": \"allsides_5134_2171_17_Mubarak_115_118\"}\n{\"mention\": \"Mursi\", \"polarity\": -1, \"from\": 39, \"to\": 44, \"sentence\": \"The military removed President Mohamed Mursi, a senior Brotherhood official, on July 3 after mass protests against his rule.\", \"id\": \"allsides_5134_2171_17_Mursi_39_44\"}\n{\"mention\": \"’m\", \"polarity\": 0, \"from\": 42, \"to\": 44, \"sentence\": \"He added: “I already know where you live I’m on you.\", \"id\": \"polusa_v1_39138877_-1_11_’m_42_44\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He added: “I already know where you live I’m on you.\", \"id\": \"polusa_v1_39138877_-1_11_Kasowitz_0_2\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 48, \"to\": 51, \"sentence\": \"Pence, though, made sure to praise Trump during his remarks Friday.\", \"id\": \"allsides_2256_917_16_Cruz_48_51\"}\n{\"mention\": \"Pence\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Pence, though, made sure to praise Trump during his remarks Friday.\", \"id\": \"allsides_2256_917_16_Pence_0_5\"}\n{\"mention\": \"Dershowitz\", \"polarity\": -1, \"from\": 173, \"to\": 183, \"sentence\": \"“When all the records come out it will show that Epstein and [Epstein’s alleged madam Ghislaine] Maxwell were trafficking girls to the benefit of his friends, including Mr. Dershowitz,” Cassell said in oral arguments for a case filed by the Miami Herald to unseal a collection of court documents relating to Giuffre’s now settled lawsuit against Maxwell.\", \"id\": \"polusa_v1_4292992_-1_12_Dershowitz_173_183\"}\n{\"mention\": \"Maxwell\", \"polarity\": -1, \"from\": 97, \"to\": 104, \"sentence\": \"“When all the records come out it will show that Epstein and [Epstein’s alleged madam Ghislaine] Maxwell were trafficking girls to the benefit of his friends, including Mr. Dershowitz,” Cassell said in oral arguments for a case filed by the Miami Herald to unseal a collection of court documents relating to Giuffre’s now settled lawsuit against Maxwell.\", \"id\": \"polusa_v1_4292992_-1_12_Maxwell_97_104\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 116, \"to\": 121, \"sentence\": \"O’Rourke condemned, “that racism that has always existed and flowed through the history of this country” and blamed Trump for allowing it to “do so in the open.”\", \"id\": \"polusa_v1_4347493_-1_5_President Donald Trump_117_122\"}\n{\"mention\": \"O’Rourke\", \"polarity\": 1, \"from\": 0, \"to\": 8, \"sentence\": \"O’Rourke condemned, “that racism that has always existed and flowed through the history of this country” and blamed Trump for allowing it to “do so in the open.”\", \"id\": \"polusa_v1_4347493_-1_5_Beto O'Rourke_1_9\"}\n{\"mention\": \"18-year-old Michael Brown\", \"polarity\": 0, \"from\": 132, \"to\": 157, \"sentence\": \"Residents in Ferguson, Missouri, on Wednesday night were once again demonstrating in protest of the controversial shooting death of 18-year-old Michael Brown.\", \"id\": \"allsides_4265_1779_1_18-year-old Michael Brown_134_159\"}\n{\"mention\": \"Ferguson\", \"polarity\": 0, \"from\": 13, \"to\": 21, \"sentence\": \"Residents in Ferguson, Missouri, on Wednesday night were once again demonstrating in protest of the controversial shooting death of 18-year-old Michael Brown.\", \"id\": \"allsides_4265_1779_1_Ferguson_15_23\"}\n{\"mention\": \"Garner\", \"polarity\": 0, \"from\": 52, \"to\": 58, \"sentence\": \"The 33-year-old officer has been on desk duty since Garner's death.\", \"id\": \"polusa_v1_113846174_-1_28_Garner_52_58\"}\n{\"mention\": \"The 33-year-old officer\", \"polarity\": -1, \"from\": 0, \"to\": 23, \"sentence\": \"The 33-year-old officer has been on desk duty since Garner's death.\", \"id\": \"polusa_v1_113846174_-1_28_Bannon_0_23\"}\n{\"mention\": \"Rove\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Rove said his other point was that Clinton’s health will be an issue if she runs in 2016 “whether she likes it or not.”\", \"id\": \"allsides_4438_1855_4_Karl Rove_0_4\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 35, \"to\": 42, \"sentence\": \"Rove said his other point was that Clinton’s health will be an issue if she runs in 2016 “whether she likes it or not.”\", \"id\": \"allsides_4438_1855_4_Hillary Clinton_35_42\"}\n{\"mention\": \"Abbott\", \"polarity\": -1, \"from\": 39, \"to\": 45, \"sentence\": \"Albanese says the negative reaction to Abbott’s first budget as prime minister underscored the fact that voters wanted to preserve the gains of the past.\", \"id\": \"polusa_v1_38914774_-1_17_Tony Abbott_40_46\"}\n{\"mention\": \"Albanese\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Albanese says the negative reaction to Abbott’s first budget as prime minister underscored the fact that voters wanted to preserve the gains of the past.\", \"id\": \"polusa_v1_38914774_-1_17_Anthony Albanese_0_9\"}\n{\"mention\": \"House Speaker John Boehner (R-Ohio)\", \"polarity\": -1, \"from\": 102, \"to\": 137, \"sentence\": \"A similar coalition balked later at final passage, which was supposed to occur around 2 p.m., forcing House Speaker John Boehner (R-Ohio) to delay a final vote until after 9 p.m. Pelosi marshaled her caucus against the bill even after the White House urged support.\", \"id\": \"allsides_3825_1583_8_House Speaker John Boehner (R-Ohio)_102_137\"}\n{\"mention\": \"Pelosi\", \"polarity\": -1, \"from\": 179, \"to\": 185, \"sentence\": \"A similar coalition balked later at final passage, which was supposed to occur around 2 p.m., forcing House Speaker John Boehner (R-Ohio) to delay a final vote until after 9 p.m. Pelosi marshaled her caucus against the bill even after the White House urged support.\", \"id\": \"allsides_3825_1583_8_Pelosi_179_185\"}\n{\"mention\": \"Sara\", \"polarity\": 0, \"from\": 15, \"to\": 19, \"sentence\": \"Mrs Heath said Sara's £189 weekly allowance will fall to £132.45 and, with rising charges, her income will be cut by 34% and she will no longer be able to afford transport to activities.\", \"id\": \"polusa_v1_18067969_-1_9_Sara_16_20\"}\n{\"mention\": \"Mrs Heath\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Mrs Heath said Sara's £189 weekly allowance will fall to £132.45 and, with rising charges, her income will be cut by 34% and she will no longer be able to afford transport to activities.\", \"id\": \"polusa_v1_18067969_-1_9_Image caption Marilyn Heath_0_10\"}\n{\"mention\": \"Museveni\", \"polarity\": 0, \"from\": 226, \"to\": 234, \"sentence\": \"Prince William accused of 'white saviour' mentality in Africa wildlife film Read more\\nTheresa May and the foreign secretary, Jeremy Hunt, attended the wildlife conference but neither were scheduled to hold separate talks with Museveni.\", \"id\": \"polusa_v1_38996546_-1_6_Museveni_227_235\"}\n{\"mention\": \"Prince William\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"Prince William accused of 'white saviour' mentality in Africa wildlife film Read more\\nTheresa May and the foreign secretary, Jeremy Hunt, attended the wildlife conference but neither were scheduled to hold separate talks with Museveni.\", \"id\": \"polusa_v1_38996546_-1_6_Prince William_1_15\"}\n{\"mention\": \"former director L. Patrick Gray\", \"polarity\": -1, \"from\": 82, \"to\": 113, \"sentence\": \"“Comey’s letter to the Hill was the most embarrassing moment for the Bureau since former director L. Patrick Gray burned Watergate documents in his fireplace,” diGenova judges.\", \"id\": \"allsides_1684_684_15_former director L. Patrick Gray_82_113\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 1, \"to\": 6, \"sentence\": \"“Comey’s letter to the Hill was the most embarrassing moment for the Bureau since former director L. Patrick Gray burned Watergate documents in his fireplace,” diGenova judges.\", \"id\": \"allsides_1684_684_15_FBI Director James Comey_1_6\"}\n{\"mention\": \"Prosecutor Benedict Peers\", \"polarity\": 0, \"from\": 0, \"to\": 25, \"sentence\": \"Prosecutor Benedict Peers claimed the officer twice drove deliberately at the fleeing suspect, however, he said PC Rumsey told his colleague \\\"sorry mate, I had a senior moment and hit the wrong pedal\\\".\", \"id\": \"polusa_v1_18551901_-1_8_Prosecutor Benedict Peers_0_26\"}\n{\"mention\": \"PC Rumsey\", \"polarity\": -1, \"from\": 112, \"to\": 121, \"sentence\": \"Prosecutor Benedict Peers claimed the officer twice drove deliberately at the fleeing suspect, however, he said PC Rumsey told his colleague \\\"sorry mate, I had a senior moment and hit the wrong pedal\\\".\", \"id\": \"polusa_v1_18551901_-1_8_Cambridgeshire PC Lee Rumsey_113_122\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 26, \"to\": 33, \"sentence\": \"Donaldson was featured in Mueller’s report repeatedly because of notes she took on the president’s comments and statements around when Trump fired FBI Director James Comey and Mueller was appointed.\", \"id\": \"polusa_v1_79088309_-1_13_Mueller_26_33\"}\n{\"mention\": \"Donaldson\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Donaldson was featured in Mueller’s report repeatedly because of notes she took on the president’s comments and statements around when Trump fired FBI Director James Comey and Mueller was appointed.\", \"id\": \"polusa_v1_79088309_-1_13_Annie Donaldson_0_9\"}\n{\"mention\": \"Edward Panetta, professor of communication studies at the University of Georgia and director of the Georgia Debate Union\", \"polarity\": 0, \"from\": 0, \"to\": 120, \"sentence\": \"Edward Panetta, professor of communication studies at the University of Georgia and director of the Georgia Debate Union, said Trump got out of the gate fast, but then struggled.\", \"id\": \"allsides_1772_722_16_Panetta_0_120\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 127, \"to\": 132, \"sentence\": \"Edward Panetta, professor of communication studies at the University of Georgia and director of the Georgia Debate Union, said Trump got out of the gate fast, but then struggled.\", \"id\": \"allsides_1772_722_16_Donald Trump_127_132\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 60, \"to\": 65, \"sentence\": \"This article has been updated with additional comments from Trump and Gingrich.\", \"id\": \"allsides_1696_690_32_Donald Trump_60_65\"}\n{\"mention\": \"Gingrich\", \"polarity\": 0, \"from\": 70, \"to\": 78, \"sentence\": \"This article has been updated with additional comments from Trump and Gingrich.\", \"id\": \"allsides_1696_690_32_Gingrich_70_78\"}\n{\"mention\": \"Roy\", \"polarity\": 0, \"from\": 34, \"to\": 37, \"sentence\": \"He also said there is no evidence Roy's life would have been saved if Carter had called for help.\", \"id\": \"polusa_v1_4431387_-1_13_Roy_34_37\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He also said there is no evidence Roy's life would have been saved if Carter had called for help.\", \"id\": \"polusa_v1_4431387_-1_13_Marx_0_2\"}\n{\"mention\": \"NPR's Ari Shapiro\", \"polarity\": 0, \"from\": 0, \"to\": 17, \"sentence\": \"NPR's Ari Shapiro speaks with Mueller's biographer, Garrett Graff, about Mueller's background — namely his formative experiences as a Marine in Vietnam.\", \"id\": \"polusa_v1_52882992_-1_2_NPR's Ari Shapiro_0_17\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 30, \"to\": 37, \"sentence\": \"NPR's Ari Shapiro speaks with Mueller's biographer, Garrett Graff, about Mueller's background — namely his formative experiences as a Marine in Vietnam.\", \"id\": \"polusa_v1_52882992_-1_2_Robert Mueller_30_37\"}\n{\"mention\": \"Tillerson\", \"polarity\": 1, \"from\": 50, \"to\": 59, \"sentence\": \"In a separate interview on CBS's Face the Nation, Tillerson said it was the goal of the U.S. and its allies to \\\"navigate a political outcome in which the Syrian people in fact will determine Bashar al-Assad's fate and his legitimacy,\\\" citing in part \\\"the United States' own founding principles are self-determination.\\\"\", \"id\": \"allsides_1183_473_22_Tillerson_50_59\"}\n{\"mention\": \"Assad\", \"polarity\": -1, \"from\": 201, \"to\": 206, \"sentence\": \"In a separate interview on CBS's Face the Nation, Tillerson said it was the goal of the U.S. and its allies to \\\"navigate a political outcome in which the Syrian people in fact will determine Bashar al-Assad's fate and his legitimacy,\\\" citing in part \\\"the United States' own founding principles are self-determination.\\\"\", \"id\": \"allsides_1183_473_22_Assad_201_206\"}\n{\"mention\": \"Japanese Prime Minister Shinzo Abe\", \"polarity\": 0, \"from\": 48, \"to\": 82, \"sentence\": \"Obama will have a press conference Tuesday with Japanese Prime 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\"polusa_v1_79077464_-1_24_Biden_128_133\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 73, \"to\": 76, \"sentence\": \"Story Continued Below\\n“Every time Devin comes on TV, we’re very proud of him,” said Mariann Hedstrom, chairwoman of the Tulare County Republican Party.\", \"id\": \"polusa_v1_79075704_-1_8_Nunes’_74_77\"}\n{\"mention\": \"Devin\", \"polarity\": 1, \"from\": 34, \"to\": 39, \"sentence\": \"Story Continued Below\\n“Every time Devin comes on TV, we’re very proud of him,” said Mariann Hedstrom, chairwoman of the Tulare County Republican Party.\", \"id\": \"polusa_v1_79075704_-1_8_Devin_35_40\"}\n{\"mention\": \"UC Berkeley Chancellor Nicholas Dirks\", \"polarity\": 1, \"from\": 14, \"to\": 51, \"sentence\": \"But actually, UC Berkeley Chancellor Nicholas Dirks had steadfastly defended the right of the Republicans to invite Yiannopoulos to speak, rejecting a request by a group of professors that the Breitbart News writer's appearance be canceled because he engaged in \\\"hate speech\\\" and, based on his appearance at another university, might harass or belittle individual students.\", \"id\": \"allsides_1381_555_6_UC Berkeley Chancellor Nicholas Dirks_14_51\"}\n{\"mention\": \"Yiannopoulos\", \"polarity\": -1, \"from\": 116, \"to\": 128, \"sentence\": \"But actually, UC Berkeley Chancellor Nicholas Dirks had steadfastly defended the right of the Republicans to invite Yiannopoulos to speak, rejecting a request by a group of professors that the Breitbart News writer's appearance be canceled because he engaged in \\\"hate speech\\\" and, based on his appearance at another university, might harass or belittle individual students.\", \"id\": \"allsides_1381_555_6_Yiannopoulos_116_128\"}\n{\"mention\": \"President Obama\", \"polarity\": 0, \"from\": 64, \"to\": 79, \"sentence\": \"I know you want to speak about Jeb Bush, but I'm speaking about President Obama,\\\" Cruz told reporters.\", \"id\": \"allsides_3811_1577_20_President Barack Obama_64_79\"}\n{\"mention\": \"Cruz\", \"polarity\": 0, \"from\": 82, \"to\": 86, \"sentence\": \"I know you want to speak about Jeb Bush, but I'm speaking about President Obama,\\\" Cruz told reporters.\", \"id\": \"allsides_3811_1577_20_Ted Cruz (R-Texas)_82_86\"}\n{\"mention\": \"HANNITY\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"HANNITY: DEMS ABUSING THEIR POWER, GUILTY OF 'PRESIDENTIAL HARASSMENT'\\n\\\"In their desperate effort to keep their Russia collusion hoax, their conspiracy theories alive for as long as possible, Chairman Jerry Nadler of the Judiciary Committee, and Intel Chair Adam 'The Cowardly' Schiff, are forcing Bob Mueller to testify in public on Capitol Hill.\\\"\", \"id\": \"polusa_v1_4434729_-1_7_Hannity_0_8\"}\n{\"mention\": \"Schiff\", \"polarity\": -1, \"from\": 278, \"to\": 284, \"sentence\": \"HANNITY: DEMS ABUSING THEIR POWER, GUILTY OF 'PRESIDENTIAL HARASSMENT'\\n\\\"In their desperate effort to keep their Russia collusion hoax, their conspiracy theories alive for as long as possible, Chairman Jerry Nadler of the Judiciary Committee, and Intel Chair Adam 'The Cowardly' Schiff, are forcing Bob Mueller to testify in public on Capitol Hill.\\\"\", \"id\": \"polusa_v1_4434729_-1_7_Schiff_279_285\"}\n{\"mention\": \"Duterte\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Duterte also asserted that he had no reason to believe China would lay claim to the Benham Rise, which it had not previously claimed.\", \"id\": \"polusa_v1_4330321_-1_13_Duterte himself_1_8\"}\n{\"mention\": \"Benham\", \"polarity\": 0, \"from\": 84, \"to\": 90, \"sentence\": \"Duterte also asserted that he had no reason to believe China would lay claim to the Benham Rise, which it had not previously claimed.\", \"id\": \"polusa_v1_4330321_-1_13_Benham_85_91\"}\n{\"mention\": \"Kanye West\", \"polarity\": -1, \"from\": 64, \"to\": 74, \"sentence\": \"Late-night funnyman Jimmy Kimmel mocked the \\\"irrational madman\\\" Kanye West for his meeting with President Donald Trump, saying that the conversation between the two men was something that \\\"typically be held between people wearing hospital bracelets.\\\"\", \"id\": \"polusa_v1_4295485_-1_1_Kanye West_66_76\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 96, \"to\": 118, \"sentence\": \"Late-night funnyman Jimmy Kimmel mocked the \\\"irrational madman\\\" Kanye West for his meeting with President Donald Trump, saying that the conversation between the two men was something that \\\"typically be held between people wearing hospital bracelets.\\\"\", \"id\": \"polusa_v1_4295485_-1_1_President Donald Trump_98_120\"}\n{\"mention\": \"Late-night funnyman Jimmy Kimmel\", \"polarity\": 1, \"from\": 0, \"to\": 32, \"sentence\": \"Late-night funnyman Jimmy Kimmel mocked the \\\"irrational madman\\\" Kanye West for his meeting with President Donald Trump, saying that the conversation between the two men was something that \\\"typically be held between people wearing hospital bracelets.\\\"\", \"id\": \"polusa_v1_4295485_-1_1_Late-night funnyman Jimmy Kimmel_0_34\"}\n{\"mention\": \"the AUMF\", \"polarity\": -1, \"from\": 314, \"to\": 322, \"sentence\": \"Ocasio-Cortez noted her error — but then insisted that Lee was correct to oppose military action after 9/11, and suggested she would have opposed the war in Afghanistan:\\nAfghanistan War* my apologies — Alexandria Ocasio-Cortez (@AOC) March 5, 2019\\n(But honestly we shouldn’t have been in either, and we should end the AUMF now while we’re at it) — Alexandria Ocasio-Cortez (@AOC) March 5, 2019\\nIn the 2008 presidential election, then-Sen.\", \"id\": \"polusa_v1_4295086_-1_29_the AUMF_315_323\"}\n{\"mention\": \"Lee\", \"polarity\": 1, \"from\": 55, \"to\": 58, \"sentence\": \"Ocasio-Cortez noted her error — but then insisted that Lee was correct to oppose military action after 9/11, and suggested she would have opposed the war in Afghanistan:\\nAfghanistan War* my apologies — Alexandria Ocasio-Cortez (@AOC) March 5, 2019\\n(But honestly we shouldn’t have been in either, and we should end the AUMF now while we’re at it) — Alexandria Ocasio-Cortez (@AOC) March 5, 2019\\nIn the 2008 presidential election, then-Sen.\", \"id\": \"polusa_v1_4295086_-1_29_Barbara Lee (D-CA)_56_59\"}\n{\"mention\": \"the president\", \"polarity\": 0, \"from\": 90, \"to\": 103, \"sentence\": \"For months, it’s been rumored that Kelly would soon leave the White House and on Saturday the president announced Kelly would be stepping down at the end of the December.\", \"id\": \"polusa_v1_4098639_-1_7_CLOSE President Donald Trump_90_103\"}\n{\"mention\": \"Kelly\", \"polarity\": 0, \"from\": 35, \"to\": 40, \"sentence\": \"For months, it’s been rumored that Kelly would soon leave the White House and on Saturday the president announced Kelly would be stepping down at the end of the December.\", \"id\": \"polusa_v1_4098639_-1_7_Rob Porter\\nKelly_35_40\"}\n{\"mention\": \"Pence\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Pence had been in contact with President Trump about the test.\", \"id\": \"allsides_1164_465_5_Pence_0_5\"}\n{\"mention\": \"President Trump\", \"polarity\": 0, \"from\": 31, \"to\": 46, \"sentence\": \"Pence had been in contact with President Trump about the test.\", \"id\": \"allsides_1164_465_5_President Trump_31_46\"}\n{\"mention\": \"Omarosa\", \"polarity\": 0, \"from\": 56, \"to\": 63, \"sentence\": \"KARL: So I want to ask you about these allegations from Omarosa, but – but before I get you on that, let’s – let’s hear again what she told us just after she left the White House in December.\", \"id\": \"polusa_v1_115899459_-1_67_Omarosa_57_64\"}\n{\"mention\": \"KARL\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"KARL: So I want to ask you about these allegations from Omarosa, but – but before I get you on that, let’s – let’s hear again what she told us just after she left the White House in December.\", \"id\": \"polusa_v1_115899459_-1_67_KARL_0_5\"}\n{\"mention\": \"Arthur Brooks, president of the conservative think tank the American Enterprise Institute\", \"polarity\": 1, \"from\": 0, \"to\": 89, \"sentence\": \"Arthur Brooks, president of the conservative think tank the American Enterprise Institute, said the meeting with Zuckerberg was \\\"productive\\\" and focused on potential solutions to avoid conscious and \\\"subconscious\\\" censorship in the future.\", \"id\": \"allsides_2161_879_18_\\\" Brooks_0_89\"}\n{\"mention\": \"Zuckerberg\", \"polarity\": 1, \"from\": 113, \"to\": 123, \"sentence\": \"Arthur Brooks, president of the conservative think tank the American Enterprise Institute, said the meeting with Zuckerberg was \\\"productive\\\" and focused on potential solutions to avoid conscious and \\\"subconscious\\\" censorship in the future.\", \"id\": \"allsides_2161_879_18_Facebook CEO Mark Zuckerberg_113_123\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 74, 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57.8; Clinton 35.5 percent General Election Clinton vs. Trump: Clinton +2.7 points Generic Congressional Vote: Republicans +0.5 DEBATE, POLL FORETELL LONG SLOG FOR HILLARY A contentious, sometimes nasty, Democratic debate between presumptive nominee Hillary Clinton and her rival, socialist Sen.\", \"id\": \"allsides_2517_1025_53_Bernie Sanders_341_348\"}\n{\"mention\": \"Rubio\", \"polarity\": 0, \"from\": 135, \"to\": 140, \"sentence\": \"Email FoxNewsFirst@FOXNEWS.COM POLL CHECK Real Clear Politics Averages National GOP nomination: Trump 33.2 percent; Cruz 20.7 percent; Rubio 13.3 percent; Carson 7.8 percent New Hampshire GOP Primary: Trump 32.4 percent; Rubio 15 percent; Cruz 12.6 percent; Kasich 11 percent; Bush 9.8 percent National Dem nomination: Clinton 50.5 percent; Sanders 37.2 percent New Hampshire Dem Primary: Sanders 57.8; Clinton 35.5 percent General Election Clinton vs. Trump: Clinton +2.7 points Generic Congressional Vote: Republicans +0.5 DEBATE, POLL FORETELL LONG SLOG 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  },
  {
    "path": "NewsSentiment/experiments/default/datasets/newsmtsc-mt-hf/train.jsonl",
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for Christians, the humanity of Holy Week makes our faith overlap with the world around us, just as after years of instructing his followers to stay quiet (at least in Mark) Jesus made his triumphant entrance into Jerusalem.\", \"id\": \"allsides_1167_466_34_Christ_178_183\"}\n{\"mention\": \"Jesus\", \"polarity\": 1, \"from\": 178, \"to\": 183, \"sentence\": \"Yet for Christians, the humanity of Holy Week makes our faith overlap with the world around us, just as after years of instructing his followers to stay quiet (at least in Mark) Jesus made his triumphant entrance into Jerusalem.\", \"id\": \"allsides_1167_466_34_Tony Blair_178_183\"}\n{\"mention\": \"Spicer\", \"polarity\": -1, \"from\": 5, \"to\": 11, \"sentence\": \"Sean Spicer Under Fire After Falsely Claims Nazis Never Used Poison Gas\", \"id\": \"allsides_1176_470_0_Spicer_5_11\"}\n{\"mention\": \"Spicer\", \"polarity\": -1, \"from\": 13, \"to\": 19, \"sentence\": \"Hours later, Spicer apologized, although he made a number 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\"sentence\": \"Russia’s international news agency RIA Novosti reports the Russian President Vladimir Putin has been alerted to the explosion, which the agency calls an “attack”.\", \"id\": \"allsides_1209_483_3_the Russian President Vladimir Putin_55_91\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said it was “too early to say” what caused the blast but that it could be “criminal or terrorist”.\", \"id\": \"allsides_1210_483_27_Putin_0_2\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 1, \"from\": 27, \"to\": 34, \"sentence\": \"McConnell said Sunday that Gorsuch “deserves to be confirmed” and “will ultimately be confirmed.”\", \"id\": \"allsides_1213_484_7_Judge Neil Gorsuch_27_34\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 75, \"to\": 80, \"sentence\": \"Some argue that Flynn's discussion of sanctions with Sergey Kislyak before Trump's inauguration may have broken an old law that prohibits unauthorized citizens from negotiating with 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22, \"sentence\": \"Donald Trump: ‘Russian connection non-sense’ is cover for Clinton’s ‘many mistakes’\", \"id\": \"allsides_1349_542_0_Russian_15_22\"}\n{\"mention\": \"former Trump campaign chairman Paul Manafort\", \"polarity\": -1, \"from\": 64, \"to\": 108, \"sentence\": \"Among those supposedly communicating with Russian nationals was former Trump campaign chairman Paul Manafort, the report said.\", \"id\": \"allsides_1349_542_14_former Trump campaign chairman Paul Manafort_64_108\"}\n{\"mention\": \"Russian\", \"polarity\": -1, \"from\": 42, \"to\": 49, \"sentence\": \"Among those supposedly communicating with Russian nationals was former Trump campaign chairman Paul Manafort, the report said.\", \"id\": \"allsides_1349_542_14_Russian_42_49\"}\n{\"mention\": \"Pence\", \"polarity\": 0, \"from\": 47, \"to\": 52, \"sentence\": \"A Trump administration official “stressed that Pence made his comments based on his conversation with Flynn,” The Post report said.\", \"id\": 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Trump_123_138\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 22, \"to\": 27, \"sentence\": \"Her relationship with Trump has been contentious: In January, Haley delivered the Republican response to President Obama's final State of the Union address, and, without mentioning Trump by name, appeared to criticize him and his candidacy: “During anxious times, it can be tempting to follow the siren call of the angriest voices.”\", \"id\": \"allsides_1617_652_27_Donald Trump_22_27\"}\n{\"mention\": \"Nikki Haley\", \"polarity\": 0, \"from\": 2, \"to\": 13, \"sentence\": \"— Nikki Haley (@nikkihaley) March 1, 2016 As it became clear Trump would win the primary, Haley's name was floated as a potential vice-presidential candidate.\", \"id\": \"allsides_1617_652_32_Nikki Haley_2_13\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She's also the first Indian American to serve as the state's governor (and only the second in the United States, after Louisiana's Bobby Jindal.) At 44, she's the youngest current governor.\", \"id\": \"allsides_1617_652_9_Nikki Haley_0_3\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 42, \"to\": 47, \"sentence\": \"“The meeting is taking place as planned,” Trump spokeswoman Hope Hicks said in a text message, according to a pool report.\", \"id\": \"allsides_1620_654_2_President-elect Donald Trump_42_47\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 59, \"to\": 68, \"sentence\": \"Eileen Murphy, a spokeswoman for the paper, confirmed that Mr. Trump’s staff told them the meeting was on again.\", \"id\": \"allsides_1620_654_3_President-elect Donald Trump_59_68\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 11, \"to\": 20, \"sentence\": \"Not nice,” Mr. Trump tweeted Tuesday.\", \"id\": \"allsides_1620_654_7_President-elect Donald Trump_11_20\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 97, \"to\": 106, \"sentence\": \"The paper disputed this, saying it had always been pushing for 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Reagan did that very skillfully, whatever one may think of his vision.\", \"id\": \"allsides_1628_656_45_Ronald Reagan_0_13\"}\n{\"mention\": \"McManus\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"McManus identified the San Antonio detective killed Sunday as Benjamin Marconi, 50, a 20-year veteran of the force.\", \"id\": \"allsides_1629_657_17_McManus_0_7\"}\n{\"mention\": \"The 46-year-old officer, who was not named\", \"polarity\": 0, \"from\": 0, \"to\": 42, \"sentence\": \"The 46-year-old officer, who was not named, is a married father of three and, like Marconi, a 20-year veteran of the force.\", \"id\": \"allsides_1630_657_20_The 46-year-old officer, who was not named_0_42\"}\n{\"mention\": \"Jeff\", \"polarity\": -1, \"from\": 12, \"to\": 16, \"sentence\": \"Trump Picks Jeff Sessions, Senator Accused Of Racism, For Attorney General\", \"id\": \"allsides_1635_660_0_Richard Shelby (R-Ala.)_12_16\"}\n{\"mention\": \"Sessions\", \"polarity\": 1, \"from\": 41, \"to\": 49, \"sentence\": \"Trump said in a statement on Friday that Sessions was a “world-class legal mind and considered a truly great Attorney General and U.S. Attorney in the state of Alabama.”\", \"id\": \"allsides_1635_660_11_Sessions_41_49\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Flynn has also worried some national security experts with his warmth toward Russia.\", \"id\": \"allsides_1636_660_28_Flynn_0_5\"}\n{\"mention\": \"Yellen\", \"polarity\": 0, \"from\": 16, \"to\": 22, \"sentence\": \"In her remarks, Yellen said the Fed, “continues to expect that the evolution of the economy will warrant only gradual increases in the federal funds rate over time” in order to reach full employment and not overshoot on inflation.\", \"id\": \"allsides_1637_661_22_Fed Chair Janet L. Yellen_16_22\"}\n{\"mention\": \"Federal Reserve Chair Janet Yellen\", \"polarity\": 0, \"from\": 2, \"to\": 36, \"sentence\": \"– Federal Reserve Chair Janet Yellen said Thursday that an interest rate increase likely will be appropriate “relatively soon” as long as there is further evidence of progress in the economy.\", \"id\": \"allsides_1638_661_2_Federal Reserve Chair Janet Yellen_2_36\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He said he was proud of the work his team had done to produce policy and personnel guidance “on the complex national security challenges facing our great country”.\", \"id\": \"allsides_1639_662_9_National security adviser Mike Rogers_0_2\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 24, \"to\": 29, \"sentence\": \"\\\"People didn't vote for Trump so that he could bring a white supremacist into the White House,\\\" Sen.\", \"id\": \"allsides_1640_662_13_President-elect Donald Trump_24_29\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 22, \"to\": 27, \"sentence\": \"And there are reports Trump is considering Sen.\", \"id\": \"allsides_1640_662_9_President-elect Donald Trump_22_27\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 112, \"to\": 117, \"sentence\": \"At the very least, the next G7 meeting scheduled for May in Sicily is going to look very different from the one Obama attended in Japan this past spring.\", \"id\": \"allsides_1641_663_27_Obama_112_117\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 19, \"to\": 24, \"sentence\": \"Without mentioning Trump by name, Obama told Greek President Prokopis Pavlopoulos that a strong NATO is of “utmost importance” and would provide “significant continuity even as we see a transition in government in the United States.”\", \"id\": \"allsides_1642_663_2_Donald Trump_19_24\"}\n{\"mention\": \"\\\" Trump\", \"polarity\": 1, \"from\": 92, \"to\": 99, \"sentence\": \"Now I will have them both with me in the White House as we work to make America great again,\\\" Trump said.\", \"id\": \"allsides_1643_664_12_President-elect Donald Trump_92_99\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 71, \"to\": 76, \"sentence\": \"\\\"We will have that same partnership in working to help President-elect Trump achieve his agenda,\\\" Bannon said.\", \"id\": \"allsides_1643_664_16_President-elect Donald Trump_71_76\"}\n{\"mention\": \"President Putin\", \"polarity\": 1, \"from\": 72, \"to\": 87, \"sentence\": \"The Trump transition team reported that “President-elect Trump noted to President Putin that he is very much looking forward to having a strong and enduring relationship with Russia and the people of Russia.”\", \"id\": \"allsides_1644_664_7_President Vladimir V. 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Comey can redeem himself in history.\", \"id\": \"allsides_1671_679_19_Clinton_66_73\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 4, \"to\": 9, \"sentence\": \"But Trump holds a sizable 53-28 percent advantage among voters who say they don't lean toward either party, a group that accounts for about 10 percent of likely voters.\", \"id\": \"allsides_1678_682_18_Donald Trump_4_9\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 56, \"to\": 61, \"sentence\": \"The professional considerations that may have motivated Comey are obvious.\", \"id\": \"allsides_1683_684_18_FBI Director James Comey_56_61\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Comey, a Republican, faced considerable criticism and scrutiny from congressional Republicans for declining to press charges against Clinton for her handling of classified emails on a private email server.\", \"id\": \"allsides_1683_684_19_FBI Director James Comey_0_5\"}\n{\"mention\": 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\"allsides_1684_684_0_Clinton_39_46\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 138, \"to\": 145, \"sentence\": \"“The stunning revelation in Comey’s letter to various Congressional committees today reveals that the Bureau’s investigation into Hillary Clinton’s use of a private, unsecured, unencrypted server in her home to conduct government business was not thorough,” diGenova told The American Spectator on Friday.\", \"id\": \"allsides_1684_684_10_Clinton_138_145\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 152, \"to\": 154, \"sentence\": \"The director, in a damned-if-I-do-damned-if-I-don’t position this summer in opening up the bureau to charges of politicizing the apolitical FBI whether he recommended an indictment of not, now, less than two weeks before an election, puts himself and the bureau in a far more precarious spot.\", \"id\": \"allsides_1684_684_18_former director L. 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.@MegynKelly made a total fool out of herself tonight- attacking @realDonaldTrump.\", \"id\": \"allsides_1696_690_23_Kelly_65_72\"}\n{\"mention\": \"Nancy Pelosi\", \"polarity\": -1, \"from\": 11, \"to\": 23, \"sentence\": \"Somewhere, Nancy Pelosi is chewing the inside of her cheek as she glares icily at a life-size Donald Trump 'FatHead' decal she's plastered onto the ceiling over her bed.\", \"id\": \"allsides_16_6_1_Nancy Pelosi_13_25\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 114, \"to\": 119, \"sentence\": \"By ELENA SCHNEIDER No presidential candidate since the advent of modern polling has overcome the sort of deficits Trump faces nationally — where he trails Clinton by an average of 5.9 points — and in swing states with two weeks to go in an election.\", \"id\": \"allsides_1701_692_11_little Trump_114_119\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 168, \"to\": 175, \"sentence\": \"With debate season over and the clock running out for significant swings in public opinion to materialize, the baton now goes to the get-out-the-vote operations, where Clinton enjoys an overwhelming advantage.\", \"id\": \"allsides_1701_692_13_Clinton_168_175\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 8, \"to\": 15, \"sentence\": \"Hillary Clinton enters the final 15 days of the race safely ahead in states worth more than 270 electoral votes.\", \"id\": \"allsides_1701_692_2_Clinton_8_15\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 121, \"to\": 128, \"sentence\": \"Larry Sabato’s Crystal Ball: “With less than three weeks to go, and all of the debates blessedly in the rearview mirror, Clinton is in a commanding position in the contest to become the 45th president… “A striking development in recent days has been the smattering of polling showing Trump with weak leads in some reliably Republican states.\", \"id\": \"allsides_1702_692_22_Hillary Clinton_121_128\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 3, \"to\": 10, \"sentence\": \"Is Clinton now the favorite to reach 270 electoral votes, or, according to some forecasts, much more?\", \"id\": \"allsides_1702_692_6_Clinton_3_10\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 15, \"to\": 18, \"sentence\": \"In the case of his Saturday speech, headlines were dominated by his lawsuit threat, not his detailed policy prescriptions.\", \"id\": \"allsides_1703_693_11_Mr. Trump_15_18\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 12, \"to\": 21, \"sentence\": \"But much of Mr. Trump’s pitch was lost as headlines instead focused on his vow to sue the 11 women that have come forward in recent weeks to accuse him of sexual assault.\", \"id\": \"allsides_1703_693_4_he_12_21\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 12, \"to\": 21, \"sentence\": \"But much of Mr. Trump’s pitch was lost as headlines instead focused on his vow to sue the 11 women that have come forward in recent weeks to accuse him of sexual assault.\", \"id\": \"allsides_1703_693_4_Mr. Trump_12_21\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump has a long history of threatening and occasionally following through on litigation, and in raising the possibility of suing his female accusers, he may have simply been trying to stop more from coming forward.\", \"id\": \"allsides_1704_693_22_Mr. Trump_0_9\"}\n{\"mention\": \"Saturday\", \"polarity\": 0, \"from\": 13, \"to\": 21, \"sentence\": \"At her rally Saturday in Pennsylvania, Mrs. Clinton devoted much of her remarks to the state’s contentious Senate race, giving an extended plug to the Democratic candidate, Katie McGinty, and attacking the Republican incumbent, Senator Patrick J. Toomey, for not denouncing Mr. Trump for his vulgar remarks about women captured in a recording.\", \"id\": \"allsides_1704_693_31_Saturday_13_21\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 274, \"to\": 283, \"sentence\": \"At her rally Saturday in Pennsylvania, Mrs. Clinton devoted much of her remarks to the state’s contentious Senate race, giving an extended plug to the Democratic candidate, Katie McGinty, and attacking the Republican incumbent, Senator Patrick J. Toomey, for not denouncing Mr. Trump for his vulgar remarks about women captured in a recording.\", \"id\": \"allsides_1704_693_31_Donald J. Trump_274_283\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 7, \"to\": 10, \"sentence\": \"Yet in his own Gettysburg address, Mr. Trump, who has been sliding in the polls less than three weeks before Election Day, did not offer much in the way of race-changing oratory and did not seem to embrace Lincoln’s unifying ambition.\", \"id\": \"allsides_1704_693_3_Donald J. Trump_7_10\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 12, \"to\": 27, \"sentence\": \"CLEVELAND — Hillary Clinton entered the final phase of her campaign on Friday, working to ensure a victory that is decisive enough to earn a mandate for her presidency and a surge of voters to help Democrats win congressional races.\", \"id\": \"allsides_1705_694_1_Hillary Clinton_14_29\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 113, \"to\": 120, \"sentence\": \"And look, I've got to tell you, I am so flattered that Donald thought I used some sort of performance enhancer,\\\" Clinton said.\", \"id\": \"allsides_1707_695_46_Clinton_113_120\"}\n{\"mention\": \"Hillary Clinton's\", \"polarity\": -1, \"from\": 286, \"to\": 303, \"sentence\": \"Conservative video-maker James O'Keefe's — best known for selectively editing undercover footage to get people fired — claimed another victim on Monday, after his Project Veritas group released the first in what he says will be a series of undercover videos revealing corruption within Hillary Clinton's campaign.\", \"id\": \"allsides_1715_698_1_Hillary Clinton_288_305\"}\n{\"mention\": \"Kennedy\", \"polarity\": 0, \"from\": 4, \"to\": 11, \"sentence\": \"Mr. Kennedy was part of a long-running battle between the State Department and the intelligence agencies over Mrs. Clinton’s emails.\", \"id\": \"allsides_1716_699_12_not Mr. Kennedy_4_11\"}\n{\"mention\": \"the State Department\", \"polarity\": 0, \"from\": 300, \"to\": 320, \"sentence\": \"In one of the newly disclosed documents, an unidentified F.B.I. employee told investigators that Mr. Kennedy, through another F.B.I. official, had sought in one case “assistance in altering the email’s classification in exchange for a ‘quid pro quo.’” The F.B.I. had deemed the email classified, but the State Department disagreed.\", \"id\": \"allsides_1716_699_15_the State Department_300_320\"}\n{\"mention\": \"Kennedy\", \"polarity\": -1, \"from\": 43, \"to\": 50, \"sentence\": \"In a letter to Mr. Kerry, they accused Mr. Kennedy, the State Department and the F.B.I. of collusion.\", \"id\": \"allsides_1716_699_29_not Mr. Kennedy_43_50\"}\n{\"mention\": \"Kennedy\", \"polarity\": 0, \"from\": 28, \"to\": 35, \"sentence\": \"The FBI official spoke with Kennedy and Kennedy raised the possibility of keeping at least one Clinton email from public disclosure by obtaining a “B9” exemption under the Freedom of Information Act, a rarely used exemption that refers to “geological and geophysical information and data.”\", \"id\": \"allsides_1717_699_11_Kennedy_28_35\"}\n{\"mention\": \"Kennedy\", \"polarity\": 0, \"from\": 119, \"to\": 126, \"sentence\": \"In the late spring or early summer of 2015, the FBI official reported to work surprised to find a note indicating that Kennedy had called.\", \"id\": \"allsides_1717_699_9_Kennedy_119_126\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 92, \"to\": 97, \"sentence\": \"Politico - Clinton 42 / Trump 28 CNN - Clinton 57 / Trump 24 YouGov - Clinton 47 / Trump 42 Trump then boasted that “the shackles have been taken off me” before attacking fellow Republicans for perceived disloyalty.\", \"id\": \"allsides_1727_704_30_BST Donald Trump_92_97\"}\n{\"mention\": \"The protest\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"The protest was organized by the Trump campaign’s Virginia state chairman, who was fired for what the deputy campaign manager, David Bossie, called “a stunt in front of the RNC without the knowledge or the approval of the Trump campaign”.\", \"id\": \"allsides_1727_704_38_protest against what they saw as the national party’s anti-Trump bias_0_11\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 170, \"to\": 175, \"sentence\": \"They could mobilize fully against him, do everything possible to deny him the nomination, sustain and support his challengers all the way to the convention, knowing that Trump would try to bring the pillars of the party down 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about an hour later, which was followed by a third tweet stating: \\\"It is so nice that the shackles have been taken off me and I can now fight for America the way I want to.\\\"\", \"id\": \"allsides_1731_705_3_Paul Ryan_61_70\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 104, \"to\": 107, \"sentence\": \"Story Continued Below \\\"Our very weak and ineffective leader, Paul Ryan, had a bad conference call where his members went wild at his disloyalty,\\\" Trump wrote in a subsequent post about an hour later, which was followed by a third tweet stating: \\\"It is so nice that the shackles have been taken off me and I can now fight for America the way I want to.\\\"\", \"id\": \"allsides_1731_705_3_Ryan (R-Wis.)_104_107\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 81, \"to\": 88, \"sentence\": \"Still, he battled his way to a strong performance in the rest of the debate, and Clinton spent much time on the defensive as the focus shifted to her record.\", \"id\": 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Donald Trump_44_49\"}\n{\"mention\": \"Kaine\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Kaine was admittedly overexcited and his constant interrupting of Pence in the first 20 minutes rubbed everyone, on the left and right, the wrong way.\", \"id\": \"allsides_1749_712_4_Tim Kaine of Virginia_0_5\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 11, \"to\": 16, \"sentence\": \"Meanwhile, Pence exuded the preternatural calm of a sociopath, increasingly frustrating Kaine with his ability to endlessly lie — about easily checked facts — with a disturbingly practiced assurance.\", \"id\": \"allsides_1749_712_5_Pence_11_16\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 6, \"to\": 11, \"sentence\": \"While Pence was the living embodiment of an unflappable liar — definitely the guy to go to if you need someone to bury the bodies — Kaine's relentlessness on this front clearly got to him enough that, for a brief, shining moment, he got flustered and angry.\", \"id\": \"allsides_1749_712_9_Pence_6_11\"}\n{\"mention\": \"House Speaker Paul Ryan (R-Wis.)\", \"polarity\": -1, \"from\": 0, \"to\": 32, \"sentence\": \"House Speaker Paul Ryan (R-Wis.) appeared on NBC’s “Today” show on Wednesday to discuss the Republican tax bill and the impact it will have on workers, leading host Savannah Guthrie to ask him if he was “living in a fantasy world.”\", \"id\": \"allsides_174_71_1_Paul Ryan_0_34\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 64, \"to\": 67, \"sentence\": \"It was a wise choice by Pence, who commanded the debate through his calm re-directing of it back to serious issues.\", \"id\": \"allsides_1750_712_11_Slays Kaine_64_67\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 24, \"to\": 29, \"sentence\": \"It was a wise choice by Pence, who commanded the debate through his calm re-directing of it back to serious issues.\", \"id\": \"allsides_1750_712_11_Mike Pence_24_29\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 145, \"to\": 152, \"sentence\": \"That Reaganesque rejoinder from Mike Pence — one of many — effectively put Tim Kaine in his place during a debate that exposed the depths of the Hillary campaign’s demagogic cheapness.\", \"id\": \"allsides_1750_712_2_Hillary_145_152\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 71, \"to\": 76, \"sentence\": \"Kaine’s labored lines and sweaty lunges contrasted embarrassingly with Pence’s smooth and substantive debate performance.\", \"id\": \"allsides_1750_712_4_Mike Pence_71_76\"}\n{\"mention\": \"Kaine\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Kaine’s labored lines and sweaty lunges contrasted embarrassingly with Pence’s smooth and substantive debate performance.\", \"id\": \"allsides_1750_712_4_Kaine_0_5\"}\n{\"mention\": \"Kaine\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Kaine puts it even more starkly than Clinton.\", \"id\": \"allsides_1754_714_106_Kaine_0_5\"}\n{\"mention\": \"Kaine\", 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Giuliani defended Mr. Trump’s tax moves by boasting that the billionaire businessman was an “absolute genius.”\", \"id\": \"allsides_1761_717_4_Mr. Trump_51_60\"}\n{\"mention\": \"the billionaire businessman was an “absolute genius\", \"polarity\": 1, \"from\": 90, \"to\": 141, \"sentence\": \"Former New York Mayor Rudolph W. Giuliani defended Mr. Trump’s tax moves by boasting that the billionaire businessman was an “absolute genius.”\", \"id\": \"allsides_1761_717_4_the billionaire businessman was an “absolute genius_90_141\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 25, \"to\": 34, \"sentence\": \"However, he has endorsed Mr. Trump’s proposals to cut taxes and reduce federal regulations, and he has criticized Mrs. Clinton’s tax plan for increasing a variety of taxes.\", \"id\": \"allsides_1761_717_69_Mr. Trump_25_34\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 117, \"to\": 124, \"sentence\": \"The wolf was replaced Monday night by a kinder, gentler Trump, a lovable lamb — now that the target in the debate is Hillary.\", \"id\": \"allsides_1763_718_40_Hillary Clinton_117_124\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 191, \"to\": 206, \"sentence\": \"On January 27, 1998, she told NBC News that there was a “vast right-wing conspiracy” out to get her husband — one that included this august publication, The American Spectator It was classic Hillary Clinton.\", \"id\": \"allsides_1763_718_60_Hillary Clinton_191_206\"}\n{\"mention\": \"It\", \"polarity\": -1, \"from\": 176, \"to\": 178, \"sentence\": \"On January 27, 1998, she told NBC News that there was a “vast right-wing conspiracy” out to get her husband — one that included this august publication, The American Spectator It was classic Hillary Clinton.\", \"id\": \"allsides_1763_718_60_It_176_178\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 49, \"to\": 51, \"sentence\": \"Rather than excoriating his debate opponent — as he did freely, wantonly, brutally, to the likes of Ted Cruz and Marco Rubio — Trump this time chose not to jump into the gutter.\", \"id\": \"allsides_1763_718_6_Donald Trump_49_51\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 52, \"to\": 61, \"sentence\": \"But when asked if he had ever cheated on his wives, Mr. Trump said: “No — I never discuss it.\", \"id\": \"allsides_1764_718_20_Donald Trump_52_61\"}\n{\"mention\": \"it\", \"polarity\": -1, \"from\": 90, \"to\": 92, \"sentence\": \"But when asked if he had ever cheated on his wives, Mr. Trump said: “No — I never discuss it.\", \"id\": \"allsides_1764_718_20_it_90_92\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump’s sharply negative attacks on the Clintons, and on Ms. Machado, pose a significant political risk to his own appeal: Two-thirds of voters already see him unfavorably, according to polls, and he is struggling to win over female voters — including white women, a majority of whom have historically supported the Republican candidate in presidential elections.\", \"id\": \"allsides_1764_718_30_Donald Trump_0_9\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 56, \"to\": 65, \"sentence\": \"The Clinton campaign is running a new attack ad against Mr. Trump featuring his insults of women over the years and has aggressively defended Ms. Machado; Mrs. Clinton called her on Friday to offer thanks “for all she had done and the courage she has shown, particularly as this became elevated through a war of some pretty unpleasant words,” according to Nick Merrill, a campaign spokesman.\", \"id\": \"allsides_1764_718_31_Trump_56_65\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 155, \"to\": 167, \"sentence\": \"The Clinton campaign is running a new attack ad against Mr. Trump featuring his insults of women over the years and has aggressively defended Ms. Machado; Mrs. Clinton called her on Friday to offer thanks “for all she had done and the courage she has shown, particularly as this became elevated through a war of some pretty unpleasant words,” according to Nick Merrill, a campaign spokesman.\", \"id\": \"allsides_1764_718_31_Hillary Clinton_155_167\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 56, \"to\": 65, \"sentence\": \"The Clinton campaign is running a new attack ad against Mr. Trump featuring his insults of women over the years and has aggressively defended Ms. Machado; Mrs. Clinton called her on Friday to offer thanks “for all she had done and the courage she has shown, particularly as this became elevated through a war of some pretty unpleasant words,” according to Nick Merrill, a campaign spokesman.\", \"id\": \"allsides_1764_718_31_Donald Trump_56_65\"}\n{\"mention\": \"Ms. Machado\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"Ms. Machado was being paid to look perfect, and when she couldn’t -- or wouldn’t -- live up to the standard she had asked to be measured by, she caught criticism.\", \"id\": \"allsides_1765_719_40_Alicia Machado_0_11\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton's campaign jumped on Trump's Machado tweets later Friday morning, eager for yet another chance to highlight his tendency to fling derogatory remarks at women.\", \"id\": \"allsides_1766_719_23_Alicia Machado_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 143, \"to\": 148, \"sentence\": \"\\\"There's been a lot of talk about sex tapes today and in a strange turn of events only one adult film has emerged today and its star is Donald Trump,\\\" Clinton spokesman Nick Merrill told her traveling press.\", \"id\": \"allsides_1766_719_37_Trump_143_148\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 130, \"to\": 135, \"sentence\": \"The former pageant winner told Cosmopolitan Magazine this week that she became a citizen last August specifically to vote against Trump, well after Clinton's 2013 departure from the State Department.\", \"id\": \"allsides_1766_719_61_Trump_130_135\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 45, \"to\": 50, \"sentence\": \"One of the main talking points has been that Trump was a “gentleman” for not bringing up Bill Clinton’s infidelities and hasn’t gotten the credit he deserved.\", \"id\": \"allsides_1766_719_72_Trump_45_50\"}\n{\"mention\": \"Bill Clinton’s\", \"polarity\": -1, \"from\": 89, \"to\": 103, \"sentence\": \"One of the main talking points has been that Trump was a “gentleman” for not bringing up Bill Clinton’s infidelities and hasn’t gotten the credit he deserved.\", \"id\": \"allsides_1766_719_72_Bill Clinton’s_89_103\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 53, \"to\": 60, \"sentence\": \"Trump struggled to defend himself against attacks by Clinton over his denigration of women, insensitivity on race relations and an assertion that he avoided paying federal taxes for years.\", \"id\": \"allsides_1771_722_13_Hillary Clinton_53_60\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump struggled to defend himself against attacks by Clinton over his denigration of women, insensitivity on race relations and an assertion that he avoided paying federal taxes for years.\", \"id\": \"allsides_1771_722_13_Trump_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 256, \"to\": 261, \"sentence\": \"On the monitor tracking the voters’ reactions to the candidates, which was visible to the handful of reporters observing the group, even those leaning toward the Republican nominee disapproved of his windy response when Clinton ticked off possible reasons Trump may not want to disclose his tax returns.\", \"id\": \"allsides_1771_722_16_Trump_256_261\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 8, \"to\": 13, \"sentence\": \"“Donald Trump just got nuked,” he said.\", \"id\": \"allsides_1771_722_18_Trump_8_13\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 31, \"to\": 33, \"sentence\": \"“Donald Trump just got nuked,” he said.\", \"id\": \"allsides_1771_722_18_The freewheeling Republican nominee_31_33\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 97, \"to\": 109, \"sentence\": \"Members of Philadelphia focus group cite Clinton’s ‘informed’ and ‘strong’ showing over ‘sloppy’ Donald Trump but remain unenthusiastic about choices Lauren Gambino in Philadelphia Tue 27 Sep 2016 12.32 BST Last modified on Fri 14 Jul 2017 19.39 BST In a clash between the two most unpopular presidential nominees in modern history, a group of undecided voters in the battleground state of Pennsylvania declared Hillary Clinton the clear winner; but remained deeply pessimistic about their choices in November.\", \"id\": \"allsides_1771_722_1_Trump_99_111\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 3, \"to\": 6, \"sentence\": \"As she spoke, many of the voters in the room agreed with her, especially among those already leaning towards her.\", \"id\": \"allsides_1771_722_24_Hillary Clinton_3_6\"}\n{\"mention\": \"—Clinton Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 16, \"sentence\": \"—Clinton Clinton exaggerates here.\", \"id\": \"allsides_1774_723_21_Hillary Clinton_0_16\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton is subtly adjusting her words here when confronted with a question about her consistency on policy positions.\", \"id\": \"allsides_1774_723_70_Hillary Clinton_0_7\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He asks no similar questions about Clinton’s record, leaving Trump himself to bring up such Clinton hits as “superpredator.”\", \"id\": \"allsides_1775_723_16_Lester Holt_0_2\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 52, \"to\": 59, \"sentence\": \"Trump counters, again, with examples of racism from Clinton’s 2008 campaign.\", \"id\": \"allsides_1775_723_20_Democratic presidential nominee Hillary Clinton_52_59\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 22, \"to\": 29, \"sentence\": \"PolitiFact notes that Clinton did, indeed, flip-flop on the deal: > LIVE FACT-CHECK: Trump is right, Clinton flip-flopped on TPP https://t.co/howNkUisAE pic.twitter.com/V70SDG3MAY > — PolitiFact Live (@politifactlive) September 27, 2016 Was that necessary, though?\", \"id\": \"allsides_1775_723_49_Democratic presidential nominee Hillary Clinton_22_29\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 22, \"to\": 29, \"sentence\": \"The whopper came from Clinton, who suggested that the U.S. does not yet have “equal pay for equal work,” something that has been a matter of law for decades.\", \"id\": \"allsides_1775_723_64_Clinton_22_29\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 34, \"to\": 41, \"sentence\": \"For months, evidence mounted that Clinton had lied.\", \"id\": \"allsides_1775_723_78_Clinton_35_42\"}\n{\"mention\": \"Mook\", \"polarity\": 0, \"from\": 68, \"to\": 72, \"sentence\": \"\\\"So we're saying this is a special circumstance, a special debate,\\\" Mook added.\", \"id\": \"allsides_1776_724_18_Clinton campaign manager Robby Mook_68_72\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 68, \"to\": 73, \"sentence\": \"\\\"It's unfair to ask for Hillary both to play traffic cop while with Trump, make sure that his lies are corrected, and also to present her vision for what she wants to do for the American people,\\\" Mook said.\", \"id\": \"allsides_1776_724_5_Trump_68_73\"}\n{\"mention\": \"Hillary\", \"polarity\": 1, \"from\": 24, \"to\": 31, \"sentence\": \"\\\"It's unfair to ask for Hillary both to play traffic cop while with Trump, make sure that his lies are corrected, and also to present her vision for what she wants to do for the American people,\\\" Mook said.\", \"id\": \"allsides_1776_724_5_Hillary Clinton's_24_31\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 36, \"to\": 43, \"sentence\": \"—Instant polls 60-70% likely to say Clinton wins.\", \"id\": \"allsides_1778_724_28_Clinton_36_43\"}\n{\"mention\": \"(Obligatory parenthetical: Yes, Clinton lies too\", \"polarity\": -1, \"from\": 0, \"to\": 48, \"sentence\": \"(Obligatory parenthetical: Yes, Clinton lies too.\", \"id\": \"allsides_1778_724_55_(Obligatory parenthetical: Yes, Clinton lies too_0_48\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 32, \"to\": 39, \"sentence\": \"(Obligatory parenthetical: Yes, Clinton lies too.\", \"id\": \"allsides_1778_724_55_Clinton_32_39\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 4, \"to\": 9, \"sentence\": \"Mr. Trump can get bored with both debate preparations and debates themselves.\", \"id\": \"allsides_1780_725_32_Mr. Trump_4_9\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 49, \"to\": 54, \"sentence\": \"Her aim is to look steady and attentive when Mr. Trump is speaking, and to avoid visibly or audibly reacting to him too much.\", \"id\": \"allsides_1780_725_40_Mr. Trump_49_54\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 41, \"to\": 50, \"sentence\": \"Mrs. Clinton has concluded that catching Mr. Trump in a lie during the debate is not enough to beat him: She needs the huge television audience to see him as temperamentally unfit for the presidency, and that she has the power to unhinge him.\", \"id\": \"allsides_1780_725_7_Donald J. Trump’s_41_50\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 277, \"to\": 289, \"sentence\": \"Given what must be the top two issues up for discussion: crime (and the subsidiary conversation about law enforcement) and terrorism, both of which should be among Trump’s few strong suits, the debate represents an unlikely opportunity for The Donald to go on offense, to show Mrs. Clinton for what she is: an elitist who is wildly out of touch with the concerns of ordinary Americans.\", \"id\": \"allsides_1781_725_20_Hillary Clinton_277_289\"}\n{\"mention\": \"Police Chief Kerr Putney\", \"polarity\": -1, \"from\": 0, \"to\": 24, \"sentence\": \"Police Chief Kerr Putney added to that anger at a news conference on Thursday when he said that the video did not give him “absolute, definitive, visual evidence that would confirm that a person is pointing a gun,” though he insisted that there was evidence to suggest that the police account of the event was correct.\", \"id\": \"allsides_1784_727_8_Police Chief Kerr Putney_0_24\"}\n{\"mention\": \"the video\", \"polarity\": -1, \"from\": 96, \"to\": 105, \"sentence\": \"Police Chief Kerr Putney added to that anger at a news conference on Thursday when he said that the video did not give him “absolute, definitive, visual evidence that would confirm that a person is pointing a gun,” though he insisted that there was evidence to suggest that the police account of the event was correct.\", \"id\": \"allsides_1784_727_8_the video_96_105\"}\n{\"mention\": \"Charlotte\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Charlotte-Mecklenburg police have resisted the calls to release dashcam and body camera footage of the death of 43-year-old Keith Lamont Scott earlier this week.\", \"id\": \"allsides_1786_727_8_Charlotte_0_9\"}\n{\"mention\": \"Rahami\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Rahami's wife is thought to be a Pakistani national.\", \"id\": \"allsides_1791_730_31_Rahami_0_6\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He viewed the teenage Mr. Rahami as the prototypical immigrant, teetering between two worlds.\", \"id\": \"allsides_1792_730_48_Mr. Rahami_0_2\"}\n{\"mention\": \"Mr. Rahami\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Mr. Rahami handled the register.\", \"id\": \"allsides_1792_730_59_Mr. Rahami_0_10\"}\n{\"mention\": \"Mr. Rahami\", \"polarity\": -1, \"from\": 12, \"to\": 22, \"sentence\": \"By sundown, Mr. Rahami had been charged with seven counts, including five counts of attempted murder of a law enforcement officer, with bail set at $5.2 million.\", \"id\": \"allsides_1794_731_71_Mr. Rahami_12_22\"}\n{\"mention\": \"Rahami\", \"polarity\": -1, \"from\": 26, \"to\": 32, \"sentence\": \"(New Jersey State Police) Rahami was charged late Monday in Union County with five counts of attempted murder of a police officer.\", \"id\": \"allsides_1795_731_14_Ahmad Khan Rahami_26_32\"}\n{\"mention\": \"Monday\", \"polarity\": 0, \"from\": 50, \"to\": 56, \"sentence\": \"(New Jersey State Police) Rahami was charged late Monday in Union County with five counts of attempted murder of a police officer.\", \"id\": \"allsides_1795_731_14_Monday_50_56\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 152, \"to\": 159, \"sentence\": \"Blake Hounshell doing his thing pic.twitter.com/1EztksmdmT — Stephen Miller (@redsteeze) September 18, 2016 UPDATE 12:09 AM EST, Sunday, September 18th Hillary briefs the press but what strikes me is how she can barely keep her eyes open.\", \"id\": \"allsides_1796_732_34_Hillary Clinton herself_152_159\"}\n{\"mention\": \"Blake Hounshell\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Blake Hounshell doing his thing pic.twitter.com/1EztksmdmT — Stephen Miller (@redsteeze) September 18, 2016 UPDATE 12:09 AM EST, Sunday, September 18th Hillary briefs the press but what strikes me is how she can barely keep her eyes open.\", \"id\": \"allsides_1796_732_34_Blake Hounshell_0_15\"}\n{\"mention\": \"CNN\", \"polarity\": 0, \"from\": 194, \"to\": 197, \"sentence\": \"Two days earlier, Trump had tweeted a response to Jay-Z after the rapper and mogul criticized the president in part for characterizing Haiti and African nations as \\\"shithole countries\\\" during a CNN interview.\", \"id\": \"allsides_17_6_22_CNN_194_197\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 27, \"to\": 30, \"sentence\": \"But Jay-Z was way ahead of him, telling CNN that the black unemployment rate doesn't make up for the president's divisive rhetoric.\", \"id\": \"allsides_17_6_24_President Barack Obama_27_30\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 19, \"to\": 24, \"sentence\": \"In a head-to-head, Trump leads by 4 points.….\", \"id\": \"allsides_1804_735_36_Donald Trump_19_24\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 7, \"to\": 12, \"sentence\": \"Donald Trump is surging in new battleground and national polls at a time when Hillary Clinton faces tough questions not only about her health but her sweeping criticism of her Republican opponent’s supporters.\", \"id\": \"allsides_1806_735_1_Trump_9_14\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 78, \"to\": 93, \"sentence\": \"Donald Trump is surging in new battleground and national polls at a time when Hillary Clinton faces tough questions not only about her health but her sweeping criticism of her Republican opponent’s supporters.\", \"id\": \"allsides_1806_735_1_Hillary Clinton_80_95\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He takes us for idiots,\\\" Powell, who is black, said in the email.\", \"id\": \"allsides_1808_737_14_Donald Trump_1_3\"}\n{\"mention\": \"Powell\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Powell also derided former Fox News CEO Roger Ailes, who advises Trump, saying the sex scandal-plagued executive would hurt Trump's chances among women voters.\", \"id\": \"allsides_1810_737_11_Powell_0_6\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 15, \"to\": 22, \"sentence\": \"“I didn't tell Hillary to have a private server at home, connected to the Clinton Foundation, two contractors, took away 60,000 emails, had her own domain,” Powell said in one Feb. 4 email to former Reagan White House chief of staff Kenneth Duberstein, in the latest cache of hacked communications among top Washington insiders to emerge in the heat of this year’s presidential campaign.\", \"id\": \"allsides_1812_738_2_Hillary_15_22\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 22, \"to\": 27, \"sentence\": \"The latest poll shows Trump winning the military vote by a landslide.\", \"id\": \"allsides_1815_739_37_Donald Trump_22_27\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 103, \"to\": 110, \"sentence\": \"The Vox website has gathered together 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\"from\": 0, \"to\": 5, \"sentence\": \"Trump spokesman Jason Miller said in a statement that Clinton had \\\"revealed her true contempt for everyday Americans\\\" and called the remarks an \\\"inexcusable mistake.\\\"\", \"id\": \"allsides_1823_742_17_Trump_0_5\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She has aggressively promoted her growing list of military endorsements from both parties.\", \"id\": \"allsides_1823_742_30_Clinton_0_3\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 8, \"to\": 15, \"sentence\": \"Hillary Clinton's declaration Friday night at a New York fundraiser that \\\"half\\\" of Donald Trump's supporters fit into a \\\"basket of deplorables\\\" seems, in its tersest formation, like a stupid comment to make.\", \"id\": \"allsides_1824_742_1_Hillary Clinton_10_17\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 119, \"to\": 126, \"sentence\": \"But he needs to do more than that — he needs to win all or 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\"id\": \"allsides_1830_745_32_Hillary Clinton_116_123\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 22, \"to\": 29, \"sentence\": \"At that time, Hillary Clinton’s lead over Trump in national polls rose to around 8 to 9 points on average, and now appears to be something more like 3 to 5 points.\", \"id\": \"allsides_1830_745_3_Hillary Clinton_22_29\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 104, \"to\": 109, \"sentence\": \"Katie ran through the basics this morning, underscoring the astonishing reversal of fortunes for Donald Trump and Hillary Clinton.\", \"id\": \"allsides_1831_745_13_Trump_104_109\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 58, \"to\": 63, \"sentence\": \"One of the key findings of the poll is that although both Trump and Clinton are dominating among their own parties' respective bases, Trump voters are more enthusiastic to turn out than hers are: Story of CNN poll showing Trump taking the lead: His voters are more enthusiastic.\", \"id\": \"allsides_1831_745_17_Trump_60_65\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton scandals taking a toll. pic.twitter.com/FA3lRy1uQt Ben Shapiro writes that unlike other \\\"good\\\" polls for Trump, in which his support remained static as Hillary's dropped, the new CNN survey actually shows him gaining.\", \"id\": \"allsides_1831_745_18_Hillary Clinton_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 113, \"to\": 118, \"sentence\": \"Clinton scandals taking a toll. pic.twitter.com/FA3lRy1uQt Ben Shapiro writes that unlike other \\\"good\\\" polls for Trump, in which his support remained static as Hillary's dropped, the new CNN survey actually shows him gaining.\", \"id\": \"allsides_1831_745_18_Trump_113_118\"}\n{\"mention\": \"Hillary Clinton's\", \"polarity\": -1, \"from\": 39, \"to\": 56, \"sentence\": \"And the relentless drip, drip, drip of Hillary Clinton's corrupt lying getting systematically exposed is really hurting her.\", \"id\": \"allsides_1831_745_23_Hillary Clinton_41_58\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 20, \"to\": 27, \"sentence\": \"Either way, perhaps Hillary's campaign might want to reconsider its recently-leaked \\\"run out the clock\\\" strategy.\", \"id\": \"allsides_1831_745_30_Hillary Clinton_21_28\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 45, \"to\": 60, \"sentence\": \"There are also some data points that suggest Hillary Clinton is on the brink of a blowout victory.\", \"id\": \"allsides_1831_745_9_Hillary Clinton_45_60\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 16, \"to\": 19, \"sentence\": \"In a statement, her campaign said it was pleased that the F.B.I. had made the documents public.\", \"id\": \"allsides_1841_750_27_Hillary Clinton Email_16_19\"}\n{\"mention\": \"Her\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"Her journalism has been recognized with several awards.\", \"id\": 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\"allsides_1851_754_19_Donald Trump's_18_20\"}\n{\"mention\": \"President Enrique Pena Nieto\", \"polarity\": 1, \"from\": 72, \"to\": 100, \"sentence\": \"Trump says on Twitter that he looks “very much forward” to meeting with President Enrique Pena Nieto.\", \"id\": \"allsides_1852_754_3_President Enrique Pena Nieto_72_100\"}\n{\"mention\": \"Donald Trump’s\", \"polarity\": -1, \"from\": 19, \"to\": 33, \"sentence\": \"DES MOINES, Iowa – Donald Trump’s experiment with “softening” his immigration policy came to a dramatic end Saturday in a fairgrounds livestock pavilion, with the Republican presidential nominee promising deportations within an hour of his inauguration.\", \"id\": \"allsides_1861_758_1_Donald Trump’s_21_35\"}\n{\"mention\": \"Iowa\", \"polarity\": 0, \"from\": 12, \"to\": 16, \"sentence\": \"DES MOINES, Iowa – Donald Trump’s experiment with “softening” his immigration policy came to a dramatic end Saturday in a fairgrounds livestock pavilion, with the Republican 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Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 34, \"sentence\": \"Democratic nominee Hillary Clinton’s powerful denunciation Thursday of “alt-right” extremism that she said GOP opponent Donald Trump embraces was cheered by adherents of the political philosophy.\", \"id\": \"allsides_1865_760_1_Hillary Clinton's_0_36\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 115, \"to\": 122, \"sentence\": \"The Daily Stormer, a neo-Nazi website that calls itself “the world’s most visited alt-right website,” also cheered Clinton’s speech.\", \"id\": \"allsides_1865_760_7_Hillary Clinton's_115_122\"}\n{\"mention\": \"Putin\", \"polarity\": -1, \"from\": 190, \"to\": 195, \"sentence\": \"How rich this is, coming from a former Secretary of State who championed the Russian “reset” and ensured, after a hefty donation to the Clinton Foundation, that a Russian firm controlled by Putin owned 20% of American uranium.\", \"id\": \"allsides_1867_760_112_Putin_190_195\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 18, \"to\": 21, \"sentence\": \"But consider what she is saying: if you speak honestly about problems in the black community, you are racist.\", \"id\": \"allsides_1867_760_27_Clinton_18_21\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 5, \"to\": 12, \"sentence\": \"What Clinton leaves out, of course, is that Trump had already denounced Duke and the KKK several times — including the day before that CNN interview.\", \"id\": \"allsides_1867_760_63_Clinton_6_13\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 44, \"to\": 49, \"sentence\": \"What Clinton leaves out, of course, is that Trump had already denounced Duke and the KKK several times — including the day before that CNN interview.\", \"id\": \"allsides_1867_760_63_Trump_45_50\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 116, \"to\": 121, \"sentence\": \"On Wednesday, the campaigns of his former rivals were quick to point this out. .@JebBush spox @kristymcampbell says Trump's shift in deportation policy is \\\"unsurprising\\\" pic.twitter.com/md073YHLxH I guess Governor Kasich's advice wasn't so bad after all?\", \"id\": \"allsides_1868_761_19_Trump_116_121\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 31, \"to\": 34, \"sentence\": \"On Wednesday, the campaigns of his former rivals were quick to point this out. .@JebBush spox @kristymcampbell says Trump's shift in deportation policy is \\\"unsurprising\\\" pic.twitter.com/md073YHLxH I guess Governor Kasich's advice wasn't so bad after all?\", \"id\": \"allsides_1868_761_19_Ted Cruz_31_34\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"On Wednesday, Trump told Hannity there would be \\\"no citizenship\\\" for those illegal immigrants.\", \"id\": \"allsides_1870_761_3_Republican presidential nominee Donald Trump_14_19\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 136, \"to\": 141, \"sentence\": \"Clinton camp: This is more about wooing Republicans and swing voters than Latinos and African Americans Team Clinton believes that this Trump campaign talk about a possible retreat on immigration -- as well as Trump’s recent appeals to African-American voters -- is aimed more at nervous Republicans and swing voters more than Latinos and African Americans.\", \"id\": \"allsides_1875_764_31_Trump_136_141\"}\n{\"mention\": \"Mr. Clinton\", \"polarity\": -1, \"from\": 87, \"to\": 98, \"sentence\": \"Indeed, as the New York Times writes, “[W]hile the move could avoid the awkwardness of Mr. Clinton jetting around the world asking for money while his wife is president, it did not resolve a more pressing question: how her administration would handle longtime donors seeking help from the United States, or whose interests might conflict with the country’s own.”\", \"id\": \"allsides_1875_764_39_Hillary Clinton_87_98\"}\n{\"mention\": \"the New York Times\", \"polarity\": 0, \"from\": 11, \"to\": 29, \"sentence\": \"Indeed, as the New York Times writes, “[W]hile the move could avoid the awkwardness of Mr. Clinton jetting around the world asking for money while his wife is president, it did not resolve a more pressing question: how her administration would handle longtime donors seeking help from the United States, or whose interests might conflict with the country’s own.”\", \"id\": \"allsides_1875_764_39_the New York Times_11_29\"}\n{\"mention\": \"Toomey\", \"polarity\": 1, \"from\": 18, \"to\": 24, \"sentence\": \"Bloomberg praised Toomey’s support of expanding background checks as his chief reason for helping him.\", \"id\": \"allsides_1878_765_21_Pat Toomey_18_24\"}\n{\"mention\": \"New York hedge fund billionaire George Soros\", \"polarity\": 1, \"from\": 15, \"to\": 59, \"sentence\": \"In July alone, New York hedge fund billionaire George Soros gave $1.5 million to Planned Parenthood’s super PAC and $35,000 to Priorities USA, both working to elect Clinton, as well as $500,000 to the Senate Majority PAC.\", \"id\": \"allsides_1878_765_9_New York hedge fund billionaire George Soros_15_59\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 48, \"to\": 50, \"sentence\": \"But this time, I actually believe that’s true,” he said, adding: “I am a Hillary Clinton fan, and I have been for quite some time.\", \"id\": \"allsides_1879_765_26_Sussman_48_50\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 81, \"to\": 88, \"sentence\": \"But this time, I actually believe that’s true,” he said, adding: “I am a Hillary Clinton fan, and I have been for quite some time.\", \"id\": \"allsides_1879_765_26_anti-Clinton_81_88\"}\n{\"mention\": \"Loewentritt\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Loewentritt also told BuzzFeed that the GSA suggested that Mueller's team issue a warrant or subpoena for the transition team materials, but the special prosecutor's office decided a letter requesting the materials would suffice.\", \"id\": \"allsides_187_77_19_GSA Deputy Counsel Lenny Loewentritt_0_11\"}\n{\"mention\": \"Lochte\", \"polarity\": -1, \"from\": 18, \"to\": 24, \"sentence\": \"Rio police indict Lochte, teammate for falsely reporting robbery\", \"id\": \"allsides_1891_770_0_Lochte_18_24\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He stopped me quickly and strongly denied that,\\\" Lauer said.\", \"id\": \"allsides_1891_770_39_Lochte_1_3\"}\n{\"mention\": \"Mr. Ailes\", \"polarity\": -1, \"from\": 104, \"to\": 113, \"sentence\": \"Before Mr. Ailes’s ouster, some of the network’s journalists and contributors privately complained that Mr. Ailes was pushing them to be more supportive of Mr. Trump.\", \"id\": \"allsides_1892_771_48_Mr. Ailes_104_113\"}\n{\"mention\": \"Mr. Bannon\", \"polarity\": -1, \"from\": 185, \"to\": 195, \"sentence\": \"The website emerged as a singular defender of Mr. Ailes, with a piece about a planned walkout by network stars loyal to him should he be forced out — it never came to pass — and one by Mr. Bannon ridiculing the “minor Murdochs” (the 21st Century Fox chief Rupert Murdoch’s sons and co-executives, James and Lachlan), who were seen as leading the push for Mr. Ailes to resign.\", \"id\": \"allsides_1892_771_51_his_185_195\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton, though, has been plastering the airwaves with ads, while taking a significant post-convention lead in a number of battleground and national polls.\", \"id\": \"allsides_1893_771_7_Clinton_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 140, \"to\": 147, \"sentence\": \"In a shift, he delivered a scripted speech to a rally audience Tuesday night in Wisconsin, appealing to minority voters in part by accusing Clinton of \\\"bigotry\\\" and saying she sees African-Americans as no more than votes to be won.\", \"id\": \"allsides_1893_771_9_Clinton_140_147\"}\n{\"mention\": \"Tuesday\", \"polarity\": 0, \"from\": 63, \"to\": 70, \"sentence\": \"In a shift, he delivered a scripted speech to a rally audience Tuesday night in Wisconsin, appealing to minority voters in part by accusing Clinton of \\\"bigotry\\\" and saying she sees African-Americans as no more than votes to be won.\", \"id\": \"allsides_1893_771_9_Tuesday_63_70\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 49, \"to\": 64, \"sentence\": \"“Incident after incident proves again and again: Hillary Clinton lacks the judgment, the temperament and the moral character to lead this nation,” he said.\", \"id\": \"allsides_1895_772_21_Clinton_49_64\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 38, \"to\": 43, \"sentence\": \"“As in several other areas of policy, Trump’s approach to foreign policy and national security seems a bit nebulous, focused on slogans rather concrete policies.”\", \"id\": \"allsides_1895_772_31_Donald Trump_38_43\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 13, \"to\": 25, \"sentence\": \"“Simply put, Donald Trump is unfit to be our commander in chief.\", \"id\": \"allsides_1895_772_33_Donald Trump_13_25\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 62, \"to\": 67, \"sentence\": \"“It all began in 2009 with what has become known as President Obama’s global ‘Apology Tour.’” Trump resurrects an old — and discredited — Republican talking point.\", \"id\": \"allsides_1896_772_26_Obama_62_67\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 55, \"to\": 60, \"sentence\": \"As we demonstrated more than five years ago, Rove took Obama’s quotes out of context and twisted their meaning in order to build a tendentious case.\", \"id\": \"allsides_1896_772_28_Obama_55_60\"}\n{\"mention\": \"Rove\", \"polarity\": -1, \"from\": 45, \"to\": 49, \"sentence\": \"As we demonstrated more than five years ago, Rove took Obama’s quotes out of context and twisted their meaning in order to build a tendentious case.\", \"id\": \"allsides_1896_772_28_Karl Rove_45_49\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 42, \"to\": 47, \"sentence\": \"In the quote cited by the Trump campaign, Obama said that intervening was “the right thing to do.”\", \"id\": \"allsides_1896_772_37_Obama_42_47\"}\n{\"mention\": \"his worst mistake\", \"polarity\": -1, \"from\": 21, \"to\": 38, \"sentence\": \"What he regretted as his worst mistake was failing to plan for “the day after.”\", \"id\": \"allsides_1896_772_38_his worst mistake_21_38\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He laid the blame for the rise of Islamic extremism on President Obama and Mrs. Clinton.\", \"id\": \"allsides_1897_773_12_Mr. Trump_0_2\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 10, \"to\": 12, \"sentence\": \"Over all, he appeared to be arguing for the kind of terrorism-centric foreign policy that President George W. Bush adopted after the Sept. 11, 2001, attacks.\", \"id\": \"allsides_1897_773_8_Donald J. Trump on Monday_10_12\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 4, \"to\": 11, \"sentence\": \"But Mueller’s team begs to differ.\", \"id\": \"allsides_189_77_7_Mueller_4_11\"}\n{\"mention\": \"\\\"Hillary Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 16, \"sentence\": \"\\\"Hillary Clinton is at the center of an international corruption scandal that reveals her use of government authority and influence for personal gain,\\\" Miller said.\", \"id\": \"allsides_1904_775_13_Hillary Clinton's_0_16\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 45, \"to\": 52, \"sentence\": \"\\\"We want to see the pay-for-play emails that Clinton’s chief of staff, Cheryl Mills, refuses to turn over,\\\" Miller continued in a statement.\", \"id\": \"allsides_1904_775_5_Hillary Clinton's_45_52\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 96, \"to\": 108, \"sentence\": \"Her primary opponent, Senator Bernie Sanders, and Mr. Trump have used those speeches to 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FBI officials recovered from Clinton’s private server.\", \"id\": \"allsides_1913_778_9_Hillary Clinton_118_125\"}\n{\"mention\": \"FBI\", \"polarity\": 0, \"from\": 89, \"to\": 92, \"sentence\": \"The emails are separate from a larger batch of several thousand work-related emails that FBI officials recovered from Clinton’s private server.\", \"id\": \"allsides_1913_778_9_FBI_89_92\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton lies more than Trump is outspoken.\", \"id\": \"allsides_1914_779_27_Clinton_0_7\"}\n{\"mention\": \"Ms. Smith and Mr. Woods\", \"polarity\": 0, \"from\": 5, \"to\": 28, \"sentence\": \"Both Ms. Smith and Mr. Woods have spoken out publicly against Mrs. Clinton during the election campaign.\", \"id\": \"allsides_1917_780_4_Patricia Smith and Charles Woods_5_28\"}\n{\"mention\": \"Smith\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Smith has been a very vocal critic of Clinton, who she says is a “liar.”\", \"id\": \"allsides_1918_780_10_Smith_0_5\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 26, \"to\": 29, \"sentence\": \"Although he didn’t accept her offer, the convention was evidence that he won’t be forgotten on the campaign trail.\", \"id\": \"allsides_1921_781_48_Ms. Stein_26_29\"}\n{\"mention\": \"Bernie Sanders\", \"polarity\": 1, \"from\": 50, \"to\": 64, \"sentence\": \"“I want to recognize the people coming out of the Bernie Sanders campaign who helped launched a revolutionary political movement,” Stein told the assembled delegates on Saturday morning during remarks by the party’s presidential candidates.\", \"id\": \"allsides_1922_781_13_Bernie Sanders_50_64\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 41, \"to\": 56, \"sentence\": \"“On the day that Bernie Sanders endorsed Hillary Clinton, the floodgates opened on our campaign,” Stein said in her acceptance speech.\", \"id\": \"allsides_1922_781_15_Hillary Clinton_41_56\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 63, \"to\": 66, \"sentence\": \"Stein also served as the party’s standard-bearer in 2012, when she received .9 percent of the national popular vote.\", \"id\": \"allsides_1922_781_3_human rights activist Ajamu Baraka_64_67\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 11, \"to\": 18, \"sentence\": \"Trump said Clinton is a \\\"dangerous liar\\\" and accused her of failing to achieve anything during her long career in public service — except, he said, avoiding criminal charges for using a private email server during her tenure as secretary of state.\", \"id\": \"allsides_1926_783_12_Clinton_11_18\"}\n{\"mention\": \"Crooked Hillary\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"Crooked Hillary said loudly, and for the world to see, that she \\\"SHORT CIRCUITED\\\" when answering a question on her e-mails.\", \"id\": \"allsides_1927_783_6_Crooked Hillary_0_15\"}\n{\"mention\": \"The Washington Post's Philip Rucker\", \"polarity\": 0, \"from\": 15, \"to\": 50, \"sentence\": \"In comments to The Washington Post's Philip Rucker on Tuesday, Trump declined to back Ryan and said nice things about Ryan's primary opponent, Paul Nehlen.\", \"id\": \"allsides_1930_784_12_The Washington Post's Philip Rucker_15_50\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 17, \"to\": 24, \"sentence\": \"Surveys indicate Clinton not only eliminating Trump's gains from his own convention, but also regaining the solid lead she held before FBI Director James Comey's criticism of her email practices depressed her support.\", \"id\": \"allsides_1936_787_22_Hillary Clinton_17_24\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 110, \"to\": 115, \"sentence\": \"Things reached the point yesterday morning that CNBC’s John Harwood tweeted: “Longtime ally of Paul Manafort, Trump's campaign manager: 'Manafort not challenging Trump anymore.\", \"id\": \"allsides_1937_787_6_Trump_110_115\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 12, \"to\": 17, \"sentence\": \"On Tuesday, Trump praised Nehlen for running “a very good campaign”.\", \"id\": \"allsides_1940_788_37_Donald Trump_12_17\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump Strikes Blow to GOP ‘Unity’ by Withholding Endorsement From House Speaker Ryan\", \"id\": \"allsides_1941_788_0_Republican presidential nominee Donald Trump_0_5\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 15, \"to\": 22, \"sentence\": \"The poll shows Clinton’s favorable rating ticking up to 43 percent, from 41 percent the week prior.\", \"id\": \"allsides_1943_789_38_Hillary Clinton's_15_22\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 26, \"to\": 33, \"sentence\": \"Patricia Smith criticized Clinton at the Republican convention, noting that she has received much different treatment than the Khan family.\", \"id\": \"allsides_1944_789_11_Clinton_26_33\"}\n{\"mention\": \"Khizr Khan\", \"polarity\": 1, \"from\": 0, \"to\": 10, \"sentence\": \"Khizr Khan blasted Trump on stage last week at the Democratic National Convention, noting that unlike his fallen son, who was killed in 2004 while guarding his base in Iraq, Trump has \\\"sacrificed nothing and no one.\\\"\", \"id\": \"allsides_1945_790_2_Khizr Khan_0_10\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 19, \"to\": 24, \"sentence\": \"Khizr Khan blasted Trump on stage last week at the Democratic National Convention, noting that unlike his fallen son, who was killed in 2004 while guarding his base in Iraq, Trump has \\\"sacrificed nothing and no one.\\\"\", \"id\": \"allsides_1945_790_2_Trump_19_24\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 9, \"to\": 11, \"sentence\": \"However, he tweeted about Khizr Khan on Monday morning.\", \"id\": \"allsides_1946_790_26_Gold Star Families Attack Trump Over Comments About Ghazala Khan_9_11\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 44, \"to\": 56, \"sentence\": \"Khizr Khan, Father Of Slain War Hero, Calls Donald Trump A 'Black Soul'\", \"id\": \"allsides_1948_791_0_Donald Trump_44_56\"}\n{\"mention\": \"Khan\", \"polarity\": 1, \"from\": 6, \"to\": 10, \"sentence\": \"Khizr Khan, Father Of Slain War Hero, Calls Donald Trump A 'Black Soul'\", \"id\": \"allsides_1948_791_0_Khan_6_10\"}\n{\"mention\": \"Khan\", \"polarity\": 1, \"from\": 6, \"to\": 10, \"sentence\": \"Khizr Khan, the father of a slain Muslim American war hero, on Sunday continued to speak out against Republican presidential nominee Donald Trump and his anti-Muslim bigotry.\", \"id\": \"allsides_1948_791_1_Khan_8_12\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 133, \"to\": 145, \"sentence\": \"Khizr Khan, the father of a slain Muslim American war hero, on Sunday continued to speak out against Republican presidential nominee Donald Trump and his anti-Muslim bigotry.\", \"id\": \"allsides_1948_791_1_Donald Trump_135_147\"}\n{\"mention\": \"Khan\", \"polarity\": 0, \"from\": 102, \"to\": 106, \"sentence\": \"Both Senate Majority Leader Mitch McConnell (R-Ky.) and House Speaker Paul Ryan (R-Wis.) responded to Khan in statements on Sunday afternoon.\", \"id\": \"allsides_1948_791_34_Khan_102_106\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 17, \"to\": 22, \"sentence\": \"Khizr Khan calls Trump's statement on fallen son 'disingenuous'\", \"id\": \"allsides_1949_791_0_Trump_17_22\"}\n{\"mention\": \"Petersen\", \"polarity\": 0, \"from\": 22, \"to\": 30, \"sentence\": \"Kennedy finally asked Petersen if he knew about an abstention doctrine (when a court refuses to hear a case because it may infringe upon the powers of another court) based on the 1971 Supreme Court case Younger v.\", \"id\": \"allsides_194_79_9_Petersen_22_30\"}\n{\"mention\": \"Smith\", \"polarity\": -1, \"from\": 14, \"to\": 19, \"sentence\": \"Another cited Smith’s speech, and the audience’s reaction (“lock her up!”), “really disturbing.”\", \"id\": \"allsides_1950_791_13_when bereaved Benghazi mother Patricia Smith_14_19\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 5, \"to\": 12, \"sentence\": \"Bill Clinton notoriously avoided the Vietnam draft — a subject that came up in his 1992 presidential campaign, as Stephanopoulos surely remembers.\", \"id\": \"allsides_1950_791_23_Hillary Clinton_5_12\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton’s actions have been reckless and have directly led to the loss of American lives.\", \"id\": \"allsides_1950_791_34_Hillary Clinton_0_7\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 46, \"to\": 61, \"sentence\": \"As Bernie Sanders said on numerous occasions, Hillary Clinton suffers from “bad judgement.”\", \"id\": \"allsides_1950_791_36_Hillary Clinton_46_61\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 158, \"to\": 164, \"sentence\": \"What’s striking about the coverage is that it barely acknowledges that this could be an open question: The New York Times headline: “Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts”: “There is simply no precedent for this: A presidential candidate publicly appealing to a foreign adversary to intervene in the election on his behalf.”\", \"id\": \"allsides_1953_793_19_Russia_158_164\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 140, \"to\": 145, \"sentence\": \"What’s striking about the coverage is that it barely acknowledges that this could be an open question: The New York Times headline: “Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts”: “There is simply no precedent for this: A presidential candidate publicly appealing to a foreign adversary to intervene in the election on his behalf.”\", \"id\": \"allsides_1953_793_19_Republican nominee Donald Trump_140_145\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 23, \"to\": 28, \"sentence\": \"The uproar over Donald Trump’s latest comments is a classic case of media-generated outrage.\", \"id\": \"allsides_1953_793_1_Republican nominee Donald Trump_25_30\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 41, \"to\": 47, \"sentence\": \"Politico’s lead: \\\"Donald Trump's call on Russia to hack Hillary Clinton's emails has shocked, flabbergasted and appalled lawmakers and national security experts across the political spectrum, with one saying it was ‘tantamount to treason.’” “Is it possible that Trump was being sarcastic?\", \"id\": \"allsides_1953_793_21_Russia_41_47\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 25, \"to\": 31, \"sentence\": \"Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts\", \"id\": \"allsides_1954_793_0_Russia_25_31\"}\n{\"mention\": \"Donald Trump’s\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts\", \"id\": \"allsides_1954_793_0_Donald Trump’s_0_14\"}\n{\"mention\": \"President Jimmy Carter\", \"polarity\": -1, \"from\": 5, \"to\": 27, \"sentence\": \"When President Jimmy Carter ran for re-election in 1980, he lost in part because he had failed to secure the freedom of 52 American hostages held in Iran.\", \"id\": \"allsides_1954_793_16_President Jimmy Carter_5_27\"}\n{\"mention\": \"the department\", \"polarity\": 0, \"from\": 87, \"to\": 101, \"sentence\": \"But she deleted a similar number of emails that she said were unrelated to her work at the department.\", \"id\": \"allsides_1954_793_8_the State Department_87_101\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 4, \"to\": 7, \"sentence\": \"But she deleted a similar number of emails that she said were unrelated to her work at the department.\", \"id\": \"allsides_1954_793_8_Hillary Clinton_4_7\"}\n{\"mention\": \"it\", \"polarity\": 0, \"from\": 172, \"to\": 174, \"sentence\": \"She quipped that “he's taken the Republican Party a long way: from ‘Morning in America’ to ‘Midnight in America.’” Trump’s megalomaniacal declaration that “I alone can fix it” was slung around his neck as Clinton framed it as fundamentally alien to the American tradition.\", \"id\": \"allsides_1955_794_10_it_172_174\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 1, \"to\": 3, \"sentence\": \"“He's forgetting every last one of us,” she said.\", \"id\": \"allsides_1955_794_11_Clinton_1_3\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton’s speech accepting the Democratic Party’s nomination was the capstone of that effort, serving as a call to unity, offering an outstretched hand to those alienated by Trump, and sketching out an optimistic vision of America’s future.\", \"id\": \"allsides_1955_794_7_Clinton_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 50, \"to\": 57, \"sentence\": \"If pundits blown away by DNC, doesn't guarantee a Clinton bounce.\", \"id\": \"allsides_1957_794_29_Hillary_50_57\"}\n{\"mention\": \"Bill Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Bill Clinton really did help Obama win.\", \"id\": \"allsides_1960_797_10_Bill Clinton_0_12\"}\n{\"mention\": \"Bill Clinton\", \"polarity\": 1, \"from\": 65, \"to\": 77, \"sentence\": \"The best jokes have at least a kernel of truth to them: Tonight, Bill Clinton strode into the spotlight once again, this time to work his magic on behalf of his wife.\", \"id\": \"allsides_1960_797_13_Clinton_65_77\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 147, \"to\": 154, \"sentence\": \"“Because this is a movement fuelled by love it can never be stopped or defeated,” said Hawaii congresswoman Tulsi Gabbard as she formally proposed Sanders for the nomination.\", \"id\": \"allsides_1962_797_33_Bernie Sanders_147_154\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 1, \"to\": 16, \"sentence\": \"“Hillary Clinton will make an outstanding president and I am proud to stand with her tonight,” Sanders said, though some in the audience still booed at Clinton’s name.\", \"id\": \"allsides_1964_799_13_Clinton_1_16\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 40, \"to\": 55, \"sentence\": \"“We’re here today because our choice is Hillary Clinton.\", \"id\": \"allsides_1964_799_21_Clinton_40_55\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 11, \"to\": 16, \"sentence\": \"She called Trump a \\\"man who inherited a fortune from his father” and cares only for himself.\", \"id\": \"allsides_1964_799_23_Trump_11_16\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 18, \"to\": 25, \"sentence\": \"But Warren called Clinton “a woman who fights for all of us.”\", \"id\": \"allsides_1964_799_27_Clinton_18_25\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 70, \"to\": 72, \"sentence\": \"I think it’s fair to say that no one is more disappointed than I am,” he told delegates.\", \"id\": \"allsides_1964_799_8_Sanders_70_72\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 105, \"to\": 112, \"sentence\": \"“Hillary Clinton will make an outstanding president, and I am proud to stand with her here tonight,” Mr. Sanders said as his supporters waved his blue campaign signs.\", \"id\": \"allsides_1966_799_15_Senator Bernie Sanders_105_112\"}\n{\"mention\": \"his supporters\", \"polarity\": 1, \"from\": 121, \"to\": 135, \"sentence\": \"“Hillary Clinton will make an outstanding president, and I am proud to stand with her here tonight,” Mr. Sanders said as his supporters waved his blue campaign signs.\", \"id\": \"allsides_1966_799_15_his supporters_121_135\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 83, \"to\": 95, \"sentence\": \"“We trusted you!” they yelled, suggesting that she had betrayed them by supporting Mrs. Clinton.\", \"id\": \"allsides_1966_799_20_Some targeted Mrs. Clinton with a taunting chant from last week_83_95\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 83, \"to\": 95, \"sentence\": \"“We trusted you!” they yelled, suggesting that she had betrayed them by supporting Mrs. Clinton.\", \"id\": \"allsides_1966_799_20_Hillary Clinton_83_95\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 127, \"to\": 139, \"sentence\": \"Some Democratic officials said the fury was an illustration of the work that still needed to be done to unify the party behind Mrs. Clinton, as well as a sign of the dedication Mr. Sanders engendered over the last year.\", \"id\": \"allsides_1966_799_39_Some targeted Mrs. Clinton with a taunting chant from last week_127_139\"}\n{\"mention\": \"Wasserman Schultz's\", \"polarity\": -1, \"from\": 13, \"to\": 32, \"sentence\": \"Even some of Wasserman Schultz's harshest critics acknowledge that part of that problem was structural: She was in elected office while also serving as the party chair.\", \"id\": \"allsides_1967_800_20_Debbie Wasserman Schultz_13_32\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She faces a primary from a Sanders-backed candidate but most political observers say she will win it.\", \"id\": \"allsides_1967_800_43_Wasserman Schultz_0_3\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 27, \"to\": 34, \"sentence\": \"She faces a primary from a Sanders-backed candidate but most political observers say she will win it.\", \"id\": \"allsides_1967_800_43_Bernie Sanders_27_34\"}\n{\"mention\": \"the DNC news\", \"polarity\": -1, \"from\": 20, \"to\": 32, \"sentence\": \"Trump tweeted after the DNC news broke: Today proves what I have always known, that @Reince Priebus is the tough one and the smart one, not Debbie Wasserman Shultz (@DWStweets.) Sanders himself blasted the DNC and Wasserman Schultz in interviews earlier Sunday, demanding her resignation as party chairwoman.\", \"id\": \"allsides_1969_800_15_Fox News_20_32\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": 1, \"from\": 60, \"to\": 77, \"sentence\": \"President Obama and Clinton both issued statements thanking Wasserman Schultz for her service.\", \"id\": \"allsides_1969_800_20_Wasserman Schultz_60_77\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": -1, \"from\": 12, \"to\": 29, \"sentence\": \"Others from Wasserman Schultz herself contained very strong language, raising questions about her status as an ostensibly neutral party official.\", \"id\": \"allsides_1969_800_27_Wasserman Schultz_12_29\"}\n{\"mention\": \"Sanders\", \"polarity\": -1, \"from\": 14, \"to\": 21, \"sentence\": \"Responding to Sanders’ complaints the party hasn’t been fair to him, she wrote to a staffer in an April email: “Spoken like someone who has never been a member of the Democratic Party and has no understanding of what we do.”\", \"id\": \"allsides_1969_800_28_Sanders'_14_21\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 143, \"to\": 146, \"sentence\": \"The announcement came just hours after reports first surfaced that Wasserman Schultz may be denied a speaking role at the convention, and that she would not be presiding -- a decision apparently made under pressure from the Clinton campaign and the White House.\", \"id\": \"allsides_1969_800_7_Vice Chairwoman Donna Brazile_143_146\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": -1, \"from\": 21, \"to\": 38, \"sentence\": \"In a statement after Wasserman Schultz’s resignation, Sanders said the DNC needs new leadership.\", \"id\": \"allsides_1972_801_27_Debbie Wasserman Schultz (Fla.) to resign_21_38\"}\n{\"mention\": \"Tim Kaine\", \"polarity\": 1, \"from\": 24, \"to\": 33, \"sentence\": \"Hillary Clinton Selects Tim Kaine, a Popular Senator From a Swing State, as Running Mate\", \"id\": \"allsides_1973_802_0_Mr. Kaine_24_33\"}\n{\"mention\": \"Tampa\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"At a rally in Tampa on Friday evening, Mrs. Clinton blasted the bleak vision of America presented by her Republican rival.\", \"id\": \"allsides_1973_802_20_Tampa_14_19\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 40, \"to\": 47, \"sentence\": \"The Trump campaign quickly labeled Mrs. Clinton’s new running mate “Corrupt Kaine,” pointing to lavish gifts he had received during his years as governor and lieutenant governor of Virginia.\", \"id\": \"allsides_1973_802_35_Clinton_40_47\"}\n{\"mention\": \"Tim Kaine\", \"polarity\": -1, \"from\": 61, \"to\": 70, \"sentence\": \"The Bernie Sanders supporters are furious with the choice of Tim Kaine, who represents the opposite of what Bernie stands for.\", \"id\": \"allsides_1974_802_1_Dem VP Pick Kaine_63_72\"}\n{\"mention\": \"Bernie\", \"polarity\": 1, \"from\": 108, \"to\": 114, \"sentence\": \"The Bernie Sanders supporters are furious with the choice of Tim Kaine, who represents the opposite of what Bernie stands for.\", \"id\": \"allsides_1974_802_1_Bernie_110_116\"}\n{\"mention\": \"Tim Kaine\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Tim Kaine is, and always has been, owned by the banks.\", \"id\": \"allsides_1974_802_3_Dem VP Pick Kaine_0_9\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"She asked, if Trump were president, “Will a woman make the same as a man and will I get to choose what I do with my body?”\", \"id\": \"allsides_1975_803_18_Ivanka Trump_14_19\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 22, \"to\": 27, \"sentence\": \"She specifically said Trump will fight to change laws in order to address these problems for working women.\", \"id\": \"allsides_1975_803_35_Ivanka Trump_22_27\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 167, \"to\": 170, \"sentence\": \"That stance is earning high praise from liberals who have been arguing for years the federal government should get involved to regulate the cost of childcare. i mean, she basically outlined Hillary Clinton's pro-working family's policy agenda... https://t.co/STm1bAK2Kg Great speech from Ivanka.\", \"id\": \"allsides_1976_803_3_Ivanka Trump's_167_170\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 35, \"to\": 38, \"sentence\": \"But then, perhaps there’s truth to his absurd promises: When the crisis is invented, the solution is simpler.\", \"id\": \"allsides_1978_804_61_Donald Trump_35_38\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 91, \"to\": 98, \"sentence\": \"“With Donald Trump and Mike Pence, America’s ready for a comeback after almost a decade of Clinton-Obama failures.”\", \"id\": \"allsides_1979_804_31_Clinton_91_98\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 1, \"from\": 6, \"to\": 18, \"sentence\": \"“With Donald Trump and Mike Pence, America’s ready for a comeback after almost a decade of Clinton-Obama failures.”\", \"id\": \"allsides_1979_804_31_Trump_6_18\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 88, \"to\": 95, \"sentence\": \"Chris Christie spoke on the second night of the convention, he ticked off criticisms of Clinton, asking the crowd of she was “guilty or not guilty.”\", \"id\": \"allsides_1986_807_3_Anti-Clinton_88_95\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 110, \"to\": 125, \"sentence\": \"The other striking thing from last night: While Patricia Smith, whose son was killed in Benghazi, was blaming Hillary Clinton on stage, Trump called in to Bill O’Reilly—essentially preempting his own convention for those few minutes.\", \"id\": \"allsides_1987_808_26_Hillary Clinton_110_125\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 44, \"to\": 49, \"sentence\": \"In March 2012, at a meeting in South Korea, Obama declared about Erdogan “that we find ourselves in frequent agreement upon a wide range of issues… [and] because he has two daughters that are a little older than mine — they’ve turned out very well, so I’m always interested in his perspective on raising girls.”\", \"id\": \"allsides_1991_811_10_Obama_44_49\"}\n{\"mention\": \"Erdogan\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Erdogan has pushed step-by-step create an Islamic state.\", \"id\": \"allsides_1991_811_11_Erdogan_0_7\"}\n{\"mention\": \"Erdogan\", \"polarity\": -1, \"from\": 154, \"to\": 161, \"sentence\": \"Obama entered power in 2009 hoping to use Turkey’s Islamist president to help remake politics in the Middle East — but the wished-for alliance crashed as Erdogan’s Islamist government became more radical year by year.\", \"id\": \"allsides_1991_811_6_Erdogan_154_161\"}\n{\"mention\": \"Erdogan\", \"polarity\": 0, \"from\": 71, \"to\": 78, \"sentence\": \"So, too, have street demonstrators and leading politicians — including Erdogan opponents.\", \"id\": \"allsides_1992_811_18_Erdogan_71_78\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 3, \"to\": 5, \"sentence\": \"If he is perceived as the defender of Turkish civilian government, his popularity could well soar.\", \"id\": \"allsides_1992_811_22_Erdogan_3_5\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 0, \"from\": 16, \"to\": 28, \"sentence\": \"Just into @CNN: Donald Trump has called Indiana Gov.\", \"id\": \"allsides_1998_814_12_Donald Trump_16_28\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 23, \"to\": 26, \"sentence\": \"Mike Pence and offered him the vice-presidential slot on his ticket.\", \"id\": \"allsides_1998_814_13_Donald Trump_23_26\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 113, \"to\": 118, \"sentence\": \"Patricia Murphy wrote, “In addition to testing the men's chemistry together, Trump was reportedly impressed with Pence's calm demeanor, his experience on Capitol Hill and as a governor, and Pence's potential to assist Trump in governing, should the ticket win in November.”\", \"id\": \"allsides_1998_814_20_Mike Pence_113_118\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 69, \"to\": 72, \"sentence\": \"Director James Comey's damning report on Clinton's email usage while she was secretary of state also didn't do her any favors.\", \"id\": \"allsides_1998_814_39_Hillary_69_72\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Pence, who twice considered running for president, is well regarded by conservatives and evangelicals around the country, earning plaudits recently from the likes of Sen.\", \"id\": \"allsides_1999_814_10_Mike Pence_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 7, \"to\": 12, \"sentence\": \"Before Trump even made his pick, he had at least one detractor in prominent conservative radio host and former Red State editor Erick Erickson, who chided Pence on Twitter.\", \"id\": \"allsides_1999_814_32_Donald Trump_7_12\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 155, \"to\": 160, \"sentence\": \"Before Trump even made his pick, he had at least one detractor in prominent conservative radio host and former Red State editor Erick Erickson, who chided Pence on Twitter.\", \"id\": \"allsides_1999_814_32_Mike Pence_155_160\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 1, \"to\": 4, \"sentence\": \"“She may have got out over her skis a little bit and more forthright and political than she should have been.\", \"id\": \"allsides_2002_816_27_Chris Murphy, D-Conn_1_4\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump’s hands, of course, are far from clean on the matter of judicial independence.\", \"id\": \"allsides_2003_816_18_Donald Trump_0_9\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 122, \"to\": 134, \"sentence\": \"In an interview with The Times published Sunday, Justice Ginsburg said, “I can’t imagine what the country would be — with Donald Trump as our president,” joking that if her husband were alive, he might have said, “It’s time for us to move to New Zealand.”\", \"id\": \"allsides_2003_816_3_Donald Trump_122_134\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 11, \"to\": 18, \"sentence\": \"He praised Clinton’s proposal in strong, unambiguous terms ― describing it as “an extremely important initiative” and predicting that “it will save lives, it will ease suffering, it will improve health care in America, and it will cut health care costs.”\", \"id\": \"allsides_2007_818_12_Clinton_11_18\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He praised Clinton’s proposal in strong, unambiguous terms ― describing it as “an extremely important initiative” and predicting that “it will save lives, it will ease suffering, it will improve health care in America, and it will cut health care costs.”\", \"id\": \"allsides_2007_818_12_Sanders_0_2\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Sanders told reporters that the two campaigns “are coming closer and closer together in trying to address the major issues facing this country.”\", \"id\": \"allsides_2008_818_19_Sanders_0_7\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 55, \"to\": 70, \"sentence\": \"(AP) — In another nod to primary rival Bernie Sanders, Hillary Clinton is proposing to increase federal money for community health centers and outlining steps to expand access to health care across the nation.\", \"id\": \"allsides_2008_818_2_Hillary Clinton_55_70\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 118, \"to\": 133, \"sentence\": \"He repeated the statements during a Wednesday morning press conference saying, “I think the DNI, Clapper, should deny Hillary Clinton access to classified information during this campaign, given how she so recklessly handled classified information.\", \"id\": \"allsides_2015_821_3_Hillary_118_133\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 17, \"to\": 24, \"sentence\": \"Comey criticized Clinton and her staff for being “extremely careless” in handling classified information, noting that 110 of Clinton’s emails contained classified information at the time they were sent and received.\", \"id\": \"allsides_2017_821_3_presumptive Democratic nominee Hillary Clinton_17_24\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 27, \"to\": 42, \"sentence\": \"Read more: Why the FBI Let Hillary Clinton Off the Hook Ryan also sent a letter to Comey, requesting that he release all of the findings from the bureau’s investigation into Clinton’s emails, saying “there are simply too many unanswered questions.”\", \"id\": \"allsides_2017_821_8_Hillary Clinton_27_42\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 13, \"to\": 20, \"sentence\": \"FBI’s Comey: Clinton 'extremely careless' about emails, but bureau will not advise criminal charges\", \"id\": \"allsides_2020_823_0_Clinton_13_20\"}\n{\"mention\": \"Comey\", \"polarity\": 0, \"from\": 288, \"to\": 293, \"sentence\": \"“There is evidence to support a conclusion that any reasonable person in Secretary Clinton’s position, or in the position of those government employees with whom she was corresponding about these matters, should have known that an unclassified system was no place for that conversation,” Comey said.\", \"id\": \"allsides_2020_823_23_FBI Director James Comey_288_293\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 139, \"to\": 142, \"sentence\": \"In the wake of that report, Trump, the presumptive Republican presidential nominee, stepped up his criticism of her email actions and said she belongs in “jail.”\", \"id\": \"allsides_2020_823_27_Clinton_139_142\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 56, \"to\": 63, \"sentence\": \"\\\"Although we did not find clear evidence that Secretary Clinton or her colleagues intended to violate laws governing the handling of classified information, there is information that they were extremely careless in their handling of very sensitive, highly classified information,\\\" Comey told reporters in Washington, D.C., noting that the probe has found that the former secretary of state used several different email servers and numerous devices during her time in office.\", \"id\": \"allsides_2021_823_2_Clinton_56_63\"}\n{\"mention\": \"Comey\", \"polarity\": 0, \"from\": 31, \"to\": 36, \"sentence\": \"Story Continued Below Even so, Comey added later, “Although there is evidence of potential violations of the statutes regarding the handling of classified information, our judgment is that no reasonable prosecutor would bring such a case.\", \"id\": \"allsides_2021_823_3_Bernie Sanders’_31_36\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 146, \"to\": 153, \"sentence\": \"Longtime Obama aide and strategist David Axelrod on Tuesday morning tweeted that Comey’s statement in which he recommended no charges but rebuked Clinton for carelessness “is about [the] best result she could get.”\", \"id\": \"allsides_2021_823_74_Clinton_146_153\"}\n{\"mention\": \"Ernst\", \"polarity\": 0, \"from\": 73, \"to\": 78, \"sentence\": \"Trump spent time with Pence and his family on Sunday and was due to meet Ernst in New Jersey on Monday.\", \"id\": \"allsides_2024_824_3_Ernst_73_78\"}\n{\"mention\": \"Pence\", \"polarity\": 0, \"from\": 140, \"to\": 145, \"sentence\": \"Cotton, 39 and thought by some a likely post-Trump presidential candidate in 2020, has not been as often named among potential Trump VPs as Pence and Ernst.\", \"id\": \"allsides_2024_824_6_Pence_140_145\"}\n{\"mention\": \"Lincoln\", \"polarity\": 1, \"from\": 44, \"to\": 51, \"sentence\": \"It is remarkable that there was a time when Lincoln’s idea, now so central to our American mindset, was not dominant.\", \"id\": \"allsides_2025_825_21_Abraham Lincoln_44_51\"}\n{\"mention\": \"the Founders\", \"polarity\": 1, \"from\": 16, \"to\": 28, \"sentence\": \"We must do what the Founders did, and what Lincoln did in his own time, and fight against the insidious notion that those words mean other than what they say.\", \"id\": \"allsides_2025_825_32_the Founders_16_28\"}\n{\"mention\": \"Lincoln\", \"polarity\": 1, \"from\": 43, \"to\": 50, \"sentence\": \"We must do what the Founders did, and what Lincoln did in his own time, and fight against the insidious notion that those words mean other than what they say.\", \"id\": \"allsides_2025_825_32_Abraham Lincoln_43_50\"}\n{\"mention\": \"Lincoln\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Lincoln meant this literally.\", \"id\": \"allsides_2025_825_4_Abraham Lincoln_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 27, \"to\": 32, \"sentence\": \"\\\"What is distasteful about Trump is not that he offends old-fashioned American values,\\\" wrote Mother Jones’s Tim Murphy in one typical reaction.\", \"id\": \"allsides_2026_825_3_Donald Trump_27_32\"}\n{\"mention\": \"\\\"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"\\\"Trump is distasteful because he taps into certain old-fashioned American values — nativism, brash tough talk, slow-burning authoritarianism; family dynasties — that have played a not-inconsequential role throughout our history.\\\"\", \"id\": \"allsides_2026_825_4_Donald Trump_0_6\"}\n{\"mention\": \"\\\" Becker\", \"polarity\": 0, \"from\": 193, \"to\": 201, \"sentence\": \"\\\"It taught that beneath all local and temporary diversity, beneath the superficial traits and talents that distinguish men and nations, all men are equal in the possession of a common humanity,\\\" Becker says.\", \"id\": \"allsides_2026_825_55_Carl Becker_193_201\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 24, \"to\": 27, \"sentence\": \"\\\"It was unfortunate and she has admitted that the optics were not good in 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Johnson_105_112\"}\n{\"mention\": \"Boris\", \"polarity\": -1, \"from\": 150, \"to\": 155, \"sentence\": \"Main public face of Brexit makes shock announcement hours after his key ally Michael Gove launched his own campaign Live coverage of the fallout from Boris Johnson’s announcement Heather Stewart and  Jessica Elgot Thu 30 Jun 2016 13.20 BST First published on Thu 30 Jun 2016 12.02 BST Boris Johnson has unexpectedly ruled himself out as a candidate for Britain’s next prime minister, after the justice secretary, Michael Gove, sent shockwaves through Westminster with a last-minute bid for the Conservative leadership.\", \"id\": \"allsides_2037_829_1_Boris_152_157\"}\n{\"mention\": \"Farage\", \"polarity\": -1, \"from\": 54, \"to\": 60, \"sentence\": \"Speaking to the host of ITV's \\\"Good Morning Britain,\\\" Farage called one of the \\\"leave\\\" campaign's biggest promises a \\\"mistake,\\\" though he distanced himself from the decision to make the promise in the first place.\", \"id\": \"allsides_2043_832_8_Nigel Farage_54_60\"}\n{\"mention\": \"Britain\", \"polarity\": 0, \"from\": 44, \"to\": 51, \"sentence\": \"Speaking to the host of ITV's \\\"Good Morning Britain,\\\" Farage called one of the \\\"leave\\\" campaign's biggest promises a \\\"mistake,\\\" though he distanced himself from the decision to make the promise in the first place.\", \"id\": \"allsides_2043_832_8_Britain_44_51\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 31, \"to\": 36, \"sentence\": \"Clinton Opens 12-Point Lead on Trump as Two-Thirds See Him as Biased (POLL)\", \"id\": \"allsides_2045_833_0_Trump_31_36\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton, further, is now leading among young adults, a group in which Trump was surprisingly competitive last month.\", \"id\": \"allsides_2045_833_59_Clinton_0_7\"}\n{\"mention\": \"presumptive Democratic presidential nominee Hillary Clinton\", \"polarity\": 1, \"from\": 17, \"to\": 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\"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He put down women based on their looks.\", \"id\": \"allsides_2152_876_26_Cameron Linton of Pittsburgh_0_2\"}\n{\"mention\": \"Presumptive Republican nominee Donald Trump\", \"polarity\": 1, \"from\": 0, \"to\": 43, \"sentence\": \"Presumptive Republican nominee Donald Trump has officially secured a majority of GOP delegates, giving him the \\\"magic number\\\" required to clinch the GOP nomination.\", \"id\": \"allsides_2154_876_1_Presumptive Republican nominee Donald Trump_0_45\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": -1, \"from\": 0, \"to\": 17, \"sentence\": \"Wasserman Schultz has long been accused of favoritism by Bernie Sanders supporters, who claimed that her decision to schedule and limit Democratic debates was meant to protect Hillary Clinton.\", \"id\": \"allsides_2157_878_2_DNC chair Debbie Wasserman Schultz_0_17\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 39, \"to\": 46, \"sentence\": \"Clinton got to fill six positions, and Sanders chose five.\", \"id\": \"allsides_2159_878_13_Sanders_39_46\"}\n{\"mention\": \"Macron\", \"polarity\": 1, \"from\": 87, \"to\": 93, \"sentence\": \"In an address from the Elysée Palace, shortly after the U.S. president’s announcement, Macron urged scientists who were annoyed with the move to “come to France and work with us together” on climate policy-related research.\", \"id\": \"allsides_215_87_3_Emmanuel Macron_87_93\"}\n{\"mention\": \"Macron\", \"polarity\": -1, \"from\": 182, \"to\": 188, \"sentence\": \"> Sadiq Khan Tells Everyone Who Doesn’t Like Trump: Move to London https://t.co/YcvLk0Khh0 pic.twitter.com/XgR0ypbt6B > — Breitbart London (@BreitbartLondon) November 17, 2016 While Macron’s attacks on Trump over the Paris agreement were hailed by an admiring French and international media, the Guardian reported that the French leader’s “tough stance” may have “backfired”, and likely prompted the U.S. leader to remind people he “was elected to serve the citizens of Pittsburgh — not Paris” Speaking in the Rose Garden after his announcement that the U.S. would be leaving the Paris agreement, President Trump said that the accord signed by the Obama administration in 2015 without the consent of Congress “disadvantages the United States to the exclusive benefit of other countries” “In order to fulfill my solemn duty to protect America and its citizens, the United States will withdraw from the Paris Climate Accord,” Trump said at the time, explaining the agreement would have left American taxpayers having to “absorb the cost in terms of lost jobs, lower wages, shuttered factories, and vastly diminished economic production.”\", \"id\": \"allsides_215_87_6_Emmanuel Macron_182_188\"}\n{\"mention\": \"Facebook CEO Mark Zuckerberg\", \"polarity\": 0, \"from\": 0, \"to\": 28, \"sentence\": \"Facebook CEO Mark Zuckerberg arranged a meeting with conservative figures last week to talk out the issue — a 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\"allsides_2190_890_17_Clinton_151_166\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 33, \"to\": 40, \"sentence\": \"TOUGH SLOG FOR CLINTON Allies of Clinton have held back from overt calls for Sanders to exit the race.\", \"id\": \"allsides_2190_890_7_Clinton_33_40\"}\n{\"mention\": \"her\", \"polarity\": -1, \"from\": 13, \"to\": 16, \"sentence\": \"Any moves by her campaign to try drive Sanders out could risk angering Democratic voters and end up backfiring.\", \"id\": \"allsides_2190_890_8_Clinton_13_16\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 112, \"to\": 119, \"sentence\": \"\\\"My husband, who I'm going to put in charge of revitalizing the economy, cause you know he knows how to do it,\\\" Clinton told the crowd at a campaign event in Kentucky on Sunday.\", \"id\": \"allsides_2191_891_4_Clinton_112_119\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 150, \"to\": 153, \"sentence\": \"\\\"I've told my husband he's got to come out of retirement 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\"allsides_2335_949_70_Sanders_1_8\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 31, \"to\": 36, \"sentence\": \"What’s more surprising is that Trump has repeatedly attacked Walker … ‘People are saying, 'He shouldn't be fighting the governor, the governor's popular,’ said Trump.\", \"id\": \"allsides_2335_949_87_Trump_31_36\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 65, \"to\": 68, \"sentence\": \"\\\"This is something else Americans deserve across our country...\\\" she told supporters.\", \"id\": \"allsides_2337_949_16_Democratic front-runner Hillary Clinton_65_68\"}\n{\"mention\": \"Cruz\", \"polarity\": 1, \"from\": 10, \"to\": 14, \"sentence\": \"A win for Cruz in Wisconsin would make it harder for Trump to secure the Republican nomination outright in the party's primaries by the time voting ends in June, increasing the likelihood of a contested convention.\", \"id\": \"allsides_2337_949_8_Cruz_10_14\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 1, 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\"id\": \"allsides_2407_976_159_Clinton_12_19\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 20, \"to\": 27, \"sentence\": \"But polls also show Clinton far ahead in Florida and in North Carolina, setting up the possibility of an outcome parallel to last week’s contests, when Sanders scored a narrow and surprising victory in Michigan, yet Clinton came away with a widened lead in the delegate count because of her resounding victory in Mississippi,” John Wagner and Jose A. 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Rubio gets 10 of the delegates and Kasich takes 9.\", \"id\": \"allsides_2412_978_3_Rubio_0_11\"}\n{\"mention\": \"Ted Cruz (Tex.)\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"Ted Cruz (Tex.) trailed by substantial margins.\", \"id\": \"allsides_2412_978_9_Ted Cruz (Tex.)_0_15\"}\n{\"mention\": \"Carson\", \"polarity\": 1, \"from\": 19, \"to\": 25, \"sentence\": \"The endorsement by Carson, who last week suspended his campaign for the Republican presidential nomination, is perhaps the most high-profile nod for Trump since New Jersey Gov.\", \"id\": \"allsides_2416_981_2_Ben Carson_19_25\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He’s actually a very intelligent man who cares deeply about America,\\\" Carson said.\", \"id\": \"allsides_2417_981_16_Donald Trump_0_2\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 76, \"to\": 81, \"sentence\": \"Carson also laid out his argument for the party and country to unify around Trump 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\"“President Obama’s executive action on immigration represents an unprecedented attempt to expand the power of the executive branch,” Texas Attorney General Ken Paxton said when the states filed their petition.\", \"id\": \"allsides_2574_1049_13_States_177_187\"}\n{\"mention\": \"President Obama\", \"polarity\": -1, \"from\": 1, \"to\": 16, \"sentence\": \"“President Obama’s executive action on immigration represents an unprecedented attempt to expand the power of the executive branch,” Texas Attorney General Ken Paxton said when the states filed their petition.\", \"id\": \"allsides_2574_1049_13_Obama_1_16\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 48, \"to\": 53, \"sentence\": \"The states and Republicans have argued that the Obama administration’s executive amnesty is an unconstitutional overreach of executive authority.\", \"id\": \"allsides_2574_1049_8_Obama_48_53\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 29, \"to\": 36, \"sentence\": \"For Clinton, 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\"allsides_2588_1054_5_Ted Cruz (R-TX)_3_5\"}\n{\"mention\": \"American\", \"polarity\": 1, \"from\": 41, \"to\": 49, \"sentence\": \"If he was president, he insisted that no American would be forced to drop to their knees in front of an enemy.\", \"id\": \"allsides_2588_1054_5_American_41_49\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 11, \"to\": 16, \"sentence\": \"THE MISSES Obama, though, missed the mark entirely on a $3,000 tax credit he said would make quality child care more affordable.\", \"id\": \"allsides_2600_1060_9_Obama_11_16\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": 1, \"from\": 17, \"to\": 26, \"sentence\": \"By all accounts, Mr. Obama is sympathetic to this view, which is shared by a number of counterterrorism veterans who contend that anxiety has warped the American public’s perspective.\", \"id\": \"allsides_2602_1060_6_President Obama_17_26\"}\n{\"mention\": \"Mr. Bowie\", \"polarity\": 1, \"from\": 89, \"to\": 98, \"sentence\": \"In the late 1960s, 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\"to\": 117, \"sentence\": \"Ammon Bundy and a handful of militiamen from other states arrived last month in Burns, some 60 miles from the Hammond ranch.\", \"id\": \"allsides_2622_1069_23_Hammond_110_117\"}\n{\"mention\": \"the Hammonds\", \"polarity\": 0, \"from\": 8, \"to\": 20, \"sentence\": \"Who are the Hammonds?\", \"id\": \"allsides_2623_1069_18_the Hammonds_8_20\"}\n{\"mention\": \"They\", \"polarity\": -1, \"from\": 0, \"to\": 4, \"sentence\": \"They’re going to do anything they can to make him look ridiculous and sound ridiculous.”\", \"id\": \"allsides_2624_1070_28_The terrorists_0_4\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 1, \"to\": 16, \"sentence\": \"[Hillary Clinton revises contested claims about Islamic State recruiters using Donald Trump video] Trump responded to Clinton’s assertion by calling her “a liar.”\", \"id\": \"allsides_2624_1070_37_Hillary Clinton_1_16\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 22, \"to\": 34, 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\"we\", \"polarity\": 1, \"from\": 7, \"to\": 9, \"sentence\": \"But if we act here, now, if we place our short-term interests behind the air that our children will breathe and the water our children will drink,” Obama said, “then we will not be too late for them.”\", \"id\": \"allsides_2720_1106_5_us_7_9\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 148, \"to\": 153, \"sentence\": \"But if we act here, now, if we place our short-term interests behind the air that our children will breathe and the water our children will drink,” Obama said, “then we will not be too late for them.”\", \"id\": \"allsides_2720_1106_5_Obama_148_153\"}\n{\"mention\": \"Dana Perino\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Dana Perino: My Thanksgiving do's and don'ts for talking politics around the table\", \"id\": \"allsides_2729_1110_0_Dana Perino_0_11\"}\n{\"mention\": \"Dana Perino\", \"polarity\": 1, \"from\": 25, \"to\": 36, \"sentence\": \"Editor's note: Fox News' Dana 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By SARAH WHEATON The pope's address to Congress devoted considerable time to the idea of giving people opportunities, and he praised King's campaign for equality for African-Americans, saying \\\"that dream continues to inspire us all.\\\"\", \"id\": \"allsides_2869_1171_17_Francis'_42_49\"}\n{\"mention\": \"Marco Rubio, R-Fla\", \"polarity\": 1, \"from\": 0, \"to\": 18, \"sentence\": \"Marco Rubio, R-Fla., will benefit the most from Walker's departure.\", \"id\": \"allsides_2873_1173_12_Marco Rubio, R-Fla_0_18\"}\n{\"mention\": \"Walker\", \"polarity\": 1, \"from\": 41, \"to\": 47, \"sentence\": \"Late Monday, Rubio was already welcoming Walker staff to his team, as was Sen.\", \"id\": \"allsides_2873_1173_14_Walker_41_47\"}\n{\"mention\": \"Rubio\", \"polarity\": 1, \"from\": 13, \"to\": 18, \"sentence\": \"Late Monday, Rubio was already welcoming Walker staff to his team, as was Sen.\", \"id\": \"allsides_2873_1173_14_Rubio_13_18\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 139, \"to\": 141, \"sentence\": \"Unfortunately, like Walker, on the stump Thompson was frighteningly unprepared, even making embarrassing gaffes about Jews and Israel, and he dropped out in August of 2007.\", \"id\": \"allsides_2875_1173_5_Bush_139_141\"}\n{\"mention\": \"Walker\", \"polarity\": -1, \"from\": 20, \"to\": 26, \"sentence\": \"Unfortunately, like Walker, on the stump Thompson was frighteningly unprepared, even making embarrassing gaffes about Jews and Israel, and he dropped out in August of 2007.\", \"id\": \"allsides_2875_1173_5_Scott Walker_20_26\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 9, \"to\": 11, \"sentence\": \"You know he's not even an American.\\\"\", \"id\": \"allsides_2885_1177_6_President Obama_9_11\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 63, \"to\": 68, \"sentence\": \"Trump, who was a driver of the \\\"birther\\\" movement that claimed Obama wasn't born in the U.S, first responded with feigned exasperation -- \\\"We need the question,\\\" he said, to laughs -- but let the man continue.\", \"id\": \"allsides_2885_1177_7_President Obama_63_68\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump, who was a driver of the \\\"birther\\\" movement that claimed Obama wasn't born in the U.S, first responded with feigned exasperation -- \\\"We need the question,\\\" he said, to laughs -- but let the man continue.\", \"id\": \"allsides_2885_1177_7_Trump_0_5\"}\n{\"mention\": \"Margaret Thatcher\", \"polarity\": 0, \"from\": 19, \"to\": 36, \"sentence\": \"Jeb walks back his Margaret Thatcher answer NBC’s Peter Alexander spoke exclusively to Jeb Bush after last night’s debate.\", \"id\": \"allsides_2886_1178_27_Margaret Thatcher_19_36\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 29, \"to\": 31, \"sentence\": \"Here’s one thing we noticed: He seemed to be walking back his answer that he’d put Margaret Thatcher on the $10 bill.\", \"id\": \"allsides_2886_1178_28_Jeb Bush_29_31\"}\n{\"mention\": \"Bush\", \"polarity\": 0, \"from\": 7, \"to\": 11, \"sentence\": \"Trump, Bush, Fiorina: Three questions, three answers at second GOP debate\", \"id\": \"allsides_2887_1178_0_Jeb Bush_7_11\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 30, \"to\": 32, \"sentence\": \"Two moments to remember: when he stood up to Trump and stood up for his brother (“he kept us safe”); at the end of the debate, when he chose “Eveready” as his Secret Service name (“it’s very high energy, Donald”).\", \"id\": \"allsides_2887_1178_23_Jeb Bush_30_32\"}\n{\"mention\": \"Davis\", \"polarity\": -1, \"from\": 5, \"to\": 10, \"sentence\": \"When Davis refused Bunning's order to issue licenses, the judge declared the clerk in contempt of court and jailed her for five days.\", \"id\": \"allsides_2892_1181_25_Davis'_5_10\"}\n{\"mention\": \"Bunning\", \"polarity\": 0, \"from\": 19, \"to\": 26, \"sentence\": \"When Davis refused Bunning's order to issue licenses, the judge declared the clerk in contempt of court and jailed her for five days.\", \"id\": \"allsides_2892_1181_25_U.S. District Judge David Bunning_19_26\"}\n{\"mention\": \"Bunning\", \"polarity\": 0, \"from\": 6, \"to\": 13, \"sentence\": \"Since Bunning first ordered Davis to issue the marriage licenses, the clerk and her attorneys have made several attempts to legally get around it.\", \"id\": \"allsides_2892_1181_31_Bunning_6_13\"}\n{\"mention\": \"Judge Bunning\", \"polarity\": 0, \"from\": 152, \"to\": 165, \"sentence\": \"But Ms. Davis refused to comply and was subsequently jailed; she was set free after five nights and after her deputy clerks began issuing licenses, and Judge Bunning ordered that she not interfere.\", \"id\": \"allsides_2893_1181_20_Judge Bunning_152_165\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Donald Trump Gets Rock Star Greeting in Iowa\", \"id\": \"allsides_2895_1182_0_Donald Trump_0_12\"}\n{\"mention\": \"Iowa\", \"polarity\": 0, \"from\": 40, \"to\": 44, \"sentence\": \"Donald Trump Gets Rock Star Greeting in Iowa\", \"id\": \"allsides_2895_1182_0_Iowa_40_44\"}\n{\"mention\": \"Mr. Rubio\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Rubio made a better impression on Evan Monson, an Iowa State junior, who praised him for hanging out at the Sigma Pi fraternity tailgate party.\", \"id\": \"allsides_2895_1182_43_Marco Rubio_0_9\"}\n{\"mention\": \"Iowa\", \"polarity\": 0, \"from\": 54, \"to\": 58, \"sentence\": \"Mr. Rubio made a better impression on Evan Monson, an Iowa State junior, who praised him for hanging out at the Sigma Pi fraternity tailgate party.\", \"id\": \"allsides_2895_1182_43_Iowa_54_58\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He visited the growers’ tent and strolled the parking lots with a more manageable level of attention than Mr. Trump.\", \"id\": \"allsides_2895_1182_46_Marco Rubio_0_2\"}\n{\"mention\": \"Carson\", \"polarity\": 1, \"from\": 38, \"to\": 44, \"sentence\": \"“Trump has an edge on leadership, but Carson has a 20-point margin when it comes to having the right temperament and personality to handle an international crisis.”\", \"id\": \"allsides_2897_1182_28_Ben Carson_38_44\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump was at 27 percent support, followed by Mr. Carson at 21 percent and Sen.\", \"id\": \"allsides_2897_1182_2_Mr. Trump_0_9\"}\n{\"mention\": \"Perry\", \"polarity\": 1, \"from\": 4, \"to\": 9, \"sentence\": \"Mr. Perry said in his prepared remarks that he leaves the race “a blessed man.”\", \"id\": \"allsides_2898_1183_38_Mr. Perry_4_9\"}\n{\"mention\": \"Perry\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Perry told The Huffington Post in April he felt more prepared this time around, even with less bells and whistles surrounding his presidential efforts.\", \"id\": \"allsides_2900_1183_12_Rick Perry_0_5\"}\n{\"mention\": \"The Huffington Post\", \"polarity\": 0, \"from\": 11, \"to\": 30, \"sentence\": \"Perry told The Huffington Post in April he felt more prepared this time around, even with less bells and whistles surrounding his presidential efforts.\", \"id\": \"allsides_2900_1183_12_The Huffington Post_11_31\"}\n{\"mention\": \"Walker\", \"polarity\": 0, \"from\": 130, \"to\": 136, \"sentence\": \"\\\"What we will try to do is try to get support from people who supported him, and any other candidate that's next moving forward,\\\" Walker said.\", \"id\": \"allsides_2900_1183_20_Scott Walker_130_136\"}\n{\"mention\": \"Iran\", \"polarity\": -1, \"from\": 36, \"to\": 40, \"sentence\": \"Donald Trump and Ted Cruz Lead Anti-Iran Deal Rally\", \"id\": \"allsides_2904_1185_0_Iran_36_40\"}\n{\"mention\": \"Franken\", \"polarity\": -1, \"from\": 29, \"to\": 36, \"sentence\": \"Some Republicans insist that Franken must resign but say that the people of Alabama should decide what to do about Moore.\", \"id\": \"allsides_290_117_34_Democratic senator Al Franken_29_36\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 1, \"to\": 3, \"sentence\": \"“He has to make a really difficult decision.\", \"id\": \"allsides_2915_1190_34_Clinton_1_3\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton then did utter the word \\\"sorry,\\\" but seemed to turn the blame on others for not understanding the ins and outs of the scandal.\", \"id\": \"allsides_2915_1190_4_Clinton_0_7\"}\n{\"mention\": \"the scandal\", \"polarity\": -1, \"from\": 122, \"to\": 133, \"sentence\": \"Clinton then did utter the word \\\"sorry,\\\" but seemed to turn the blame on others for not understanding the ins and outs of the scandal.\", \"id\": \"allsides_2915_1190_4_the email scandal_122_133\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 38, \"to\": 45, \"sentence\": \"In the interview, Mitchell also asked Clinton how she feels that a Quinnipiac poll found that the first words that came to mind among voters when asked about her were “liar,” “untrustworthy” and “crooked.\\\"\", \"id\": \"allsides_2916_1190_11_Clinton_38_45\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 201, \"to\": 208, \"sentence\": \"“At the end of the day, I am sorry that this has been confusing to people and has raised a lot of questions, but there are answers to all these questions and I will continue to provide those answers,” Clinton told MSNBC’s Andrea Mitchell.\", \"id\": \"allsides_2916_1190_3_Clinton_201_208\"}\n{\"mention\": \"Yates\", \"polarity\": 0, \"from\": 68, \"to\": 73, \"sentence\": \"Her office was dark Friday morning as the license was issued to Mr. Yates and Mr. Smith, with a sheriff’s deputy standing guard in front of it.\", \"id\": \"allsides_2918_1191_11_Yates_68_73\"}\n{\"mention\": \"Davis\", \"polarity\": -1, \"from\": 255, \"to\": 260, \"sentence\": \"It is a Heaven or Hell decision\\\" \\\\- Kim Davis Davis' office has steadfastly denied marriage licenses since the Supreme Court legalized gay marriage this summer, and that practice continued Tuesday morning when at least two same-sex couples were denied as Davis invoked \\\"God's authority.\\\"\", \"id\": \"allsides_2925_1194_9_Rowan County Clerk Kim Davis_255_260\"}\n{\"mention\": \"the county clerk\", \"polarity\": -1, \"from\": 164, \"to\": 180, \"sentence\": \"Here's raw footage of the confrontation. http://goo.gl/jYNVXo UPDATE: The lawyers for the same-sex couples who originally sued Davis filed a motion Tuesday to hold the county clerk in contempt of court for refusing to issue them a marriage license.\", \"id\": \"allsides_2926_1194_8_Rowan County Clerk Kim Davis_164_180\"}\n{\"mention\": \"the same-sex couples who originally sued Davis\", \"polarity\": 0, \"from\": 86, \"to\": 132, \"sentence\": \"Here's raw footage of the confrontation. http://goo.gl/jYNVXo UPDATE: The lawyers for the same-sex couples who originally sued Davis 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\"allsides_2934_1198_38_George W. Bush_26_29\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": 1, \"from\": 99, \"to\": 108, \"sentence\": \"Such racial divides are braided through this city’s history like Creole and jambalaya, a past that Mr. Obama celebrated as he toured a series of new pastel-colored homes in a district, Tremé, that he said was a birthplace of jazz and one of the most important African-American communities in the country.\", \"id\": \"allsides_2935_1198_18_Mr. Obama_99_108\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 137, \"to\": 139, \"sentence\": \"Mr. Flanagan, 41, who went by the name Bryce Williams in recent years, had not been convicted of a crime or adjudicated mentally ill, so he apparently passed a background check in June, when he bought the Glock 19 handgun used in the killings.\", \"id\": \"allsides_2937_1199_23_Senator Marco Rubio of Florida, a Republican presidential contender_137_139\"}\n{\"mention\": \"the Glock 19 handgun used in the killings\", \"polarity\": -1, \"from\": 201, \"to\": 242, \"sentence\": \"Mr. Flanagan, 41, who went by the name Bryce Williams in recent years, had not been convicted of a crime or adjudicated mentally ill, so he apparently passed a background check in June, when he bought the Glock 19 handgun used in the killings.\", \"id\": \"allsides_2937_1199_23_the Glock 19 handgun used in the killings_201_242\"}\n{\"mention\": \"Biden\", \"polarity\": 1, \"from\": 29, \"to\": 34, \"sentence\": \"And a Quinnipiac Poll showed Biden running strong in head-to-head match-ups with Republican candidates in key states.\", \"id\": \"allsides_2946_1204_12_Biden_29_34\"}\n{\"mention\": \"Warren\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Warren has so far decline.\", \"id\": \"allsides_2946_1204_4_Warren_0_6\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 87, \"to\": 94, \"sentence\": \"Earlier this year, campaign-watchers focused on Warren and whether she would challenge Clinton, prompting a vibrant \\\"Draft 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has begun to explore a possible presidential campaign in recent weeks, made the trip Saturday from his home in Wilmington, Del., to his official residence at the Naval Observatory in Washington to meet Warren, who has become an icon to liberal activists who view financial institutions as wielding too much clout in the corridors of power.\", \"id\": \"allsides_2947_1204_4_Warren_213_219\"}\n{\"mention\": \"Carter\", \"polarity\": 1, \"from\": 109, \"to\": 115, \"sentence\": \"\\\"I plan to teach Sunday school this Sunday -- and every Sunday as long as I'm physically and mentally able,\\\" Carter said.\", \"id\": \"allsides_2953_1207_38_Former president Jimmy Carter_109_115\"}\n{\"mention\": \"Jimmy Carter\", \"polarity\": 1, \"from\": 18, \"to\": 30, \"sentence\": \"[Former president Jimmy Carter, 90, announces that he has cancer] He noted that the well wishes have poured in from President Barack Obama and the first family, as well as all of the living former presidents.\", \"id\": \"allsides_2953_1207_39_Former president Jimmy Carter_18_30\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 22, \"to\": 25, \"sentence\": \"Bar and I are wishing him the very best as he fights the good fight.\", \"id\": \"allsides_2953_1207_41_Former president Jimmy Carter_22_25\"}\n{\"mention\": \"Carter\", \"polarity\": 1, \"from\": 38, \"to\": 44, \"sentence\": \"In a frank discussion with reporters, Carter said he is “in the hands of God” and feels “prepared for anything that comes.”\", \"id\": \"allsides_2954_1207_4_Jimmy Carter_38_44\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 60, \"to\": 67, \"sentence\": \"Unlike his key Democratic opponent whom he refuses to bash, Sanders appears both honest and trustworthy.\", \"id\": \"allsides_2967_1214_2_Bernie Sanders'_60_67\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Obama wanted to be a Reagan of the left, a \\\"transformative\\\" president who moved the magnetic poles of 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\"allsides_297_119_23_(AP) Conyers, 88, the longest-serving House member_0_51\"}\n{\"mention\": \"Carly\", \"polarity\": 1, \"from\": 1, \"to\": 6, \"sentence\": \"“Carly obviously struck a sweet spot with politically engaged seniors during the first debate.”\", \"id\": \"allsides_2981_1219_12_Carly_1_6\"}\n{\"mention\": \"Carly\", \"polarity\": 1, \"from\": 26, \"to\": 31, \"sentence\": \"“For those of us who know Carly, her dominating performance was no surprise,” Anna Epstein, press secretary for Fiorina’s campaign told TheBlaze.\", \"id\": \"allsides_2981_1219_5_Carly_26_31\"}\n{\"mention\": \"Donald Trump's\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"Donald Trump's war on Megyn Kelly\", \"id\": \"allsides_2983_1220_0_Donald Trump's_0_14\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump’s spat with Fox News began after Kelly asked him during the debate about disparaging comments he had made towards women in the past.\", \"id\": \"allsides_2984_1220_9_Real estate tycoon Donald Trump_0_5\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 78, \"to\": 82, \"sentence\": \"But, Kasich is popular with moderates who are skittish about electing another Bush, and this debate allowed him to reach a bigger audience.\", \"id\": \"allsides_2985_1221_28_Bush_78_82\"}\n{\"mention\": \"Kasich\", \"polarity\": 1, \"from\": 5, \"to\": 11, \"sentence\": \"But, Kasich is popular with moderates who are skittish about electing another Bush, and this debate allowed him to reach a bigger audience.\", \"id\": \"allsides_2985_1221_28_John Kasich_5_11\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 6, \"to\": 8, \"sentence\": \"Maybe he really is simply rusty.\", \"id\": \"allsides_2985_1221_32_Bush_6_8\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 4, \"to\": 6, \"sentence\": \"Did he make any great errors?\", \"id\": \"allsides_2987_1221_9_Jeb Bush_4_6\"}\n{\"mention\": \"the next president\", \"polarity\": 0, \"from\": 63, \"to\": 81, \"sentence\": \"But a recent CNN poll indicates the majority of Americans want the next president to change most of President Obama’s policies.\", \"id\": \"allsides_2990_1223_4_President Obama_63_81\"}\n{\"mention\": \"President Bush\", \"polarity\": -1, \"from\": 48, \"to\": 62, \"sentence\": \"Still voters don’t want a return to the days of President Bush and have expressed their frustration with both presidents by indicating preferences for Trump and Sanders despite their extreme views.\", \"id\": \"allsides_2990_1223_5_President Obama_48_62\"}\n{\"mention\": \"voters\", \"polarity\": 0, \"from\": 6, \"to\": 12, \"sentence\": \"Still voters don’t want a return to the days of President Bush and have expressed their frustration with both presidents by indicating preferences for Trump and Sanders despite their extreme views.\", \"id\": \"allsides_2990_1223_5_voters_6_12\"}\n{\"mention\": \"Bill Sammon\", \"polarity\": 1, \"from\": 196, \"to\": 207, \"sentence\": \"Drawing on exhaustive, on-the-scene reporting and exclusive interviews with the key players -- including President George W. 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\"allsides_2991_1223_189_Roger Fontaine_105_119\"}\n{\"mention\": \"Fox\", \"polarity\": 0, \"from\": 41, \"to\": 44, \"sentence\": \"Sammon subsequently appeared on multiple Fox programs -- and penned an article for FoxNews.com -- promoting Obama's ties to \\\"Marxists.\\\"\", \"id\": \"allsides_2991_1223_45_[Media Matters,3/29/11] Roger Ailes_41_44\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 137, \"to\": 144, \"sentence\": \"On the other hand, Mr. Sanders argued Sunday that he is better positioned to win the Democratic nomination than either Mr. Biden or Mrs. Clinton, who are both viewed as members of the party establishment.\", \"id\": \"allsides_2995_1225_32_Clinton_137_144\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She’s a disaster because of arrogance.”\", \"id\": \"allsides_2995_1225_6_Hillary Clinton_0_3\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 1, \"to\": 4, \"sentence\": \"“She has the most money and she is beating every Republican in most of the polls,” Jennifer Palmieri, a spokeswoman for the campaign, told CNN on Sunday.\", \"id\": \"allsides_2997_1225_8_Hillary Rodham Clinton_1_4\"}\n{\"mention\": \"Cuban\", \"polarity\": 1, \"from\": 20, \"to\": 25, \"sentence\": \"People, at least if Cuban is to be believed (and I think he is), aren't really listening to the specifics of what Trump is saying.\", \"id\": \"allsides_3005_1229_18_Mark Cuban_20_25\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump would do better.\", \"id\": \"allsides_3005_1229_26_Donald Trump's_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 5, \"to\": 10, \"sentence\": \"Yes, Trump's unscriptedness is a trait more politicians can and should adopt.\", \"id\": \"allsides_3005_1229_32_Donald Trump's_6_11\"}\n{\"mention\": \"Sarah Palin\", \"polarity\": 1, \"from\": 39, \"to\": 50, \"sentence\": \"And maybe that’s part of the beauty of Sarah Palin.\", \"id\": \"allsides_3006_1229_12_Sarah Palin_39_50\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 8, \"to\": 11, \"sentence\": \"I think she’s terrific.”\", \"id\": \"allsides_3006_1229_14_Sarah Palin_8_11\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 35, \"to\": 38, \"sentence\": \"“And I think people know that, and she’s got a following that’s unbelievable.\", \"id\": \"allsides_3006_1229_6_Sarah Palin_35_38\"}\n{\"mention\": \"Joyce Mitchell\", \"polarity\": -1, \"from\": 23, \"to\": 37, \"sentence\": \"Former prison employee Joyce Mitchell pleaded guilty today to helping two convicted murderers escape from a maximum security prison last month in New York.\", \"id\": \"allsides_3008_1230_1_Joyce Mitchell_25_39\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 12, \"to\": 19, \"sentence\": \"The fact is Hillary wants to punish success in order to grow government, and that means the biggest loser will be our economy,\\\" he said.\", \"id\": \"allsides_3017_1234_9_Hillary Clinton_12_19\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 41, \"to\": 48, \"sentence\": \"It also reveals the deeply wonky side of Clinton.\", \"id\": \"allsides_3018_1234_4_Hillary Clinton_41_48\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 32, \"to\": 39, \"sentence\": \"Voters in all three states gave Clinton low marks for honesty and trustworthiness, with 62 percent of Colorado voters saying she is not honest or trustworthy, compared to only 34 percent who think she is.\", \"id\": \"allsides_3022_1236_11_Clinton_32_39\"}\n{\"mention\": \"Colorado\", \"polarity\": 0, \"from\": 102, \"to\": 110, \"sentence\": \"Voters in all three states gave Clinton low marks for honesty and trustworthiness, with 62 percent of Colorado voters saying she is not honest or trustworthy, compared to only 34 percent who think she is.\", \"id\": \"allsides_3022_1236_11_Colorado_102_110\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 174, 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Carter_22_32\"}\n{\"mention\": \"Ferguson\", \"polarity\": 0, \"from\": 84, \"to\": 92, \"sentence\": \"The president has faced a challenge in calibrating his response to the situation in Ferguson, working to balance the task of urging calm and unity with his desire, as America’s first black president, to acknowledge racial wounds — all while being careful not to interfere in the investigation.\", \"id\": \"allsides_3868_1602_7_Ferguson_84_92\"}\n{\"mention\": \"The president\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"The president also is scheduled to meet on Monday with elected officials, law enforcement officials and community, civil rights and religious leaders from around the country to discuss ways they can work together to foster stronger communities.\", \"id\": \"allsides_3868_1602_9_Mr. Obama_0_13\"}\n{\"mention\": \"Chuck Schumer\", \"polarity\": -1, \"from\": 10, \"to\": 23, \"sentence\": \"”’Senator Chuck Schumer helping to import Europes problems,’” said Col.Tony Shaffer,” Trump wrote.\", \"id\": \"allsides_386_155_14_Chuck Schumer_10_23\"}\n{\"mention\": \"Michael Brown's\", \"polarity\": 1, \"from\": 15, \"to\": 30, \"sentence\": \"\\\"We were after Michael Brown's justice.\\\"\", \"id\": \"allsides_3871_1604_11_Brown_15_30\"}\n{\"mention\": \"Ginsburg\", \"polarity\": 1, \"from\": 63, \"to\": 71, \"sentence\": \"In an October interview in The New Yorker magazine, Obama said Ginsburg was \\\"doing a wonderful job.\\\"\", \"id\": \"allsides_3874_1606_25_Justice Ruth Bader Ginsburg_63_71\"}\n{\"mention\": \"Brown\", \"polarity\": -1, \"from\": 63, \"to\": 68, \"sentence\": \"Wilson, who is much smaller than the 6-foot, 4-inch, 290-pound Brown was, told the panel of being attacked and in fear for his life as Brown slammed his squad car door on him and pummeled him through the window moments after Wilson confronted him walking in the middle of the street.\", \"id\": \"allsides_3881_1609_12_Brown_63_68\"}\n{\"mention\": \"Wilson\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Wilson testified that, “I felt like a 5-year-old holding onto Hulk Hogan.”\", \"id\": \"allsides_3881_1609_13_Wilson_0_6\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 61, \"to\": 67, \"sentence\": \"Brown stopped and turned to face the officer, however, after Wilson shot again.\", \"id\": \"allsides_3881_1609_42_Wilson_61_67\"}\n{\"mention\": \"Johnson\", \"polarity\": 0, \"from\": 177, \"to\": 184, \"sentence\": \"“At that time Big Mike’s hands was up, but not so much in the air, because he had been struck … he said, 'I don’t have a gun,' but he’s still mad, he still has his angry face,” Johnson said.\", \"id\": \"allsides_3881_1609_43_Johnson_177_184\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 35, \"to\": 41, \"sentence\": \"A majority of black Americans said Wilson would be punished too leniently, with just 2 percent worrying his punishment would be too harsh.\", \"id\": \"allsides_3882_1609_10_Wilson_35_41\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 68, \"to\": 74, \"sentence\": \"Democrats were also three times more likely than Republicans to say Wilson was at fault, and to fear that he would be punished too leniently.\", \"id\": \"allsides_3882_1609_11_Wilson_68_74\"}\n{\"mention\": \"Wilson\", \"polarity\": 0, \"from\": 32, \"to\": 38, \"sentence\": \"Twenty-two percent had expected Wilson to be punished too harshly, while 26 percent believed he'd get off too lightly.\", \"id\": \"allsides_3882_1609_4_Wilson_32_38\"}\n{\"mention\": \"Wilson\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Wilson told grand jurors he was thinking: “What do I do not to get beaten inside my car.”\", \"id\": \"allsides_3884_1610_17_Ferguson Officer Darren Wilson_0_6\"}\n{\"mention\": \"Wilson\", \"polarity\": 0, \"from\": 91, \"to\": 97, \"sentence\": \"“Hulk Hogan, that’s just how big he felt and how small I felt just from grasping his arm,” Wilson replied.\", \"id\": \"allsides_3884_1610_21_Ferguson Officer Darren Wilson_91_97\"}\n{\"mention\": \"[Brown\", \"polarity\": 0, \"from\": 81, \"to\": 87, \"sentence\": \"“After I fired… I paused for a second, yelled at him to get on the ground again. 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117, \"to\": 119, \"sentence\": \"I don’t understand why United States senators want to block debate when the leader has said we can have amendments,\\\" he said.\", \"id\": \"allsides_5555_2370_12_John McCain_117_119\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 90, \"to\": 92, \"sentence\": \"“It can get done, but what’s it’s going to require is for Republicans not to filibuster,” he said.\", \"id\": \"allsides_5556_2370_5_Mr. Pfeiffer_90_92\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 22, \"to\": 27, \"sentence\": \"Upon hearing that Mr. Trump had disinvited Stephen Curry of the Golden State Warriors from the traditional White House ceremony honoring championship teams, Mr. James said on Twitter: “U bum,” adding, “Going to White House was a great honor until you showed up!”\", \"id\": \"allsides_555_220_19_President Trump_22_27\"}\n{\"mention\": \"The former N.F.L. coach Rex Ryan, who introduced Mr. Trump at a rally during the campaign\", \"polarity\": -1, 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\"to\": 59, \"sentence\": \"A month ago, women favored Obama over Romney on the economy 56 percent to 40 percent.\", \"id\": \"allsides_6094_2617_30_the economy_48_59\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 4, \"to\": 9, \"sentence\": \"For Obama it is the natural urge to explain what he has done on foreign policy.\", \"id\": \"allsides_6104_2622_15_Obama_4_9\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 4, \"to\": 10, \"sentence\": \"For Romney it is the natural urge to prove he is competent on this turf and not just a businessman.\", \"id\": \"allsides_6104_2622_16_Mitt Romney_4_10\"}\n{\"mention\": \"Mitt Romney\", \"polarity\": 1, \"from\": 27, \"to\": 38, \"sentence\": \"President Barack Obama and Mitt Romney have had two of the most memorable debates in modern presidential history, and they get together for the last one in Boca Raton, Fla. tonight.\", \"id\": \"allsides_6104_2622_2_Mitt Romney_27_38\"}\n{\"mention\": \"Obama\", \"polarity\": 0, 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American people to win votes, but the truth is he’d take us back to the same failed policies that devastated the middle class in the first place,” campaign spokesman Danny Kanner said in a statement.\", \"id\": \"allsides_6107_2623_27_Obama_4_9\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 1, \"to\": 7, \"sentence\": \"“Romney is a man with a plan.\", \"id\": \"allsides_6107_2623_5_Romney_1_7\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 22, \"to\": 27, \"sentence\": \"NEW YORK –  President Obama and Mitt Romney squeezed a comedy break in between debates last night, drawing laughs at a New York charity dinner that's long been a required stop for anyone trying to capture the White House.\", \"id\": \"allsides_6108_2624_1_Obama_24_29\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 59, \"to\": 65, \"sentence\": \"Obama said he has been preparing for the final debate with Romney on Monday, which will focus on foreign policy.\", \"id\": 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history'\", \"id\": \"allsides_611_243_0_Former White House chief strategist Steve Bannon_27_38\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 57, \"to\": 62, \"sentence\": \"Poll gives Romney national edge, underscoring stakes for Obama at debate\", \"id\": \"allsides_6120_2629_0_Obama_57_62\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Romney's running mate Paul Ryan took on the challenge, asserting in Ohio and Wisconsin that Obama had inherited a tough economic situation but made things worse.\", \"id\": \"allsides_6120_2629_36_Romney_0_6\"}\n{\"mention\": \"The president\", \"polarity\": 1, \"from\": 62, \"to\": 75, \"sentence\": \"But Obama’s attack will also be more explicitly gender-based: The president will look for an opportunity to talk about social issues, especially Romney’s flip from pro-abortion rights as a gubernatorial candidate to anti-abortion as Massachusetts governor — and the GOP nominee’s opposition to Planned 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\"id\": \"allsides_6210_2668_20_Mitt Romney_30_36\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 25, \"to\": 31, \"sentence\": \"As we have noted before, Romney's financial life as a very wealthy person is significantly more exotic than the average person he needs to vote for him; that he made almost $14 million in 2011 (and $21 million in 2010) without drawing any salary is all the confirmation you need of that fact.\", \"id\": \"allsides_6210_2668_2_Mitt Romney_25_31\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 20, \"to\": 26, \"sentence\": \"And that's not what Romney wants.\", \"id\": \"allsides_6210_2668_30_Mitt Romney_21_27\"}\n{\"mention\": \"Washington Post\", \"polarity\": 0, \"from\": 208, \"to\": 223, \"sentence\": \"Must-reads: \\\"Romney Is Latest in a Long Line to Trip Over a Tongue\\\" -- John Harwood, New York Times \\\"Scott Gessler, Colorado’s ‘honey badger,’ may be most closely watched election official\\\" -- Robert Barnes, Washington Post \\\"Obama mocks Romney on ‘47 percent’ remarks during Univision forum\\\" -- David Nakamura, Washington Post \\\"Why early voting could  be pivotal\\\" -- Major Garrett, National Journal \\\"Obama pressed on failures at Univision forum\\\" -- Reid J. Epstein, Politico \\\"GOP retreat on taxes likely if Obama wins\\\" -- Lori Montgomery and Paul Kane, Washington Post \\\"Romney campaign hits a financial snag\\\" -- Dan Eggen, Washington Post\", \"id\": \"allsides_6211_2669_36_Washington Post_208_223\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 13, \"to\": 19, \"sentence\": \"Must-reads: \\\"Romney Is Latest in a Long Line to Trip Over a Tongue\\\" -- John Harwood, New York Times \\\"Scott Gessler, Colorado’s ‘honey badger,’ may be most closely watched election official\\\" -- Robert Barnes, Washington Post \\\"Obama mocks Romney on ‘47 percent’ remarks during Univision forum\\\" -- David Nakamura, Washington Post \\\"Why early voting could  be pivotal\\\" -- Major Garrett, National Journal \\\"Obama pressed on failures at Univision forum\\\" -- Reid J. Epstein, Politico \\\"GOP retreat on taxes likely if Obama wins\\\" -- Lori Montgomery and Paul Kane, Washington Post \\\"Romney campaign hits a financial snag\\\" -- Dan Eggen, Washington Post\", \"id\": \"allsides_6211_2669_36_Moderate Mitt Romney_13_19\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 6, \"to\": 12, \"sentence\": \"After Romney focused on the “can’t change Washington from the inside” segment of Obama’s remarks, the president’s campaign countered quickly by noting that Romney said exactly that in 2007, when he was running for the 2008 Republican nomination: “I don’t think you change Washington from the inside.\", \"id\": \"allsides_6213_2669_14_Romney_6_12\"}\n{\"mention\": \"Mitt\", \"polarity\": 1, \"from\": 120, \"to\": 124, \"sentence\": \"“And it is time for all Americans to realize how significant this election is and how lucky we are to have someone with Mitt’s qualifications and experience and know-how to be able to have the opportunity to run this 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\"sentence\": \"Mitt Romney's \\\"off-the-cuff\\\" remarks that nearly half of Americans are \\\"dependent\\\" on government and believe they are \\\"victims\\\" who are \\\"entitled to health care, to food, to housing, to-you-name-it,\\\"  were widely publicized.\", \"id\": \"allsides_6223_2674_1_Mitt Romney's_2_15\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 88, \"to\": 94, \"sentence\": \"It’s an approach that carries the risk of a big defeat, but it’s still a better one for Romney.\", \"id\": \"allsides_6224_2674_39_Romney_88_94\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 57, \"to\": 63, \"sentence\": \"Political pundits are comparing the leaked video of Mitt Romney at a fundraiser writing off the 47 percent of the electorate who don’t pay federal income taxes to the leaked 2008 fundraiser video of then-Sen.\", \"id\": \"allsides_6224_2674_7_Romney_57_63\"}\n{\"mention\": \"the leaked video of Mitt Romney\", \"polarity\": -1, \"from\": 32, \"to\": 63, \"sentence\": \"Political pundits are comparing the leaked video of Mitt Romney at a fundraiser writing off the 47 percent of the electorate who don’t pay federal income taxes to the leaked 2008 fundraiser video of then-Sen.\", \"id\": \"allsides_6224_2674_7_a video obtained by liberal magazine Mother Jones_32_63\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 10, \"to\": 15, \"sentence\": \"But while Obama was talking about something in contradiction to his campaign message – talking down the very voters he was trying to persuade to come to his side – Romney was actually on message, just in more blunt fashion than usual.\", \"id\": \"allsides_6224_2674_9_Barack Obama_10_15\"}\n{\"mention\": \"Barack Obama\", \"polarity\": -1, \"from\": 103, \"to\": 115, \"sentence\": \"A second Romney ad out Monday, “ Failing American Families,” is harsher, with a male narrator saying: “Barack Obama: More spending.\", \"id\": \"allsides_6226_2676_13_Obama_103_115\"}\n{\"mention\": \"POLITICO\", \"polarity\": 0, \"from\": 32, \"to\": 40, \"sentence\": \"Story Continued Below ( Also on POLITICO: Inside the campaign: How Mitt stumbled) But with polls showing Obama for the first time moving clearly ahead in important swing states— most notably, Ohio—Romney advisers concluded they had to make a painful course correction.\", \"id\": \"allsides_6226_2676_4_POLITICO_32_40\"}\n{\"mention\": \"Stevens\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Stevens said the economy is likely to remain “the dominant focus” of the campaign.\", \"id\": \"allsides_6226_2676_5_Romney_0_7\"}\n{\"mention\": \"Stevens\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Stevens said the big, unifying question will be: “Can we do better on every front?”\", \"id\": \"allsides_6226_2676_7_Romney_0_7\"}\n{\"mention\": \"Mr. Gillespie\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"Mr. Gillespie’s conference call with reporters followed a report in Politico 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\"allsides_6313_2714_15_Mrs. Romney_117_127\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 24, \"to\": 27, \"sentence\": \"Their personality gap — her ease, his discomfort — has been evident in most of the many joint interviews they have given television reporters.\", \"id\": \"allsides_6313_2714_3_Ann Romney_24_27\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 34, \"to\": 37, \"sentence\": \"Their personality gap — her ease, his discomfort — has been evident in most of the many joint interviews they have given television reporters.\", \"id\": \"allsides_6313_2714_3_a Husband_34_37\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He also briefly considered running for president himself this year, but ruled it out, concluding that he was not yet ready to assume the office.\", \"id\": \"allsides_6315_2715_10_Mr. Romney_0_2\"}\n{\"mention\": \"the hall\", \"polarity\": 0, \"from\": 141, \"to\": 149, \"sentence\": \"But his aggressive style, 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president_37_48\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 31, \"to\": 43, \"sentence\": \"Nothing James Comey said about Donald Trump Thursday inspired any confidence in the leadership of the president.\", \"id\": \"allsides_985_395_57_Donald Trump Here_31_43\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 102, \"to\": 114, \"sentence\": \"Comey’s prepared testimony, released Wednesday afternoon, gave the public a narrative: that President Donald Trump consistently either failed to understand or intentionally violated the norms of independence that set the FBI out of political reach.\", \"id\": \"allsides_985_395_7_Donald Trump Here_102_114\"}\n{\"mention\": \"Comey\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Comey will also state that Trump was briefed because the intelligence community officials knew that “the media was about to publicly report the material and we believed the IC should not keep knowledge of the material and its imminent release from the President-Elect.”\", \"id\": \"allsides_988_397_21_Former FBI Director James Comey_0_5\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Flynn is at the center of several investigations.\", \"id\": \"allsides_988_397_40_Flynn_0_5\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He may have lied to the FBI about his calls with Kislyak.\", \"id\": \"allsides_988_397_41_Flynn_0_2\"}\n{\"mention\": \"the FBI\", \"polarity\": 0, \"from\": 20, \"to\": 27, \"sentence\": \"He may have lied to the FBI about his calls with Kislyak.\", \"id\": \"allsides_988_397_41_FBI_20_27\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 78, \"to\": 83, \"sentence\": \"That revelation has already led to obstruction of justice allegations against Trump.\", \"id\": \"allsides_988_397_6_President Trump_78_83\"}\n{\"mention\": \"\\\"President Trump\", \"polarity\": 1, \"from\": 0, \"to\": 16, \"sentence\": \"\\\"President Trump is committed to the rule of law, and will work with members of both parties to reach a permanent solution that corrects the unconstitutional actions taken by the last administration.\\\"\", \"id\": \"allsides_98_40_18_President Trump_0_16\"}\n{\"mention\": \"Mr. Comey\", \"polarity\": -1, \"from\": 20, \"to\": 29, \"sentence\": \"Asked to respond to Mr. Comey’s assertion that the president had lied, she said, “I can definitively say the president is not a liar, and frankly I’m insulted by that question.”\", \"id\": \"allsides_990_397_12_Mr. Comey_20_29\"}\n{\"mention\": \"Mr. Comey\", \"polarity\": -1, \"from\": 15, \"to\": 24, \"sentence\": \"— Glenn Thrush Mr. Comey acknowledged for the first time that the F.B.I. was scrutinizing Mr. Trump’s actions.\", \"id\": \"allsides_990_397_23_Mr. Comey_15_24\"}\n{\"mention\": \"Mr. Comey\", \"polarity\": 0, \"from\": 40, \"to\": 49, \"sentence\": \"Mr. Trump made that claim when he fired Mr. Comey last month.\", \"id\": \"allsides_990_397_6_Matt Apuzzo Mr. Comey_40_49\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 83, \"to\": 88, \"sentence\": \"\\\"I had understood the President to be requesting that we drop any investigation of Flynn in connection with false statements about his conversations with the Russian ambassador in December,\\\" the former FBI director explained in his testimony.\", \"id\": \"allsides_991_398_11_Mike Flynn_83_88\"}\n{\"mention\": \"Comey\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Comey's interpretation is not unreasonable, and, of course, bears significant credibility given that he was the only person to actually hear the president's words.\", \"id\": \"allsides_991_398_12_James Comey's_0_5\"}\n{\"mention\": \"the president\", \"polarity\": 0, \"from\": 141, \"to\": 154, \"sentence\": \"Comey's interpretation is not unreasonable, and, of course, bears significant credibility given that he was the only person to actually hear the president's words.\", \"id\": \"allsides_991_398_12_Trump_141_154\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 30, \"to\": 35, \"sentence\": \"But take another look at what Trump actually said, according to Comey's account: \\\"I hope you can see your way clear to letting this go, to letting Flynn go.\\\"\", \"id\": \"allsides_991_398_13_Trump_30_35\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 17, \"to\": 22, \"sentence\": \"He repeated that Flynn hadn't done anything wrong on his calls with the Russians, but had misled the Vice President.\", \"id\": \"allsides_991_398_3_Mike Flynn_17_22\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump had encouraged Mr. Comey to say so publicly, but Mr. Comey refused — in part because he did not want to have to recant if that changed.\", \"id\": \"allsides_992_398_10_Mr. Trump_0_9\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 47, \"to\": 56, \"sentence\": \"“He is a good guy and has been through a lot,” Mr. Trump said, according to Mr. Comey’s testimony.\", \"id\": \"allsides_992_398_48_Mr. Trump_47_56\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He added: “I hope you can see your way clear to letting this go, to letting Flynn go.\", \"id\": \"allsides_992_398_49_Mr. Trump_0_2\"}\n{\"mention\": \"Wray\", \"polarity\": 1, \"from\": 37, \"to\": 41, \"sentence\": \"“I will be nominating Christopher A. Wray, a man of impeccable credentials, to be the new Director of the FBI,” the president announced on Twitter on Wednesday morning.\", \"id\": \"allsides_994_399_2_Christopher Wray_37_41\"}\n{\"mention\": \"Wray\", \"polarity\": 1, \"from\": 28, \"to\": 32, \"sentence\": \"Last week, Christie praised Wray as an “outstanding lawyer,” after it was revealed that he was under consideration.\", \"id\": \"allsides_994_399_7_Christopher Wray_28_32\"}\n{\"mention\": \"Christie\", \"polarity\": 1, \"from\": 11, \"to\": 19, \"sentence\": \"Last week, Christie praised Wray as an “outstanding lawyer,” after it was revealed that he was under consideration.\", \"id\": \"allsides_994_399_7_Governor Chris Christie_11_19\"}\n{\"mention\": \"FBI\", \"polarity\": 0, \"from\": 140, \"to\": 143, \"sentence\": \"“He has absolute integrity and honesty, and I think that the president certainly would not be making a mistake if he asked Chris Wray to be FBI director.”\", \"id\": \"allsides_995_399_62_FBI_140_143\"}\n{\"mention\": \"Chris Wray\", \"polarity\": 1, \"from\": 123, \"to\": 133, \"sentence\": \"“He has absolute integrity and honesty, and I think that the president certainly would not be making a mistake if he asked Chris Wray to be FBI director.”\", \"id\": \"allsides_995_399_62_Wray_123_133\"}\n{\"mention\": \"the N.S.A.\", \"polarity\": 0, \"from\": 100, \"to\": 110, \"sentence\": \"The F.B.I. affidavit said reporters for the news outlet, which it also did not name, had approached the N.S.A. with questions for their story and, in the course of that dialogue, provided a copy of the document in their possession.\", \"id\": \"allsides_999_401_12_N.S.A._100_110\"}\n{\"mention\": \"Sarah Huckabee Sanders\", \"polarity\": -1, \"from\": 4, \"to\": 26, \"sentence\": \"NB: Sarah Huckabee Sanders appears to have as tenuous a grasp on the separation of powers as her boss, as only utter and absolute misapprehension could explain why she’d argue that the executive’s meeting with legislators should dictate the judiciary’s actions in pending cases.\", \"id\": \"allsides_99_40_16_Sarah Huckabee Sanders_4_26\"}\n{\"mention\": \"Northam\", \"polarity\": -1, \"from\": 148, \"to\": 155, \"sentence\": \"At the same time that Gillespie released these advertisements, the Virginia Republican Party sent a new mailer, approved by Gillespie, that accused Northam of wanting to “tear down history while making life easier for illegal immigrants.”\", \"id\": \"polusa_v1_113704059_-1_35_Northam_148_155\"}\n{\"mention\": \"the cops\", \"polarity\": -1, \"from\": 96, \"to\": 104, \"sentence\": \"In a city—Chicago, no less, that favorite race-coded target of Trump’s dishonest rhetoric—where the cops can’t or won’t do their job, it falls to Willis to keep the peace, with increasingly small reservations and increasingly large guns.\", \"id\": \"polusa_v1_113705206_-1_7_the cops_96_104\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 63, \"to\": 68, \"sentence\": \"In a city—Chicago, no less, that favorite race-coded target of Trump’s dishonest rhetoric—where the cops can’t or won’t do their job, it falls to Willis to keep the peace, with increasingly small reservations and increasingly large guns.\", \"id\": \"polusa_v1_113705206_-1_7_Donald Trump_63_68\"}\n{\"mention\": \"Donald Trump's\", \"polarity\": -1, \"from\": 18, \"to\": 32, \"sentence\": \"“They do not want Donald Trump's populist, economic nationalist agenda to be implemented.\", \"id\": \"polusa_v1_113706422_-1_8_Donald Trump's_18_32\"}\n{\"mention\": \"Comey\", \"polarity\": 1, \"from\": 73, \"to\": 78, \"sentence\": \"After being fired for doing his job investigating government corruption, Comey—like so many whistleblowers before him—recognized the likely futility of an independent investigation being launched into potentially one of the most serious abuses of power in history without the power of the press.\", \"id\": \"polusa_v1_113706996_-1_41_former FBI Director James Comey_74_79\"}\n{\"mention\": \"Will Saletan, who just read it\", \"polarity\": 0, \"from\": 110, \"to\": 140, \"sentence\": \"Justin Sullivan/Getty Images\\nRight on: Michael Wolff’s book can be hard to believe in its particulars, writes Will Saletan, who just read it.\", \"id\": \"polusa_v1_113707351_-1_3_Will Saletan, who just read it_112_142\"}\n{\"mention\": \"Alexa\", \"polarity\": 1, \"from\": 43, \"to\": 48, \"sentence\": \"Even though I’m conscious of the fact that Alexa is an algorithm, I will still say thank you after she feeds me the information I’ve requested.”\", \"id\": \"polusa_v1_113708233_-1_112_Alexa_43_48\"}\n{\"mention\": \"myself\", \"polarity\": 0, \"from\": 103, \"to\": 109, \"sentence\": \"“When you’re in a house by yourself, which I am as a self-employed [person] a lot of times, talking to myself out loud is just not a thing I do.”\", \"id\": \"polusa_v1_113708233_-1_53_Emily_103_109\"}\n{\"mention\": \"Margolis\", \"polarity\": 1, \"from\": 1, \"to\": 9, \"sentence\": \"“Margolis was jovial and extroverted … and he enjoyed his food and his wine and made crass jokes.\", \"id\": \"polusa_v1_113708375_-1_73_Margolis_1_9\"}\n{\"mention\": \"Maduro\", \"polarity\": -1, \"from\": 113, \"to\": 119, \"sentence\": \"On Monday, National Security Advisor H.R. McMaster struggled to respond to a reporter’s question about what made Maduro’s power grab notably worse than the referendum that Trump had praised Erdogan for.\", \"id\": \"polusa_v1_113709000_-1_20_Maduro_113_119\"}\n{\"mention\": \"Kennedy\", \"polarity\": 1, \"from\": 82, \"to\": 89, \"sentence\": \"“A people confident in its laws and institutions should not be ashamed of mercy,” Kennedy said, perhaps drawing on his Catholic faith as he petitioned his audience of lawyers to make more such requests to presidents and governors.\", \"id\": \"polusa_v1_113709173_-1_31_Supreme Court Justice Anthony Kennedy_82_89\"}\n{\"mention\": \"Dr. Sanjay Gupta\", \"polarity\": 0, \"from\": 6, \"to\": 22, \"sentence\": \"CNN’s Dr. Sanjay Gupta suggested on air Wednesday night, after speaking with McCain’s doctors, that some combination of surgery, chemotherapy, and radiation would likely be required to combat the tumor.\", \"id\": \"polusa_v1_113711090_-1_10_Dr. Sanjay Gupta_7_23\"}\n{\"mention\": \"President George W. Bush\", \"polarity\": -1, \"from\": 28, \"to\": 52, \"sentence\": \"Advertisement\\nConsider that President George W. Bush is remembered for following the neocons Dick Cheney and Donald Rumsfeld down an ideological rabbit hole of invading Iraq.\", \"id\": \"polusa_v1_113711199_-1_10_Bush_29_53\"}\n{\"mention\": \"Dick Cheney\", \"polarity\": -1, \"from\": 93, \"to\": 104, \"sentence\": \"Advertisement\\nConsider that President George W. Bush is remembered for following the neocons Dick Cheney and Donald Rumsfeld down an ideological rabbit hole of invading Iraq.\", \"id\": \"polusa_v1_113711199_-1_10_Dick Cheney_94_105\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Donald Trump would promise some unbelievable benefit: an incredible investment opportunity, an unprecedented chance to learn valuable real estate skills, high-quality steaks for supermarket prices.\", \"id\": \"polusa_v1_113712974_-1_20_President Trump_0_12\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Gorsuch is equally clever when penning less freighted and consequential opinions.\", \"id\": \"polusa_v1_113713175_-1_28_Neil Gorsuch_1_8\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Gorsuch is equally clever when penning less freighted and consequential opinions.\", \"id\": \"polusa_v1_113713175_-1_28_Gorsuch_1_8\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 0, \"from\": 28, \"to\": 35, \"sentence\": \"Alex Wong/Getty Images\\nNeil Gorsuch is strikingly different from the man who nominated him to the United States Supreme Court.\", \"id\": \"polusa_v1_113713175_-1_3_Gorsuch_30_37\"}\n{\"mention\": \"Mike Pence\", \"polarity\": 1, \"from\": 74, \"to\": 84, \"sentence\": \"Wouldn’t literally everyone everywhere feel more comfortable right now if Mike Pence were in charge?\", \"id\": \"polusa_v1_113713260_-1_1_Mike Pence_76_86\"}\n{\"mention\": \"Thomas\", \"polarity\": 1, \"from\": 9, \"to\": 15, \"sentence\": \"Clarence Thomas’ consistency handed Democrats—and the principle of equality—a remarkable victory.\", \"id\": \"polusa_v1_113713857_-1_14_Thomas_10_16\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 54, \"to\": 57, \"sentence\": \"More than 100 of the country’s best legal minds think she’s right.\", \"id\": \"polusa_v1_113714131_-1_15_Ayala_54_57\"}\n{\"mention\": \"Smith\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Smith is quite right (with the possible exception of when A.I. algorithms train themselves independent of human involvement—but that’s another story).\", \"id\": \"polusa_v1_113715046_-1_17_U.S. Magistrate Judge Stephen Smith_0_5\"}\n{\"mention\": \"Sue Gordon\", \"polarity\": 1, \"from\": 1, \"to\": 11, \"sentence\": \"\\\"Sue Gordon is a great professional with a long and distinguished career,\\\" the president tweeted late Thursday.\", \"id\": \"polusa_v1_113832214_-1_6_Sue Gordon_2_12\"}\n{\"mention\": \"Sao Paulo\", \"polarity\": 0, \"from\": 84, \"to\": 93, \"sentence\": \"In the end, it was funny because we never expect these kinds of things to happen in Sao Paulo.\\\"\", \"id\": \"polusa_v1_113832465_-1_12_Sao Paulo_84_93\"}\n{\"mention\": \"we\", \"polarity\": 1, \"from\": 33, \"to\": 35, \"sentence\": \"In the end, it was funny because we never expect these kinds of things to happen in Sao Paulo.\\\"\", \"id\": \"polusa_v1_113832465_-1_12_lawyer Hugo Vecchiatto, who works on the 17th floor of an office building on Paulista Avenue in Sao Paulo_33_35\"}\n{\"mention\": \"Stephen Miller\", \"polarity\": -1, \"from\": 47, \"to\": 61, \"sentence\": \"President Donald Trump's senior policy advisor Stephen Miller was \\\"escorted\\\" off a CNN TV set in Washington on Sunday by the network's security officers following a contentious interview with Jake Tapper, CNN has said.\", \"id\": \"polusa_v1_113833129_-1_2_Top Trump advisor Stephen Miller \\\"_49_63\"}\n{\"mention\": \"CNN\", \"polarity\": 0, \"from\": 83, \"to\": 86, \"sentence\": \"President Donald Trump's senior policy advisor Stephen Miller was \\\"escorted\\\" off a CNN TV set in Washington on Sunday by the network's security officers following a contentious interview with Jake Tapper, CNN has said.\", \"id\": \"polusa_v1_113833129_-1_2_CNN_85_88\"}\n{\"mention\": \"Neal\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Neal said fresher, hotter lava could emerge because magma has been moving down Kilauea's rift zone toward the area where the volcano is erupting.\", \"id\": \"polusa_v1_113834047_-1_17_Hawaiian Volcano Observatory Scientist Tina Neal_0_5\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She said hotter, fresher and gassier magma can result in more voluminous lava flows.\", \"id\": \"polusa_v1_113834047_-1_18_Hawaiian Volcano Observatory Scientist Tina Neal_1_4\"}\n{\"mention\": \"Klobuchar\", \"polarity\": 0, \"from\": 9, \"to\": 18, \"sentence\": \"However, Klobuchar stressed that all candidates should be focused on their foremost priority: thwarting President Trump's reelection bid next year.\", \"id\": \"polusa_v1_113834074_-1_13_Amy Klobuchar_10_19\"}\n{\"mention\": \"Stormy Daniels'\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Stormy Daniels' lawyer Michael Avenatti did not comment if there are photos, texts or videos relating to her alleged relationship with Trump\", \"id\": \"polusa_v1_113835015_-1_1_Stormy Daniels'_0_17\"}\n{\"mention\": \"Clifford\", \"polarity\": -1, \"from\": 24, \"to\": 32, \"sentence\": \"WASHINGTON -- Stephanie Clifford, the adult film star otherwise known as Stormy Daniels who alleges she had an affair with President Trump, is offering to return the $130,000 the president's personal lawyer Michael Cohen paid her in exchange for silence on the subject.\", \"id\": \"polusa_v1_113835015_-1_2_Clifford_26_34\"}\n{\"mention\": \"Franken\", \"polarity\": -1, \"from\": 64, \"to\": 71, \"sentence\": \"Sanders joined the chorus of more than 30 lawmakers calling for Franken to resign from the Senate after previously saying it should be up to the people of Minnesota to decide his fate.\", \"id\": \"polusa_v1_113835270_-1_7_Franken_65_72\"}\n{\"mention\": \"Epstein\", \"polarity\": -1, \"from\": 30, \"to\": 37, \"sentence\": \"Hoffenberg told CBS News that Epstein was in charge of the illegal transfer and sale of bonds and investments out of United Diversified accounts.\", \"id\": \"polusa_v1_113835627_-1_48_Jeffrey Epstein_30_37\"}\n{\"mention\": \"our nation\", \"polarity\": 1, \"from\": 45, \"to\": 55, \"sentence\": \"Ryan and Rebecca, you embody the goodness of our nation.\", \"id\": \"polusa_v1_113836094_-1_273_a compassionate nation_45_55\"}\n{\"mention\": \"Ryan\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Ryan and Rebecca, you embody the goodness of our nation.\", \"id\": \"polusa_v1_113836094_-1_273_Ryan Holets_0_4\"}\n{\"mention\": \"Morgenthau\", \"polarity\": 1, \"from\": 31, \"to\": 41, \"sentence\": \"Over the next quarter-century, Morgenthau was elected another seven times as head of one of the nation's largest law offices, with 550 prosecutors and 700 other staffers.\", \"id\": \"polusa_v1_113836369_-1_39_Morgenthau_32_42\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 38, \"to\": 43, \"sentence\": \"As some Republicans grumbled that Mr. Trump caved, McConnell lashed out at Democrats for failing to give Trump any of the $5 billion that he wanted for the wall.\", \"id\": \"polusa_v1_113836991_-1_34_President Trump_39_44\"}\n{\"mention\": \"Labor Secretary Alex Acosta\", \"polarity\": -1, \"from\": 0, \"to\": 27, \"sentence\": \"Labor Secretary Alex Acosta came under fire for his handling of the Jeffrey Epstein case and ultimately resigned, saying his role in the matter a distraction from the economy's success and the Trump administration's achievements.\", \"id\": \"polusa_v1_113837081_-1_24_Labor Secretary Alex Acosta_0_27\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 25, \"to\": 28, \"sentence\": \"\\\"Absolutely it matters,\\\" she said.\", \"id\": \"polusa_v1_113839127_-1_13_Cheri Bustos_26_29\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump has made the stock market a key barometer of his success, pointing to its strong performance earlier this year as proof his policies are working.\", \"id\": \"polusa_v1_113840224_-1_5_Donald Trump_1_10\"}\n{\"mention\": \"Jeff Sessions\", \"polarity\": 1, \"from\": 40, \"to\": 53, \"sentence\": \"\\\"I join the people of Alabama in giving Jeff Sessions my deep respect and unwavering support.\\\"\", \"id\": \"polusa_v1_113841683_-1_18_Jeff Sessions_41_54\"}\n{\"mention\": \"Michael Bloomberg\", \"polarity\": 1, \"from\": 0, \"to\": 17, \"sentence\": \"Michael Bloomberg: Reasonably self-confident.\", \"id\": \"polusa_v1_113842502_-1_62_Michael Bloomberg's_1_18\"}\n{\"mention\": \"Pompeo on Iran\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Pompeo on Iran: \\\"President Trump does not want war\\\"\", \"id\": \"polusa_v1_113842654_-1_0_Pompeo on Iran_0_14\"}\n{\"mention\": \"Riehl\", \"polarity\": 0, \"from\": 28, \"to\": 33, \"sentence\": \"When deputies later return, Riehl again talks to at least one deputy through a closed door.\", \"id\": \"polusa_v1_113842673_-1_16_Matthew Riehl_29_34\"}\n{\"mention\": \"Jared Diamond\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"Jared Diamond is a professor at UCLA and a Pulitzer Prize winning author.\", \"id\": \"polusa_v1_113842743_-1_4_Jared Diamond_0_14\"}\n{\"mention\": \"Jerusalem\", \"polarity\": 0, \"from\": 110, \"to\": 119, \"sentence\": \"While the embassy move is delayed, Morrison said his government would establish a defense and trade office in Jerusalem and would also start looking for an appropriate site for the embassy.\", \"id\": \"polusa_v1_113842860_-1_6_west Jerusalem_111_120\"}\n{\"mention\": \"Democrats\", \"polarity\": -1, \"from\": 80, \"to\": 89, \"sentence\": \"Testifying before the Senate Judiciary Committee last week, Kavanaugh lambasted Democrats for their handling of the accusations against him, at one point turning a question back on Democratic Sen.\", \"id\": \"polusa_v1_113843484_-1_9_Democrats_80_89\"}\n{\"mention\": \"Homeland Security Secretary Kirstjen Nielsen\", \"polarity\": -1, \"from\": 103, \"to\": 147, \"sentence\": \"MARGARET BRENNAN: The president gave an interview this morning to Fox's Chris Wallace and he said that Homeland Security Secretary Kirstjen Nielsen needs to be much tougher on the border.\", \"id\": \"polusa_v1_113843703_-1_12_Homeland Security Secretary Kirstjen Nielsen_104_148\"}\n{\"mention\": \"Winterkorn\", \"polarity\": -1, \"from\": 0, \"to\": 10, \"sentence\": \"Winterkorn was charged with three counts of wire fraud and one of conspiring with other senior VW executives and employees to violate the Clean Air Act.\", \"id\": \"polusa_v1_113844462_-1_13_former CEO Martin Winterkorn_0_11\"}\n{\"mention\": \"Bill Nelson\", \"polarity\": 0, \"from\": 38, \"to\": 49, \"sentence\": \"Obama campaigns for Andrew Gillum and Bill Nelson in Florida - live stream\", \"id\": \"polusa_v1_113844599_-1_0_Bill Nelson_38_49\"}\n{\"mention\": \"Bill Nelson\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Bill Nelson, the three-time incumbent Democratic senator from Florida seeking his fourth term.\", \"id\": \"polusa_v1_113844599_-1_3_Bill Nelson_0_11\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 48, \"to\": 53, \"sentence\": \"His remarks come after media criticism that the Trump administration - the president as well as Tillerson and Mattis - had offered mixed messages as tension rose over North Korea's nuclear program.\", \"id\": \"polusa_v1_113845120_-1_6_President Trump_49_54\"}\n{\"mention\": \"Longshoreman Paul Moe\", \"polarity\": -1, \"from\": 0, \"to\": 21, \"sentence\": \"Longshoreman Paul Moe held one such job, earning $493,000 a year, until he was convicted of fraud and sentenced to federal prison in March.\", \"id\": \"polusa_v1_113847098_-1_21_Longshoreman Paul Moe_1_22\"}\n{\"mention\": \"Francis\", \"polarity\": 1, \"from\": 33, \"to\": 40, \"sentence\": \"\\\"Thank you for your generosity,\\\" Francis said.\", \"id\": \"polusa_v1_113847513_-1_36_Pope Francis_34_41\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 73, \"to\": 75, \"sentence\": \"Whitney said Castanenda lived in a Garden Grove apartment building where he stabbed two men during some kind of confrontation.\", \"id\": \"polusa_v1_113848457_-1_16_Zachary Castaneda_74_76\"}\n{\"mention\": \"\\\" Mr. Trump\", \"polarity\": 1, \"from\": 89, \"to\": 100, \"sentence\": \"\\\"We have 32,000 soldiers in South Korea, I would like to be able to bring them back home,\\\" Mr. Trump said in his press conference early Tuesday morning ET during the summit.\", \"id\": \"polusa_v1_113849233_-1_4_President Trump_90_101\"}\n{\"mention\": \"the Sacklers\", \"polarity\": 0, \"from\": 8, \"to\": 20, \"sentence\": \"Who are the Sacklers?\", \"id\": \"polusa_v1_113849571_-1_2_the Sacklers_10_22\"}\n{\"mention\": \"Perez\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Perez was arrested last month at the U.S.-Mexico border during a shopping trip, Wolf said.\", \"id\": \"polusa_v1_113849883_-1_10_Macrina Perez_0_6\"}\n{\"mention\": \"Warren\", \"polarity\": 0, \"from\": 315, \"to\": 321, \"sentence\": \"Some of the largest: Kohlberg, Kravis, Roberts & Co.'s 1989 purchase of RJR Nabiso, a deal that became a symbol of Wall Street greed; a $27 billion purchase of media company Clear Channel (now iHeartMedia) by Bain Capital and Thomas H. 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employees_1_3\"}\n{\"mention\": \"Bloomberg\", \"polarity\": 1, \"from\": 22, \"to\": 31, \"sentence\": \"Before this donation, Bloomberg had already donated a total of $1.5 billion to the university.\", \"id\": \"polusa_v1_115847567_-1_12_Bloomberg_23_32\"}\n{\"mention\": \"the university\", \"polarity\": 0, \"from\": 79, \"to\": 93, \"sentence\": \"Before this donation, Bloomberg had already donated a total of $1.5 billion to the university.\", \"id\": \"polusa_v1_115847567_-1_12_the university_80_94\"}\n{\"mention\": \"House Speaker Paul Ryan\", \"polarity\": -1, \"from\": 169, \"to\": 192, \"sentence\": \"On Saturday -- hours after Donald Trump tweeted to his followers, “Watch @JudgeJeanine on @FoxNews tonight at 9:00 P.M.” – Jeanine Pirro opened her show with a call for House Speaker Paul Ryan to step down. http://abcn.ws/2o6hFaJ\\nSPEED READ with ABC's ADAM KELSEY\\nROGER STONE: ‘I’VE HAD NO CONTACTS OR COLLUSION’ WITH RUSSIANS.\", \"id\": \"polusa_v1_115848162_-1_29_House 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displayed Eleanor Roosevelt’s penchant for shamelessly flouting the wishes of her husband, as Roosevelt did with her campaign to end lynching, half the country and cable news could have erupted in faux outrage.\", \"id\": \"polusa_v1_115868271_-1_8_Michelle Obama_4_9\"}\n{\"mention\": \"her husband\", \"polarity\": -1, \"from\": 88, \"to\": 99, \"sentence\": \"Had Obama displayed Eleanor Roosevelt’s penchant for shamelessly flouting the wishes of her husband, as Roosevelt did with her campaign to end lynching, half the country and cable news could have erupted in faux outrage.\", \"id\": \"polusa_v1_115868271_-1_8_her husband’s_88_99\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She was wearing a thong with a lace front.”\", \"id\": \"polusa_v1_115868518_-1_7_defense attorney Elizabeth O’Connell_0_3\"}\n{\"mention\": \"Omar\", \"polarity\": -1, \"from\": 62, \"to\": 66, \"sentence\": \"Attacks on Israel\\nWHAT TRUMP SAID: On Monday, Trump also said Omar \\\"says horrible things about Israel, hates Israel, hates Jews, it's very simple.\\\"\", \"id\": \"polusa_v1_115868970_-1_32_Omar_63_67\"}\n{\"mention\": \"Butina\", \"polarity\": 1, \"from\": 39, \"to\": 45, \"sentence\": \"J.D. Gordon was among the people Maria Butina befriended during her time in D.C.\", \"id\": \"polusa_v1_115869592_-1_1_Ms. Butina_41_47\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 91, \"to\": 93, \"sentence\": \"For the past decade, \\\"she has been harassed on a regular basis when she goes to airports,\\\" he said.\", \"id\": \"polusa_v1_115870821_-1_47_hard-line President Mahmoud Ahmadinejad_92_94\"}\n{\"mention\": \"Senate\", \"polarity\": -1, \"from\": 60, \"to\": 66, \"sentence\": \"NEED TO READ with ABC News' Daksha Sthipam\\nTrump criticizes Senate GOP for not doing \\\"their job\\\" in Obamacare fight.\", \"id\": \"polusa_v1_115872639_-1_27_Senate_61_67\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 48, \"to\": 50, \"sentence\": \"Not because I agreed with every policy position he took, but because, like Senator Kennedy, he was guided by a loyalty to public service and the American people.\", \"id\": \"polusa_v1_115873329_-1_11_McCain_48_50\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 8, \"to\": 10, \"sentence\": \"\\\"I know he's a busy man.\", \"id\": \"polusa_v1_115873895_-1_50_Debich_8_10\"}\n{\"mention\": \"Rozi Mehmet\", \"polarity\": 1, \"from\": 31, \"to\": 42, \"sentence\": \"———\\nFEARLESS 'PAWNS'\\nLike Ali, Rozi Mehmet wanted to do something to help his people fight Chinese oppression.\", \"id\": \"polusa_v1_115874320_-1_84_Rozi Mehmet_32_43\"}\n{\"mention\": \"Lowe\", \"polarity\": 1, \"from\": 175, \"to\": 179, \"sentence\": \"The bonuses, which will be given out to both part-time and full-time hourly workers across all its U.S. facilities including distribution centers, will be paid in addition to Lowe's long-standing, store-level bonus program.\", \"id\": \"polusa_v1_115874785_-1_6_Lowe_176_180\"}\n{\"mention\": \"Godbolt\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Godbolt's stepfather-in-law, Vincent Mitchell, says the slayings \\\"all stemmed from domestic violence.\\\"\", \"id\": 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GO!\\\"\", \"id\": \"polusa_v1_115877943_-1_5_Vice President Mike Pence_51_62\"}\n{\"mention\": \"Sentsov\", \"polarity\": -1, \"from\": 15, \"to\": 22, \"sentence\": \"In the photos, Sentsov looks gaunt and weak, noticeably reduced from the 220 pounds he weighed when he entered prison.\", \"id\": \"polusa_v1_115878064_-1_13_Sentsov_15_22\"}\n{\"mention\": \"Sentsov\", \"polarity\": -1, \"from\": 15, \"to\": 22, \"sentence\": \"In the photos, Sentsov looks gaunt and weak, noticeably reduced from the 220 pounds he weighed when he entered prison.\", \"id\": \"polusa_v1_115878064_-1_13_Oleg Sentsov_15_22\"}\n{\"mention\": \"Ashton\", \"polarity\": 1, \"from\": 69, \"to\": 75, \"sentence\": \"The Leeds Family\\nThis drug could provide new hope for thousands like Ashton.\", \"id\": \"polusa_v1_115878583_-1_23_Ashton_70_76\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 3, \"to\": 5, \"sentence\": \"So he slaughtered the animal instead of his son.\", \"id\": 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pupils by locking a classroom door when he was struck by bullets allegedly fired by 19-year-old Nikolas Cruz.\", \"id\": \"polusa_v1_115884352_-1_3_19-year-old Nikolas Cruz_184_208\"}\n{\"mention\": \"Hyten\", \"polarity\": -1, \"from\": 124, \"to\": 129, \"sentence\": \"Last week, Spletstoser detailed her sexual assault allegations in a New York Times interview where she claimed that in 2017 Hyten came to her hotel room and \\\"pulled her to him and kissed her on the lips while pressing himself against her,\\\" and ejaculated.\", \"id\": \"polusa_v1_115885383_-1_5_Hyten_125_130\"}\n{\"mention\": \"Obamacare\", \"polarity\": -1, \"from\": 28, \"to\": 37, \"sentence\": \"The Latest: Trump says 'let Obamacare implode'\", \"id\": \"polusa_v1_115886648_-1_0_Obamacare_28_37\"}\n{\"mention\": \"Barr\", \"polarity\": 0, \"from\": 105, \"to\": 109, \"sentence\": \"Other Democratic presidential hopefuls like South Bend, Indiana Mayor Pete Buttigieg, say the release of Barr's summary underscores the point that the party can never fully rely on the famed prosecutor's mysterious report as the sole rationale for denying Trump a second term in office.\", \"id\": \"polusa_v1_115887199_-1_54_U.S. Attorney General William Barr_106_110\"}\n{\"mention\": \"Bauman\", \"polarity\": 0, \"from\": 217, \"to\": 223, \"sentence\": \"\\\"In a liquid modern life there are no permanent bonds, and any that we take up for a time must be tied loosely so that they can be untied again, as quickly and as effortlessly as possible, when circumstances change,\\\" Bauman wrote.\", \"id\": \"polusa_v1_115888446_-1_12_Bauman_218_224\"}\n{\"mention\": \"Poland\", \"polarity\": 0, \"from\": 3, \"to\": 9, \"sentence\": \"In Poland, he was a controversial figure in some circles.\", \"id\": \"polusa_v1_115888446_-1_14_Poland_4_10\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 11, \"to\": 13, \"sentence\": \"In Poland, he was a controversial figure in some circles.\", \"id\": 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4, 1946 pogrom in the town of Kielce — where a mob and secret security forces killed at least 40 Jews and two Poles who were defending them — Rosen said that Hlond \\\"did not condemn the pogrom nor urge Poles to stop murdering Jews.\", \"id\": \"polusa_v1_115894413_-1_31_the pogrom_204_214\"}\n{\"mention\": \"Yusuf\", \"polarity\": -1, \"from\": 29, \"to\": 34, \"sentence\": \"As condition of his release, Yusuf is barred from social media and accessing content with extremist views.\", \"id\": \"polusa_v1_115895188_-1_5_Yusuf_30_35\"}\n{\"mention\": \"his release\", \"polarity\": 0, \"from\": 16, \"to\": 27, \"sentence\": \"As condition of his release, Yusuf is barred from social media and accessing content with extremist views.\", \"id\": \"polusa_v1_115895188_-1_5_21-year-old Abdullahi Mohamud Yusuf's release to his family Thursday_17_28\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 156, \"to\": 161, \"sentence\": \"\\\"Nobody is above the law in this country and that 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Secretary-General Antonio Guterres_0_9\"}\n{\"mention\": \"Manigault Newman\", \"polarity\": -1, \"from\": 117, \"to\": 133, \"sentence\": \"As the most prominent African-American in the White House and a self-professed advocate for African-American issues, Manigault Newman took the blame for this inaction.\", \"id\": \"polusa_v1_115896860_-1_24_Omarosa Manigault Newman_118_134\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He escapes back under some rock, and a few news cycles later it's on to a new enemy and new crisis.\\\"\", \"id\": \"polusa_v1_115897359_-1_126_Osama Bin Laden_0_2\"}\n{\"mention\": \"George\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"George has played a prominent role in the creation of the commission, according to a source familiar with the plans for the commission.\", \"id\": \"polusa_v1_115898063_-1_12_Princeton professor Robert George_0_7\"}\n{\"mention\": \"the commission\", \"polarity\": 1, \"from\": 54, 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interviewer called the Russian leader \\\"a killer,\\\" Trump said the United States has many of them.\", \"id\": \"polusa_v1_115903739_-1_2_Putin_42_56\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 22, \"sentence\": \"President Donald Trump said he respects Vladimir Putin, and when an interviewer called the Russian leader \\\"a killer,\\\" Trump said the United States has many of them.\", \"id\": \"polusa_v1_115903739_-1_2_Trump_0_24\"}\n{\"mention\": \"America\", \"polarity\": 1, \"from\": 89, \"to\": 96, \"sentence\": \"While saying he would not critique \\\"every utterance\\\" by Trump, McConnell said he thinks \\\"America's exceptional, America is different, we don't operate in any way the way the Russians do.\", \"id\": \"polusa_v1_115903739_-1_34_America_90_97\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 56, \"to\": 61, \"sentence\": \"While saying he would not critique \\\"every utterance\\\" by Trump, McConnell said he thinks \\\"America's exceptional, America is different, we don't operate in any way the way the Russians do.\", \"id\": \"polusa_v1_115903739_-1_34_Trump_57_62\"}\n{\"mention\": \"her\", \"polarity\": -1, \"from\": 85, \"to\": 88, \"sentence\": \"Four months later, the 19-year-old was arrested for allegedly setting small fires on her former college campus in St. Paul in what prosecutors say was a self-proclaimed act of jihad.\", \"id\": \"polusa_v1_115904184_-1_5_Tnuza Jamal Hassan_86_89\"}\n{\"mention\": \"Maduro\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Maduro spoke Saturday in the capital of Caracas during a celebration of the National Guard's 81 anniversary.\", \"id\": \"polusa_v1_115905126_-1_5_Venezuelan President Nicolas Maduro_0_7\"}\n{\"mention\": \"Hurricane Irma\", \"polarity\": -1, \"from\": 169, \"to\": 183, \"sentence\": \"2. 'IT'S SAD WHEN YOU COME HOME TO THIS'\\nHundreds of people across St. Martin, an island shared by the Dutch and French, are trying to rebuild the lives they had before Hurricane Irma hit.\", \"id\": \"polusa_v1_115905594_-1_4_Irma_170_184\"}\n{\"mention\": \"Charlie\", \"polarity\": 1, \"from\": 32, \"to\": 39, \"sentence\": \"\\\"It was three years after I met Charlie and bonded a fast friendship that I learned he was a Medal of Honor recipient\\\" when Liteky told him about his plans to renounce the medal, Olive said.\", \"id\": \"polusa_v1_115906714_-1_17_Charlie_32_39\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 12, \"to\": 17, \"sentence\": \"Trump fired Flynn early in his term as national security adviser for allegedly misleading Vice President Mike Pence about his contacts with Russian officials.\", \"id\": \"polusa_v1_115908474_-1_12_Flynn_13_18\"}\n{\"mention\": \"Poroshenko\", \"polarity\": -1, \"from\": 110, \"to\": 120, \"sentence\": \"Former Georgian president Mikhail Saakashvili, who leads a Ukrainian opposition party, said at the rally that Poroshenko was responsible for \\\"poverty and humiliation.\\\"\", \"id\": \"polusa_v1_115908637_-1_3_President Petro Poroshenko_111_121\"}\n{\"mention\": \"Pelosi\", \"polarity\": -1, \"from\": 81, \"to\": 87, \"sentence\": \"RADDATZ: -- traded some very big jabs, one (ph) about the State of the Union but Pelosi calling on the president to delay that.\", \"id\": \"polusa_v1_115909542_-1_412_Speaker Pelosi_82_88\"}\n{\"mention\": \"the president\", \"polarity\": -1, \"from\": 130, \"to\": 143, \"sentence\": \"So why does Nancy Pelosi or any other Democrat on Capitol Hill, coming off of this election where they just won big, look at what the president has put on the table and say anything but \\\"no way?\\\"\", \"id\": \"polusa_v1_115909542_-1_425_President Trump_130_143\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 24, \"to\": 26, \"sentence\": \"It's one of the reasons he tells users never to take drugs alone.\", \"id\": \"polusa_v1_115910200_-1_29_overdose survivor Richie Webber_24_26\"}\n{\"mention\": \"Tudor\", \"polarity\": 0, \"from\": 9, \"to\": 14, \"sentence\": \"However, Tudor then received a call from a Southeastern employee who informed her that \\\"Southeastern’s Vice President for Academic Affairs, Dr. Douglas McMillan, had inquired whether Dr. Tudor could be fired because her 'transgender lifestyle' offended his religious beliefs,\\\" the lawsuit states.\", \"id\": \"polusa_v1_115911497_-1_10_Tudor_9_14\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 21, \"to\": 26, \"sentence\": \"Interested in Donald Trump?\", \"id\": \"polusa_v1_115912256_-1_4_— Donald J. 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2006 when he got caught driving with a fake driver’s license, and another time in 2010 following traffic citation, his lawyer said.\", \"id\": \"polusa_v1_115932242_-1_16_\\\" the 30-year-old Berrones_1_3\"}\n{\"mention\": \"Adam Koenig\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Adam Koenig from the northern Kentucky suburbs of Cincinnati, where Bevin has some of his strongest support.\", \"id\": \"polusa_v1_115932580_-1_38_Adam Koenig_0_11\"}\n{\"mention\": \"Murphy\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Murphy has argued that a Guadagno’s governorship would represent a continuation of Christie’s tenure, while Guadagno has pointed to moments of disagreement with her boss to attempt to distance herself from the two-term governor and former Republican presidential primary candidate.\", \"id\": \"polusa_v1_115932661_-1_18_Murphy_0_6\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 5, \"to\": 8, \"sentence\": \"Lock him up, lock him up, lock 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142, \"to\": 149, \"sentence\": \"Add Interest\\nJason Sullivan, a social media specialist who worked for Stone’s political action committee in 2016, received two subpoenas from Mueller last week, Knut Johnson, a lawyer for Sullivan, told ABC News.\", \"id\": \"polusa_v1_115937474_-1_5_Robert Mueller_142_149\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 13, \"to\": 18, \"sentence\": \"AP\\nPresident Trump also blamed the Democrats for inflating the numbers, a statement that is also not supported by any facts.\", \"id\": \"polusa_v1_115938164_-1_22_Donald Trump_14_19\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 21, \"to\": 24, \"sentence\": \"But Yellen said that she was grateful for the Fed career she did have which covered not only a four-year term as Fed chair but also serving as Fed vice chair for four years before that and also service as president of the Fed's San Francisco regional bank.\", \"id\": \"polusa_v1_115938245_-1_10_Federal Reserve Chair Janet 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\"polusa_v1_115940821_-1_12_Manchin_97_104\"}\n{\"mention\": \"Sharif\", \"polarity\": -1, \"from\": 119, \"to\": 125, \"sentence\": \"The manipulation is seen as seeking to prevent the Pakistan Muslim League, the party of disgraced Prime Minister Nawaz Sharif, from returning to power, while giving a shot at running the country to former cricket star Imran Khan and his Pakistan Tehreek-e-Insaf party, or PTI.\", \"id\": \"polusa_v1_115941489_-1_6_Sharif_120_126\"}\n{\"mention\": \"The cabinet secretary\", \"polarity\": -1, \"from\": 13, \"to\": 34, \"sentence\": \"Add Interest\\nThe cabinet secretary came under sharp questioning at the hearing last month and was called out on Twitter for mishearing the housing term “REO” as an OREO cookie.\", \"id\": \"polusa_v1_115941603_-1_5_Housing Secretary Ben Carson_13_34\"}\n{\"mention\": \"the hearing\", \"polarity\": 0, \"from\": 67, \"to\": 78, \"sentence\": \"Add Interest\\nThe cabinet secretary came under sharp questioning at the hearing last month and was called out on Twitter for mishearing the housing term “REO” as an OREO cookie.\", \"id\": \"polusa_v1_115941603_-1_5_the hearing_67_78\"}\n{\"mention\": \"Salvini\", \"polarity\": 0, \"from\": 19, \"to\": 26, \"sentence\": \"In a Twitter post, Salvini wrote he wanted to host Putin and Trump next.\", \"id\": \"polusa_v1_115941775_-1_26_Salvini_19_26\"}\n{\"mention\": \"The Body Shop\", \"polarity\": 1, \"from\": 6, \"to\": 19, \"sentence\": \"While The Body Shop became known for its activist efforts against animal testing, Natura is known for environmental and social efforts.\", \"id\": \"polusa_v1_115941959_-1_6_Body Shop_6_19\"}\n{\"mention\": \"Natura\", \"polarity\": 1, \"from\": 82, \"to\": 88, \"sentence\": \"While The Body Shop became known for its activist efforts against animal testing, Natura is known for environmental and social efforts.\", \"id\": \"polusa_v1_115941959_-1_6_Brazil's Natura_82_88\"}\n{\"mention\": \"McDonald\", \"polarity\": -1, \"from\": 8, \"to\": 16, \"sentence\": \"He said McDonald apologized for what occurred and for embarrassing the department.\", \"id\": \"polusa_v1_115942775_-1_13_Robert McDonald_9_17\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said McDonald apologized for what occurred and for embarrassing the department.\", \"id\": \"polusa_v1_115942775_-1_13_Gwinnett County Police Chief Butch Ayers_1_3\"}\n{\"mention\": \"McDonald\", \"polarity\": 0, \"from\": 41, \"to\": 49, \"sentence\": \"\\\"It shouldn't have happened,\\\" Ayers said McDonald told him.\", \"id\": \"polusa_v1_115942775_-1_14_Robert McDonald_42_50\"}\n{\"mention\": \"Zhang\", \"polarity\": 0, \"from\": 148, \"to\": 153, \"sentence\": \"According to an affidavit filed in federal court, Christensen was under surveillance Thursday when agents overheard him explaining he had kidnapped Zhang.\", \"id\": \"polusa_v1_115943049_-1_13_Professor Lance Cooper_149_154\"}\n{\"mention\": \"Zhang\", \"polarity\": 0, \"from\": 101, \"to\": 106, \"sentence\": \"One belonging to Christensen was first seen in an apartment complex parking lot June 12 — days after Zhang went missing — and investigators questioned him.\", \"id\": \"polusa_v1_115943049_-1_31_Professor Lance Cooper_101_106\"}\n{\"mention\": \"Le Pen\", \"polarity\": -1, \"from\": 4, \"to\": 10, \"sentence\": \"But Le Pen won't win the decisive May 7 runoff unless large numbers break with past voting habits and, like Evrard, abandon traditional, even life-long, allegiances.\", \"id\": \"polusa_v1_115943964_-1_11_presidential candidate Marine Le Pen_4_10\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 132, \"to\": 137, \"sentence\": \"He also expressed deep appreciation for his \\\"symbolic and timely visit immediately after the meetings at the G-20 in Hamburg\\\" where Trump met with Putin.\", \"id\": \"polusa_v1_115944764_-1_6_Donald Trump_132_137\"}\n{\"mention\": \"Putin\", \"polarity\": 0, \"from\": 147, \"to\": 152, \"sentence\": \"He also expressed deep appreciation for his \\\"symbolic and timely visit immediately after the meetings at the G-20 in Hamburg\\\" where Trump met with Putin.\", \"id\": \"polusa_v1_115944764_-1_6_Vladimir Putin_147_152\"}\n{\"mention\": \"Carter\", \"polarity\": 0, \"from\": 124, \"to\": 130, \"sentence\": \"\\\"The Joe Biden in my picture is a close friend helping someone get through a big day, for which I will always be grateful,\\\" Carter wrote.\", \"id\": \"polusa_v1_115945078_-1_11_Carter_125_131\"}\n{\"mention\": \"Pope Francis\", \"polarity\": 0, \"from\": 4, \"to\": 16, \"sentence\": \"Add Pope Francis as an interest to stay up to date on the latest Pope Francis news, video, and analysis from ABC News.\", \"id\": \"polusa_v1_115945237_-1_4_Pope Francis_4_16\"}\n{\"mention\": \"President Uhuru Kenyatta\", \"polarity\": -1, \"from\": 228, \"to\": 252, \"sentence\": \"However, Mahama says election observers don't have the capacity to investigate allegations by opposition leader Raila Odinga that hackers infiltrated the Kenyan election commission's database and manipulated results in favor of President Uhuru Kenyatta.\", \"id\": \"polusa_v1_115945653_-1_4_President Uhuru Kenyatta_229_253\"}\n{\"mention\": \"the Kenyan election commission\", \"polarity\": -1, \"from\": 150, \"to\": 180, \"sentence\": \"However, Mahama says election observers don't have the capacity to investigate allegations by opposition leader Raila Odinga that hackers infiltrated the Kenyan election commission's database and manipulated results in favor of President Uhuru Kenyatta.\", \"id\": \"polusa_v1_115945653_-1_4_the Kenyan election commission_151_181\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said Peoples “has not shown any remorse,” but added, \\\"When we took him into custody, he did not behave in any manner that would be considered bizarre to us.\\\"\", \"id\": \"polusa_v1_115945763_-1_16_Jim Choi of the Sunnyvale Department of Public Safety_1_3\"}\n{\"mention\": \"Madonna\", \"polarity\": 1, \"from\": 75, \"to\": 82, \"sentence\": \"Like John Paul, the Argentinian-born Francis is exceedingly devoted to the Madonna, thanks in large part to the strong role that Marian devotions play in the popular piety of Latin American Catholics.\", \"id\": \"polusa_v1_115946796_-1_18_\\\"the real Madonna_76_83\"}\n{\"mention\": \"Jetter\", \"polarity\": -1, \"from\": 1, \"to\": 7, \"sentence\": \"(Jetter eventually pleaded guilty to public consumption of marijuana, and was fined $100.\", \"id\": \"polusa_v1_115947083_-1_40_Jetter_2_8\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He was a big man and he had a big heart to go with it,\\\" Smith said.\", \"id\": \"polusa_v1_115947408_-1_23_Peters_2_4\"}\n{\"mention\": \"Nasheed\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Nasheed's release would have allowed him to contest a presidential election later this 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adventurer, VanHecke had planned a spring break trip to drive from Texas to the Grand Canyon.\", \"id\": \"polusa_v1_115954199_-1_16_the Grand Canyon_178_194\"}\n{\"mention\": \"Senate Majority Leader Mitch McConnell\", \"polarity\": 1, \"from\": 13, \"to\": 51, \"sentence\": \"Add Interest\\nSenate Majority Leader Mitch McConnell thanked President Donald Trump on Wednesday for helping keep the Senate in Republican hands though Democrats won the House.\", \"id\": \"polusa_v1_115956189_-1_5_Senate Majority Leader Mitch McConnell_13_51\"}\n{\"mention\": \"Assad\", \"polarity\": -1, \"from\": 94, \"to\": 99, \"sentence\": \"April 4, 2017: President Donald Trump issues a statement saying that the \\\"heinous\\\" actions of Assad's government are the direct result of Obama administration's \\\"weakness and irresolution.\\\"\", \"id\": \"polusa_v1_115957742_-1_38_President Bashar Assad_95_100\"}\n{\"mention\": \"Arthur\", \"polarity\": -1, \"from\": 106, \"to\": 112, \"sentence\": \"After her conviction, she changed her story and testified that she had discussed killing her husband with Arthur, who wore a wig and painted his face in an attempt to look like a black man.\", \"id\": \"polusa_v1_115958277_-1_18_Arthur_106_112\"}\n{\"mention\": \"Barrow\", \"polarity\": 1, \"from\": 81, \"to\": 87, \"sentence\": \"Jammeh has resisted strong international pressure for him to step down and allow Barrow to take office and allow a peaceful resolution to Gambia's crisis.\", \"id\": \"polusa_v1_115958928_-1_7_Adama Barrow_82_88\"}\n{\"mention\": \"Gambia\", \"polarity\": -1, \"from\": 138, \"to\": 144, \"sentence\": \"Jammeh has resisted strong international pressure for him to step down and allow Barrow to take office and allow a peaceful resolution to Gambia's crisis.\", \"id\": \"polusa_v1_115958928_-1_7_Gambia_139_145\"}\n{\"mention\": \"Braun\", \"polarity\": -1, \"from\": 50, \"to\": 55, \"sentence\": \"Federal Department of Transportation records show Braun's operation has been cited 55 times since September 2015 for unsafe driving violations and 41 times for truck driver \\\"hours of service\\\" violations.\", \"id\": \"polusa_v1_115960218_-1_25_Mike Braun_51_56\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She appeared tired from swimming into the current and was even moving backward as other whales sprinted by her.\", \"id\": \"polusa_v1_115961996_-1_13_Hanson_0_3\"}\n{\"mention\": \"Boudou\", \"polarity\": -1, \"from\": 20, \"to\": 26, \"sentence\": \"In a separate case, Boudou was arrested in early November 2017 on charges of money laundering and illicit association.\", \"id\": \"polusa_v1_115962366_-1_10_former Vice President Amado Boudou_21_27\"}\n{\"mention\": \"Boudou\", \"polarity\": -1, \"from\": 43, \"to\": 49, \"sentence\": \"The decision is a hard fall from grace for Boudou, 55, who also served as economy minister during the 2007-2015 administration of President Cristina Fernandez, and who was the first sitting Argentine vice president to face such charges.\", \"id\": \"polusa_v1_115962366_-1_4_former Vice President Amado Boudou_44_50\"}\n{\"mention\": \"Moore\", \"polarity\": -1, \"from\": 42, \"to\": 47, \"sentence\": \"Long a bane to establishment Republicans, Moore is thumbing his nose at calls by Senate Majority Leader Mitch McConnell and other GOP members of Congress to drop out of the campaign, and accusing them of trying to \\\"steal\\\" the race from his loyal insurgents.\", \"id\": \"polusa_v1_115962521_-1_13_Moore_43_48\"}\n{\"mention\": \"Macron\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Macron campaigned on promises of cleaning up French politics, and says he will require ministers to sign a commitment to \\\"integrity and morality.\\\"\", \"id\": \"polusa_v1_115962681_-1_13_French President Emmanuel Macron_0_7\"}\n{\"mention\": \"Patterson\", \"polarity\": 1, \"from\": 5, \"to\": 14, \"sentence\": \"When Patterson said that he grew up on Poe Place, Bailly told him that he remembered the street well because he helped deliver a baby there 27 years ago when he was a \\\"rookie cop,\\\" according to police.\", \"id\": \"polusa_v1_115963047_-1_6_Trooper Michael Patterson_6_15\"}\n{\"mention\": \"McConnell\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"McConnell, who has expressed confidence in Mueller's work, said the Senate's role in the investigation is being performed by the chamber's Intelligence committee.\", \"id\": \"polusa_v1_115963354_-1_9_McConnell_1_10\"}\n{\"mention\": \"Mueller\", \"polarity\": 1, \"from\": 43, \"to\": 50, \"sentence\": \"McConnell, who has expressed confidence in Mueller's work, said the Senate's role in the investigation is being performed by the chamber's Intelligence committee.\", \"id\": \"polusa_v1_115963354_-1_9_Robert Mueller_44_51\"}\n{\"mention\": \"Walter\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Walter is the 63rd member of Virginia State Police to be killed 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\"to\": 115, \"sentence\": \"\\\"I was trying to let her know that the military profession in the United States is an honorable and noble one,\\\" Lin told Cmdr.\", \"id\": \"polusa_v1_115969742_-1_16_Edward C. 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reports, policy staff for the tax-writing committee and members of the Trump transition team discussed a proposal in Trump's childcare plan that would allow parents to deduct some childcare expenses from their income taxes. http://abcn.ws/2jpFnwa\\nIN CASE YOU MISSED IT\\nPRESIDENT OBAMA SURPRISES VICE PRESIDENT BIDEN WITH PRESIDENTIAL MEDAL OF FREEDOM.\", \"id\": \"polusa_v1_115988046_-1_46_http://abcn.ws/2hiExTh\\nTRUMP TEAM_89_114\"}\n{\"mention\": \"President-elect Donald Trump\", \"polarity\": -1, \"from\": 51, \"to\": 79, \"sentence\": \"Al Franken of Minnesota says he doesn't trust what President-elect Donald Trump says about the role that Russia played during the 2016 presidential campaign.\", \"id\": \"polusa_v1_115988046_-1_9_DONALD TRUMP_51_79\"}\n{\"mention\": \"the 2016 presidential campaign\", \"polarity\": 0, \"from\": 126, \"to\": 156, \"sentence\": \"Al Franken of Minnesota says he doesn't trust what President-elect Donald Trump says about the role that Russia played 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\"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She eventually told family members, including her children when they became teens.\", \"id\": \"polusa_v1_115993020_-1_25_Corfman_0_3\"}\n{\"mention\": \"Gomez\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Gomez says fake news poses \\\"a direct threat to our democracy.\\\"\", \"id\": \"polusa_v1_115993688_-1_8_Assemblyman Jimmy Gomez_1_6\"}\n{\"mention\": \"Ted Cruz\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Ted Cruz and Democratic Congressman Beto O'Rourke faced off in an at-times-testy debate in San Antonio Tuesday evening, as both men sought to paint their opponent as the wrong choice to represent the nation's third-largest state.\", \"id\": \"polusa_v1_115995234_-1_7_Cruz_0_8\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 17, \"to\": 19, \"sentence\": \"Late last night, he issued what many online are calling a \\\"bizarre\\\" statement, condemning recent reports.\", \"id\": 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but, \\\"Others without rehabilitation would have continued to suffer substantially.\\\"\", \"id\": \"polusa_v1_116012876_-1_27_Smith_105_110\"}\n{\"mention\": \"Smith\", \"polarity\": 0, \"from\": 4, \"to\": 9, \"sentence\": \"But Smith, who heads the Center for Brain Injury and Repair and leads the team that has examined 21 of the affected individuals, says they still do not know what kind of exposure is responsible, with microwaves one of a handful of possibilities.\", \"id\": \"polusa_v1_116012876_-1_8_Smith_5_10\"}\n{\"mention\": \"The company\", \"polarity\": 1, \"from\": 0, \"to\": 11, \"sentence\": \"The company says in a statement that its mission is to make roads safer.\", \"id\": \"polusa_v1_116013373_-1_16_Waymo_1_12\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 62, \"to\": 84, \"sentence\": \"Burciaga says no matter what, immigrants deserve respect from President Donald Trump's administration.\", \"id\": \"polusa_v1_116013453_-1_39_President 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behind them\\nAnother Murdoch property, Fox News, has been vociferously pro-Trump, often supplying information that winds up in the president's tweets.\", \"id\": \"polusa_v1_116942156_-1_25_Rupert Murdoch_67_74\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He and I worked together for so many years, for a long time, and I only wish him the best moving forward.\\\"\", \"id\": \"polusa_v1_116943626_-1_5_Bush_1_3\"}\n{\"mention\": \"Baquet\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Baquet said on Sunday that despite the president's attacks, the newspaper's mission is now \\\"clearer than it's ever been.\\\"\", \"id\": \"polusa_v1_116948101_-1_12_Times executive editor Dean Baquet_1_7\"}\n{\"mention\": \"Fox\", \"polarity\": 0, \"from\": 79, \"to\": 82, \"sentence\": \"Additionally, Buffett is a longtime Democrat who backed Hillary Clinton, while Fox has firmly aligned itself with President Trump.\", \"id\": 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\"id\": \"polusa_v1_131723539_-1_0_Ed Whelan_0_9\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 12, \"to\": 14, \"sentence\": \"And the man he pushed for the job was none other than his own close friend, and former colleague, Brett Kavanaugh.\", \"id\": \"polusa_v1_131723539_-1_39_Ed Whelan_12_14\"}\n{\"mention\": \"Tom Cotton:\\n“\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"Tom Cotton:\\n“We do not recall the President saying these comments specifically but what he did call out was the imbalance in our current immigration system, which does not protect American workers and our national interest,” [the senators] said in a statement.\", \"id\": \"polusa_v1_131724089_-1_30_Tom Cotton:\\n“_0_13\"}\n{\"mention\": \"Cohen\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"On Wednesday, Cohen’s own attorney, David Schwartz, said explicitly on CNN that Trump was not aware of the NDA or the $130,000 payment when it was made.\", \"id\": 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Sanders speaks during a rally at Howard University on Monday in Washington, D.C. Alex Wong/Getty Images\\nAs the clear front-runner for the Democratic nomination, Joe Biden knows that he’s all but guaranteed to face attacks from several of his rivals at the first primary debate next month.\", \"id\": \"polusa_v1_131728375_-1_3_Bernie Sanders_0_14\"}\n{\"mention\": \"Biden\", \"polarity\": 0, \"from\": 29, \"to\": 34, \"sentence\": \"It’s simply that Sanders and Biden may not share the stage at all in June.\", \"id\": \"polusa_v1_131728375_-1_6_Joe Biden_29_34\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 148, \"to\": 152, \"sentence\": \"During the course of our conversation, which has been edited and condensed for clarity, we discussed the effect Scott Pruitt had on EPA morale, the Bush administration’s role in undermining faith in the science of climate change, and the myth that environmental protection and a good economy cannot go hand in hand.\", \"id\": \"polusa_v1_131728681_-1_9_Bush_148_152\"}\n{\"mention\": \"Schumer\", \"polarity\": -1, \"from\": 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but that it amounted to “the kind of inappropriate behavior that makes many women feel uncomfortable and unequal in the workplace.”\", \"id\": \"polusa_v1_131730016_-1_41_Former Vice President Joe Biden_21_26\"}\n{\"mention\": \"Kim Jong Un\", \"polarity\": 0, \"from\": 30, \"to\": 41, \"sentence\": \"BREAKING: President Trump and Kim Jong Un just shook hands ahead of their historic summit.\", \"id\": \"polusa_v1_131730135_-1_2_Kim Jong Un_32_43\"}\n{\"mention\": \"Singapore\", \"polarity\": 0, \"from\": 66, \"to\": 75, \"sentence\": \"WATCH: President Trump and Kim Jong Un meet at historic summit in Singapore. https://t.co/MmLKv5K6vV pic.twitter.com/rlVlIPEYLn — NBC News (@NBCNews) June 12, 2018\\n\\\"It's my honor -- we will have a terrific relationship, no doubt,\\\" President Trump says as he sits down with Kim Jong Un. https://t.co/SBcHAGxnM4 pic.twitter.com/47Jw6TdbNu — NBC News (@NBCNews) June 12, 2018\\n“The old prejudices and practices worked as obstacles on our way forward, but we’ve overcome all of them and we are here today,” Kim Jong Un says as he sits down with President Trump in Singapore. pic.twitter.com/2N9opWxsZK — NBC News (@NBCNews) June 12, 2018\\nTrump and Kim conclude their first face-to-face meeting of the day:\\nJUST IN: President Trump and Kim emerge from first meeting.\", \"id\": \"polusa_v1_131730135_-1_6_Singapore_67_76\"}\n{\"mention\": \"a complaint against Trump and Trump’s presidential campaign\", \"polarity\": -1, \"from\": 68, \"to\": 127, \"sentence\": \"On Jan. 22, campaign finance reform organization Common Cause filed a complaint against Trump and Trump’s presidential campaign, accusing them of violating federal election law in relation to the Daniels payment.\", \"id\": \"polusa_v1_131730283_-1_16_a complaint against Trump and Trump’s presidential campaign_69_128\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 10, \"to\": 15, \"sentence\": \"Get ready Comey, because they will be coming, nice and new and “smart!”\", 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people of Biafra wey say dem wan comot from Nigeria\\nFederal high court for Nigeria don postpone di trial of di leader of di Indigenous People of Biafra (IPOB) Nnamdi Kanu go 5 December 2017 because di judge ontop di mata justice Binta Nyako no show.\", \"id\": \"polusa_v1_18005560_-1_2_Nnamdi Kanu_45_56\"}\n{\"mention\": \"Salt\", \"polarity\": -1, \"from\": 16, \"to\": 20, \"sentence\": \"Kristopher John Salt, 27, had three adults and six children, including a one-year-old, hiding in his van.\", \"id\": \"polusa_v1_18006436_-1_1_Salt_18_22\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 108, \"to\": 111, \"sentence\": \"Shark, whose real name is Amy Louise Billings, is a prominent singer-songwriter in Australia best known for her songs Adore and I Said Hi.\", \"id\": \"polusa_v1_18012268_-1_7_Amy Shark_109_112\"}\n{\"mention\": \"Pastor Biodun\", \"polarity\": -1, \"from\": 64, \"to\": 77, \"sentence\": \"Women's rights activist Laila St Matthew-Daniel also criticised Pastor 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\"sentence\": \"\\\"Sarah was an energetic character, full of life and joy.\", \"id\": \"polusa_v1_18045339_-1_9_Sarah_2_7\"}\n{\"mention\": \"Abbot Xuecheng\", \"polarity\": 0, \"from\": 79, \"to\": 93, \"sentence\": \"It said the \\\"fabricated evidence\\\" had \\\"illegal intentions to maliciously frame Abbot Xuecheng\\\".\", \"id\": \"polusa_v1_18055080_-1_9_Abbot Xuecheng's_80_94\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She was arrested in Iran April 2016 and later sentenced for allegedly plotting against the Iranian government.\", \"id\": \"polusa_v1_18061790_-1_33_Mrs Zaghari-Ratcliffe_1_4\"}\n{\"mention\": \"Iran\", \"polarity\": 0, \"from\": 20, \"to\": 24, \"sentence\": \"She was arrested in Iran April 2016 and later sentenced for allegedly plotting against the Iranian government.\", \"id\": \"polusa_v1_18061790_-1_33_Iran_21_25\"}\n{\"mention\": \"Winston Churchill\", \"polarity\": 0, \"from\": 43, \"to\": 60, \"sentence\": 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\"id\": \"polusa_v1_18088798_-1_147_London_97_103\"}\n{\"mention\": \"Cecília Apalai\", \"polarity\": 1, \"from\": 36, \"to\": 50, \"sentence\": \"This would cost a lot of money, but Cecília Apalai says it's essential because indigenous people are obliged to travel to cities to take advantage of their rights as Brazilian citizens.\", \"id\": \"polusa_v1_18090234_-1_53_Cecília Apalai_37_51\"}\n{\"mention\": \"indigenous people\", \"polarity\": 1, \"from\": 79, \"to\": 96, \"sentence\": \"This would cost a lot of money, but Cecília Apalai says it's essential because indigenous people are obliged to travel to cities to take advantage of their rights as Brazilian citizens.\", \"id\": \"polusa_v1_18090234_-1_53_indigenous people_80_97\"}\n{\"mention\": \"Uganda\", \"polarity\": -1, \"from\": 119, \"to\": 125, \"sentence\": \"Julius Kaggwa was born intersex, which made for a confusing, isolating and sometimes dangerous childhood growing up in Uganda.\", \"id\": \"polusa_v1_18090420_-1_1_Uganda_121_127\"}\n{\"mention\": \"\\\" Mr Campbell\", \"polarity\": 0, \"from\": 101, \"to\": 114, \"sentence\": \"\\\"He thinks, probably rightly, that the country has decided it will not put Jeremy Corbyn into office,\\\" Mr Campbell continued.\", \"id\": \"polusa_v1_18093557_-1_10_\\\" Mr Campbell_102_115\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He eventually plead guilty ahead of his trial.\", \"id\": \"polusa_v1_18096846_-1_6_McGilloway_1_3\"}\n{\"mention\": \"Maupin\", \"polarity\": 0, \"from\": 102, \"to\": 108, \"sentence\": \"I've always wanted a gay man to play Michael Tolliver, for instance, he's sort of my alter ego,\\\" says Maupin.\", \"id\": \"polusa_v1_18097042_-1_21_Maupin_102_108\"}\n{\"mention\": \"Maupin\", \"polarity\": 1, \"from\": 126, \"to\": 132, \"sentence\": \"Younger generations of LGBT people may not be aware of Tales of the City existing prior to this Netflix series launching, but Maupin 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\"sentence\": \"Image caption Viriginia student Malika Fowler says blackface is really disrespectful and the recent stories have shocked her\\nReverend Sharpton gave a rousing speech, drawing claps, cheers and a standing ovation, as he called for Mr Northam to step down.\", \"id\": \"polusa_v1_18259065_-1_20_Reverend Sharpton_126_143\"}\n{\"mention\": \"Mr Northam\", \"polarity\": -1, \"from\": 74, \"to\": 84, \"sentence\": \"A right-leaning independent, and a Democrat respectively, they both think Mr Northam should resign, especially because of his lack of clarity on his involvement.\", \"id\": \"polusa_v1_18259065_-1_51_Mr Northam_74_84\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 50, \"to\": 53, \"sentence\": \"A medical report reportedly said Richards \\\"forced her to drink so he could control her\\\" - a Caid representative said details could not be disclosed.\", \"id\": \"polusa_v1_18268013_-1_47_Chochi_50_53\"}\n{\"mention\": \"Jewel\", \"polarity\": 0, \"from\": 3, \"to\": 8, \"sentence\": \"Mr Jewel's father, Babul Hossain, was outspoken about his support for his son's marriage and filed a petition against the law.\", \"id\": \"polusa_v1_18278048_-1_12_Shoaib Hossain Jewel_4_9\"}\n{\"mention\": \"Steve Baker\", \"polarity\": 0, \"from\": 125, \"to\": 136, \"sentence\": \"Video\\nThose who wish to launch a formal challenge to Theresa May's leadership are \\\"pretty close\\\" to getting 48 letters, says Steve Baker.\", \"id\": \"polusa_v1_18287613_-1_2_Baker_127_138\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 140, \"to\": 142, \"sentence\": \"\\\"I believe that this is a real opportunity to re-set our relationship with the European Union and to have one based on democratic consent,\\\" he said.\", \"id\": \"polusa_v1_18301697_-1_12_Aberavon's Stephen Kinnock_141_143\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 32, \"to\": 34, \"sentence\": \"\\\"By that I mean the family knew he had been a soldier, but it wasn't really talked of, 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174, \"sentence\": \"McCrae Dowless, an operative working on Harris’ behalf, is accused of paying people to collect completed absentee ballots from voters ― something that violates North Carolina law.\", \"id\": \"polusa_v1_3949582_-1_12_North Carolina_160_174\"}\n{\"mention\": \"Harris\", \"polarity\": -1, \"from\": 40, \"to\": 46, \"sentence\": \"McCrae Dowless, an operative working on Harris’ behalf, is accused of paying people to collect completed absentee ballots from voters ― something that violates North Carolina law.\", \"id\": \"polusa_v1_3949582_-1_12_Harris_40_46\"}\n{\"mention\": \"Murphy\", \"polarity\": 0, \"from\": 17, \"to\": 23, \"sentence\": \"DeVos first told Murphy that the 1982 Supreme Court decision in Plyler v.\", \"id\": \"polusa_v1_3949850_-1_5_Chris Murphy_17_23\"}\n{\"mention\": \"Russian President Vladimir Putin\", \"polarity\": -1, \"from\": 95, \"to\": 127, \"sentence\": \"Trump has been assailed by Democratic and GOP lawmakers for a disastrous press 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Youth,” featuring 10 British activists reflecting on the stigma they regularly experience because of their gender identity.\", \"id\": \"polusa_v1_3960151_-1_14_Graf_11_13\"}\n{\"mention\": \"Kahlil\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Kahlil began to learn English and a whole new world of artistic influences began to inspire him.\", \"id\": \"polusa_v1_3960396_-1_34_Kahlil_0_6\"}\n{\"mention\": \"Kahlil\", \"polarity\": 1, \"from\": 10, \"to\": 16, \"sentence\": \"In Jesus, Kahlil saw an all-embracing figure, and he was enraptured by his character.\", \"id\": \"polusa_v1_3960396_-1_50_Kahlil_11_17\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 3, \"to\": 5, \"sentence\": \"If he fails that test, he’s failing the presidency, he’s failing the American people, he’s failing the Constitution and failing all of us.”\", \"id\": \"polusa_v1_3960647_-1_15_Dillon_3_5\"}\n{\"mention\": \"it\", \"polarity\": 1, \"from\": 58, \"to\": 60, \"sentence\": \"“[The commission] will not be a cure for the problem, but it will go a long way towards holding those who abuse their powers accountable, and towards deterring those who may be tempted to break the rules,” wrote John Raphling, a senior researcher at Human Rights Watch, in a letter to Cuomo in support of the commission.\", \"id\": \"polusa_v1_3960761_-1_18_The commission_59_61\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 23, \"to\": 35, \"sentence\": \"Our selected president Donald Trump isn't only delusional, but his behavior also demonstrates the man chosen, not by Americans but by the outmoded Electoral College, has no inhibitions about shameful conduct.\", \"id\": \"polusa_v1_3960888_-1_4_Donald Trump_23_35\"}\n{\"mention\": \"Our\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"Our selected president Donald Trump isn't only delusional, but his behavior also demonstrates the man chosen, not by Americans but by the outmoded Electoral College, has no 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bullying, bombastic nature toward a more presidential demeanor, it is the Republican Party en masse that has pivoted.\", \"id\": \"polusa_v1_3966847_-1_28_the Republican Party_124_144\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 28, \"to\": 33, \"sentence\": \"But instead of the promised Trump pivot away from his bullying, bombastic nature toward a more presidential demeanor, it is the Republican Party en masse that has pivoted.\", \"id\": \"polusa_v1_3966847_-1_28_Donald Trump_28_33\"}\n{\"mention\": \"Milo Yiannopoulos\", \"polarity\": 1, \"from\": 65, \"to\": 82, \"sentence\": \"Robert Mercer Sells Stake In Breitbart News, Recants Support For Milo Yiannopoulos\", \"id\": \"polusa_v1_3967064_-1_0_Milo Yiannopoulos_65_82\"}\n{\"mention\": \"Moore\", \"polarity\": 0, \"from\": 116, \"to\": 121, \"sentence\": \"That night, in the back row of a theater a few blocks from the state capitol, I watched the first U.S. screening of Moore’s latest movie, SiCKO.\", \"id\": 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Trump is a really bad character, an awful role model for his kids, the worst example of how America creates and protects this class of robber barons.\", \"id\": \"polusa_v1_3985246_-1_27_That laid-off, middle-aged, white Rust Belt guy_16_18\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 6, \"to\": 15, \"sentence\": \"Photo\\nMr. Trump has barely paid lip service to the promotion of universal human rights, and experts say his warm embrace of hard-line leaders like President Rodrigo Duterte of the Philippines, whose antidrug drive has killed thousands of his own citizens without due process, has only encouraged their worst excesses.\", \"id\": \"polusa_v1_3992132_-1_10_Mr. Trump_7_16\"}\n{\"mention\": \"Mr. Netanyahu\", \"polarity\": -1, \"from\": 0, \"to\": 13, \"sentence\": \"Mr. Netanyahu is almost certain to try to persuade his coalition partners to pass a law granting him immunity from prosecution.\", \"id\": \"polusa_v1_3992856_-1_8_Benjamin 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him.\", \"id\": \"polusa_v1_4003199_-1_4_Stephen Wynn_1_9\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 23, \"to\": 26, \"sentence\": \"Democratic voters view him in overwhelmingly favorable terms, as a thoroughly qualified commander-in-chief and an emblem of the Obama administration.\", \"id\": \"polusa_v1_4004167_-1_5_Biden_23_26\"}\n{\"mention\": \"Mr. Rubio\", \"polarity\": 1, \"from\": 30, \"to\": 39, \"sentence\": \"Whether they think so or not, Mr. Rubio and Ms. Trump are lighting the way toward an effective system of paid family leave a quarter-century after we enacted unpaid leave during the first Clinton administration.\", \"id\": \"polusa_v1_4005414_-1_36_Mr. Rubio_31_40\"}\n{\"mention\": \"Ms. Abrams\", \"polarity\": 1, \"from\": 44, \"to\": 54, \"sentence\": \"Ms. Winfrey was energetic in her praise for Ms. Abrams and her policy proposals, but she focused her most impassioned remarks on voting rights, delivering a pointed rebuke to people who might willfully stay 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He studied at the Kiev Higher Engineering Radio-Technical College of the Soviet Air Force.\", \"id\": \"polusa_v1_4050274_-1_11_Colonel Petrov_57_59\"}\n{\"mention\": \"Mr. Kilimnik\", \"polarity\": -1, \"from\": 43, \"to\": 55, \"sentence\": \"Mr. Gates, Mr. Manafort’s deputy, believed Mr. Kilimnik to be a “spy.”\", \"id\": \"polusa_v1_4050489_-1_11_Mr. Kilimnik_43_55\"}\n{\"mention\": \"the data\", \"polarity\": 0, \"from\": 28, \"to\": 36, \"sentence\": \"Mr. Gates sent Mr. Kilimnik the data regularly, deleting the WhatsApp messages after he did so.\", \"id\": \"polusa_v1_4050489_-1_14_“internal polling data” private to the campaign with Mr. Kilimnik_28_36\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 124, \"to\": 131, \"sentence\": \"After his July 27 comment, the report states, Mr. Trump “asked individuals affiliated with his Campaign to find the deleted Clinton emails” — including Michael Flynn.\", \"id\": \"polusa_v1_4050489_-1_2_Clinton_126_133\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He swept to re-election in 1936 with 61 percent of the vote, winning all but two states in one of the biggest landslides in American history, and his approval ratings remained high.\", \"id\": \"polusa_v1_4052760_-1_36_Roosevelt_0_2\"}\n{\"mention\": \"a campaign against the conservative Democrats\", \"polarity\": -1, \"from\": 45, \"to\": 90, \"sentence\": \"So Roosevelt put together a team to organize a campaign against the conservative Democrats.\", \"id\": \"polusa_v1_4052760_-1_42_a campaign against the conservative Democrats_45_90\"}\n{\"mention\": \"President Niinisto\", \"polarity\": 0, \"from\": 32, \"to\": 50, \"sentence\": \"But the closest competition for President Niinisto came from Pekka Haavisto, a gay, left-wing Green who reached a second round against Mr. Niinisto in 2012 — a campaign that enchanted liberal-minded celebrities and electrified younger voters, especially in Helsinki.\", \"id\": \"polusa_v1_4053357_-1_2_President Niinisto_34_52\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 61, \"to\": 64, \"sentence\": \"Confronting one of the most serious leadership challenges of his career, Mr. McConnell used all the tools at his disposal — special benefits for some states, appeals to party loyalty, plain old arm-twisting — to win the vote by the narrowest margin possible.\", \"id\": \"polusa_v1_4053812_-1_27_the president_62_65\"}\n{\"mention\": \"Mayor Bill de Blasio\", \"polarity\": -1, \"from\": 0, \"to\": 20, \"sentence\": \"Mayor Bill de Blasio offered no apology for the missives, which provided an unvarnished look at his criticisms of his staff and the media in New York City.\", \"id\": \"polusa_v1_4056024_-1_1_Mayor Bill de Blasio_0_22\"}\n{\"mention\": \"Mr. Pappas\", \"polarity\": 1, \"from\": 7, \"to\": 17, \"sentence\": \"Should Mr. Pappas win in November, he would be the state’s first openly gay representative in Congress.\", \"id\": \"polusa_v1_4056729_-1_12_Chris Pappas_7_17\"}\n{\"mention\": \"former President George W. 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Bush’s_125_141\"}\n{\"mention\": \"Mr. Goodfriend\", \"polarity\": 1, \"from\": 65, \"to\": 79, \"sentence\": \"The White House said in a statement that it continued to support Mr. Goodfriend.\", \"id\": \"polusa_v1_4082392_-1_26_Marvin Goodfriend_66_80\"}\n{\"mention\": \"Ms. Alberto\", \"polarity\": 1, \"from\": 0, \"to\": 11, \"sentence\": \"Ms. Alberto has established herself as one of the city’s rising female trail runners after a string of podium finishes, including winning a 27.9-mile ultramarathon in January.\", \"id\": \"polusa_v1_4083234_-1_5_Ms. Alberto_0_11\"}\n{\"mention\": \"Fox\", \"polarity\": -1, \"from\": 22, \"to\": 25, \"sentence\": \"James Murdoch thought Fox News was toxic to the company.\", \"id\": \"polusa_v1_4084296_-1_41_James_23_26\"}\n{\"mention\": \"Mr. Weinstein\", \"polarity\": -1, \"from\": 47, \"to\": 60, \"sentence\": \"Ms. McGowan reached a $100,000 settlement with Mr. Weinstein in 1997 after a hotel room incident at the Sundance Film Festival, and in recent days has been vocal in her support of women who have stepped forward to reveal that the producer sexually harassed them or worse.\", \"id\": \"polusa_v1_4085034_-1_12_Mr. Weinstein_48_61\"}\n{\"mention\": \"Mr. Frawley\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Mr. Frawley described a different, perhaps more Australian, sensibility.\", \"id\": \"polusa_v1_4089726_-1_12_Mr. Frawley_1_12\"}\n{\"mention\": \"Bernie Sanders\", \"polarity\": 1, \"from\": 4, \"to\": 18, \"sentence\": \"How Bernie Sanders Learned to Walk the Line\", \"id\": \"polusa_v1_4090270_-1_1_Bernie Sanders_4_18\"}\n{\"mention\": \"Mr. Bolton\", \"polarity\": -1, \"from\": 0, \"to\": 10, \"sentence\": \"Mr. Bolton also was accused of attempting to inflate the dangers of Syria’s biological and nuclear weapons programs, by trying to sneak exaggerated assertions into speeches and congressional testimony before being called on it by intelligence officials.\", \"id\": \"polusa_v1_4091030_-1_5_John Bolton_1_11\"}\n{\"mention\": \"Mr. Bolton\", \"polarity\": -1, \"from\": 0, \"to\": 10, \"sentence\": \"Mr. Bolton also was accused of attempting to inflate the dangers of Syria’s biological and nuclear weapons programs, by trying to sneak exaggerated assertions into speeches and congressional testimony before being called on it by intelligence officials.\", \"id\": \"polusa_v1_4091030_-1_5_President Bush_1_11\"}\n{\"mention\": \"Roy Moore\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Roy Moore faces criticism from Drudge Report, Sean Hannity\", \"id\": \"polusa_v1_4093540_-1_0_Roy Moore_0_9\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 77, \"to\": 82, \"sentence\": \"President Donald Trump and China President Xi Jinping (Photo: Andy Wong, AP)\\nTrump announced Sunday on Twitter that he intended to increase tariffs on $200 billion in Chinese goods and impose new levies on another $350 billion in imports because he was angry about the pace of the talks and at what he said was China’s attempts at backtracking on several commitments it had made during months of negotiations.\", \"id\": \"polusa_v1_4095571_-1_10_President Trump_78_83\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He just wrote me a beautiful letter.\", \"id\": \"polusa_v1_4095571_-1_16_President Trump_1_3\"}\n{\"mention\": \"a beautiful letter\", \"polarity\": 1, \"from\": 18, \"to\": 36, \"sentence\": \"\\\"He just wrote me a beautiful letter.\", \"id\": \"polusa_v1_4095571_-1_16_a beautiful letter_18_36\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 27, \"to\": 32, \"sentence\": \"By the end of this circus, Trump was practically mewling, begging for Putin’s approval, saying that Putin’s denials were “extremely powerful and strong,” almost in a kind of weirdly erotic tone of admiration.\", \"id\": \"polusa_v1_4096279_-1_45_Donald Trump_28_33\"}\n{\"mention\": \"Putin\", \"polarity\": -1, \"from\": 70, \"to\": 75, \"sentence\": 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John Kelly_47_54\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 3, \"to\": 6, \"sentence\": \"In his first year, Trump has delivered fiery speeches to campaign rallies around the country.\", \"id\": \"polusa_v1_4099478_-1_18_President Obama_4_7\"}\n{\"mention\": \"Italy\", \"polarity\": -1, \"from\": 63, \"to\": 68, \"sentence\": \"CLOSE Amanda Knox is getting $20,000 in financial damages from Italy for failing to provide her with legal assistance and a translator in 2007.\", \"id\": \"polusa_v1_4099539_-1_9_Italy_64_69\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 94, \"to\": 99, \"sentence\": \"“Being president has cost me a fortune — a tremendous fortune like you’ve never seen before,” Trump said to reporters last year.\", \"id\": \"polusa_v1_4099972_-1_15_Donald Trump_95_100\"}\n{\"mention\": \"Lamb\", \"polarity\": 1, \"from\": 69, \"to\": 73, \"sentence\": \"To win consistently again, Democrats must understand what helped put Lamb over the top in that corner of Trump Country.\", \"id\": \"polusa_v1_4100796_-1_36_Conor Lamb_69_73\"}\n{\"mention\": \"Heyer\", \"polarity\": 1, \"from\": 75, \"to\": 80, \"sentence\": \"Alfred Wilson, her supervisor of five years at Miller Law Group, described Heyer as “strong, outspoken, loving.”\", \"id\": \"polusa_v1_4101796_-1_100_Heyer_76_81\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 15, \"to\": 18, \"sentence\": \"Alfred Wilson, her supervisor of five years at Miller Law Group, described Heyer as “strong, outspoken, loving.”\", \"id\": \"polusa_v1_4101796_-1_100_her_16_19\"}\n{\"mention\": \"Heyer\", \"polarity\": 1, \"from\": 39, \"to\": 44, \"sentence\": \"But marchers gathered anyway, honoring Heyer at the downtown cross-street where she was killed\\nJason Kessler, the local organizer of Saturday’s Unite the Right rally, tried to hold a news conference earlier Sunday in front of Charlottesville City Hall — and it quickly descended into chaos.\", \"id\": \"polusa_v1_4101796_-1_13_Heyer_39_44\"}\n{\"mention\": \"Heyer\", \"polarity\": 1, \"from\": 18, \"to\": 23, \"sentence\": \"Friends described Heyer as a woman with a generous spirit and strong sense of justice.\", \"id\": \"polusa_v1_4101796_-1_97_Heyer_19_24\"}\n{\"mention\": \"Tenney\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Tenney's Democratic opponent, state Assemblyman Anthony Brindisi, was graded an \\\"F.\\\" Brindisi has gone against the majority of Democrats in the Assembly and voted against the SAFE Act, which is not favored by gun owners.\", \"id\": \"polusa_v1_4103516_-1_26_\\\"Congresswoman Claudia Tenney_0_6\"}\n{\"mention\": \"Evers\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Evers formed The Historic Preservation Society Inc. days after the judgement in what he said was an effort to “preserve historic monuments that are threatened with destruction.”\", \"id\": \"polusa_v1_4105137_-1_24_Greg Evers_1_6\"}\n{\"mention\": \"Jack 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and so I think that's what we're really seeing, even though things are hitting the fan right now, we're seeing people activate and educate themselves.\\\"\", \"id\": \"polusa_v1_4111567_-1_11_Alexandria Ocasio-Cortez_1_4\"}\n{\"mention\": \"we\", \"polarity\": 1, \"from\": 126, \"to\": 128, \"sentence\": \"She continued: \\\"But you know, times of great challenge can also bring out the best in people, too, and so I think that's what we're really seeing, even though things are hitting the fan right now, we're seeing people activate and educate themselves.\\\"\", \"id\": \"polusa_v1_4111567_-1_11_we_127_129\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": -1, \"from\": 9, \"to\": 18, \"sentence\": \"Fighting Kavanaugh's confirmation is hopeless\\nIn the eyes of many Democratic party activists, of course, votes for confirmation by the three endangered senators and a few others somewhat less vulnerable would be selling out for the cheapened coin of incumbency.\", \"id\": \"polusa_v1_4113215_-1_31_Judge Brett Kavanaugh outside Sen._10_19\"}\n{\"mention\": \"Jim Acosta\", \"polarity\": -1, \"from\": 77, \"to\": 87, \"sentence\": \"— Anne Frank Center (@AnneFrankCenter) August 2, 2017\\nStephen Miller calling Jim Acosta ignorant on live TV is officially the best thing I've seen this week.\", \"id\": \"polusa_v1_4113667_-1_27_Jim Acosta_77_87\"}\n{\"mention\": \"media professor Mira Sotirovic\", \"polarity\": 1, \"from\": 98, \"to\": 128, \"sentence\": \"The eight-week course, scheduled for the second half of the fall 2018 semester, will be taught by media professor Mira Sotirovic for both journalism and non-journalism students at the university's Urbana-Champaign campus.\", \"id\": \"polusa_v1_4114400_-1_5_media professor Mira Sotirovic_99_129\"}\n{\"mention\": \"House Speaker Nancy Pelosi\", \"polarity\": -1, \"from\": 70, \"to\": 96, \"sentence\": \"CLOSE\\nWhite House counselor Kellyanne Conway is taking verbal jabs at House Speaker Nancy Pelosi 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18, \"to\": 23, \"sentence\": \"That is something Putin has been loath to do since the Syrian leader is one of his few allies in the Middle East.\", \"id\": \"polusa_v1_4216529_-1_15_Putin_18_23\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She eventually spent five days in jail for refusing to follow court orders.\", \"id\": \"polusa_v1_4216832_-1_12_Matthew Barzun_0_3\"}\n{\"mention\": \"Mariah Carey\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Mariah Carey knew nothing about this.\", \"id\": \"polusa_v1_4217579_-1_13_Mariah Carey_0_12\"}\n{\"mention\": \"Harry Potter\", \"polarity\": 1, \"from\": 43, \"to\": 55, \"sentence\": \"USA TODAY\\nThe Internet is 9¾ obsessed with Harry Potter today\\nThanks, Harry, for making Muggles everywhere feel old.\", \"id\": \"polusa_v1_4218292_-1_17_Harry Potter_43_55\"}\n{\"mention\": \"USA TODAY\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"USA TODAY\\nThe Internet is 9¾ obsessed with Harry Potter today\\nThanks, Harry, for making Muggles everywhere feel old.\", \"id\": \"polusa_v1_4218292_-1_17_USA TODAY_0_10\"}\n{\"mention\": \"Harry Potter\", \"polarity\": 1, \"from\": 46, \"to\": 58, \"sentence\": \"And this magical thing happens when you type \\\"Harry Potter\\\" into Facebook.\", \"id\": \"polusa_v1_4218292_-1_22_Harry Potter_46_58\"}\n{\"mention\": \"Hogg\", \"polarity\": 0, \"from\": 97, \"to\": 101, \"sentence\": \"\\\"The apology ... was kind of expected, especially after so many of her advertisers dropped out,\\\" Hogg said.\", \"id\": \"polusa_v1_4220142_-1_26_Hogg_97_101\"}\n{\"mention\": \"Apuron\", \"polarity\": -1, \"from\": 22, \"to\": 28, \"sentence\": \"Archbishop Anthony S. 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\"sentence\": \"More: President Donald Trump on Anthony Scaramucci: He was 'totally incapable of handling' White House job\\nMore: Anthony Scaramucci: Replace Donald Trump as Republican nominee in 2020\\nMore: Scaramucci on Trump: 'Very clear that it’s impossible for him to win'\\nTrump has recently escalated his rhetorical war with his former staffer and has called him \\\"totally incapable of handling\\\" his White House job.\", \"id\": \"polusa_v1_4221104_-1_12_WASHINGTON – President Donald Trump_205_210\"}\n{\"mention\": \"Anthony Scaramucci\", \"polarity\": -1, \"from\": 32, \"to\": 50, \"sentence\": \"More: President Donald Trump on Anthony Scaramucci: He was 'totally incapable of handling' White House job\\nMore: Anthony Scaramucci: Replace Donald Trump as Republican nominee in 2020\\nMore: Scaramucci on Trump: 'Very clear that it’s impossible for him to win'\\nTrump has recently escalated his rhetorical war with his former staffer and has called him \\\"totally incapable of 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she felt only about half the patients she saw at Hanson's clinic had legitimate needs for oxycodone, which she estimated made up 65% of all her prescriptions.\", \"id\": \"polusa_v1_4222396_-1_26_Rachel McCauley_0_15\"}\n{\"mention\": \"Driscoll\", \"polarity\": -1, \"from\": 34, \"to\": 42, \"sentence\": \"To the DEA, those numbers suggest Driscoll is \\\"likely prescribing Oxycodone to patients without a legitimate medical purpose.\\\"\", \"id\": \"polusa_v1_4222396_-1_36_Julie Driscoll_35_43\"}\n{\"mention\": \"Brown\", \"polarity\": 0, \"from\": 110, \"to\": 115, \"sentence\": \"\\\"She stayed on the ground the whole time — never saw him, just saw his boots as he walked around the church,\\\" Brown said.\", \"id\": \"polusa_v1_4222809_-1_24_David Brown_111_116\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 99, \"to\": 101, \"sentence\": \"Grassley said the president should refrain from nominating a justice during campaign season and if he does, the Senate should refuse to consider the nomination\\nRead more commentary:\\nConservatives are already packing the courts.\", \"id\": \"polusa_v1_4223374_-1_12_President Barack Obama_99_101\"}\n{\"mention\": \"Grassley\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Grassley, meanwhile, is dodging responsibility for keeping his word.\", \"id\": \"polusa_v1_4223374_-1_34_Grassley_0_9\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 7, \"to\": 10, \"sentence\": \"I wish him and his family all the best.\\\"\", \"id\": \"polusa_v1_4226506_-1_26_Ducey_7_10\"}\n{\"mention\": \"Ducey\", \"polarity\": 0, \"from\": 51, \"to\": 56, \"sentence\": \"Other names have been mentioned as well, including Ducey's former chief-of-staff, Kirk Adams, and state Treasurer Eileen Klein.\", \"id\": \"polusa_v1_4226506_-1_36_Ducey_52_57\"}\n{\"mention\": \"Koch\", \"polarity\": -1, \"from\": 14, \"to\": 18, \"sentence\": \"The globalist Koch Brothers, who have become a total joke in real Republican circles, are against 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\"polarity\": -1, \"from\": 23, \"to\": 28, \"sentence\": \"Nixon referred back to Cuomo's recent comment that America \\\"was never that great,\\\" which drew a rebuke from Trump.\", \"id\": \"polusa_v1_4230790_-1_16_Cuomo_24_29\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 63, \"to\": 66, \"sentence\": \"He'd just taken a bottle full of antidepressant pills, he told her.\", \"id\": \"polusa_v1_4230846_-1_70_Sandy Metzmeier_63_66\"}\n{\"mention\": \"Kraft\", \"polarity\": 0, \"from\": 198, \"to\": 203, \"sentence\": \"#DemDebates#CNNDebate@KSMKidScoop#BehindTheScenespic.twitter.com/0Nj0auy6Tb — Nico Maounis (@nicomaounis) July 31, 2019\\nWhen asked what animal she would take with her to Washington, Williamson told Kraft, \\\"I love cats but I had a dog when I was a child.\", \"id\": \"polusa_v1_4231813_-1_13_Jeffrey Kraft_198_203\"}\n{\"mention\": \"Delaware\", \"polarity\": 0, \"from\": 148, \"to\": 156, \"sentence\": \"The News Journal\\nAfter graduating from Archmere 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1, \"from\": 77, \"to\": 86, \"sentence\": \"Earlier Saturday, Trump praised Senate Republicans for their work in getting Kavanaugh confirmed and said he believes a speech he made earlier this week attacking the credibility of accuser Christine Blasey Ford helped generate support for the embattled nominee.\", \"id\": \"polusa_v1_4233698_-1_27_Kavanaugh_78_87\"}\n{\"mention\": \"Monday\", \"polarity\": 0, \"from\": 92, \"to\": 98, \"sentence\": \"I’m just so happy that I and my family have finally had justice in this case,\\\" Godfrey said Monday.\", \"id\": \"polusa_v1_4234648_-1_10_Monday_92_98\"}\n{\"mention\": \"Paul Ryan\", \"polarity\": 1, \"from\": 1, \"to\": 10, \"sentence\": \"“Paul Ryan is a leader.\", \"id\": \"polusa_v1_4235345_-1_17_House speaker Paul Ryan_1_10\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 18, \"to\": 23, \"sentence\": \"Also on Thursday: Trump attacked McConnell, Clapper and spelling in general, while the Secret Service still struggled to get 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\"Turkish president Recep Tayyip Erdoğan\", \"polarity\": 0, \"from\": 119, \"to\": 157, \"sentence\": \"Both Kurz and Strache have railed against some members of the Turkish community in Austria, particularly supporters of Turkish president Recep Tayyip Erdoğan.\", \"id\": \"polusa_v1_4282018_-1_14_Turkish president Recep Tayyip Erdoğan_120_158\"}\n{\"mention\": \"Santos\", \"polarity\": -1, \"from\": 1, \"to\": 7, \"sentence\": \"“Santos is facing local charges for assault and other offenses.\", \"id\": \"polusa_v1_4282255_-1_5_Santos_1_7\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She added: “I would much rather, from the standpoint of handicapping, be Democrats than Republicans today.\", \"id\": \"polusa_v1_4282661_-1_13_Would-be Speaker Nancy Pelosi_1_4\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 216, \"to\": 221, \"sentence\": \"His comments came after the two outlets on Saturday published an article alleging the Texas migrant 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\"id\": \"polusa_v1_4288968_-1_11_Mohandas Karamchand Gandhi_86_88\"}\n{\"mention\": \"Hyten\", \"polarity\": -1, \"from\": 128, \"to\": 133, \"sentence\": \"The witness said that after she was fired and escorted out of the building in March 2018, there were rumors that she threatened Hyten and that his security team had to increase measures, especially when attending events that Spletstoser could possibly attend.\", \"id\": \"polusa_v1_4289463_-1_74_General Hyten_129_134\"}\n{\"mention\": \"Zapatero\", \"polarity\": 0, \"from\": 349, \"to\": 357, \"sentence\": \"That deal collapsed as Maduro refused to give in power, hold new presidential elections, free the nation’s hundreds of political prisoners, or cease deploying the nation’s military to attack unarmed civilians.\\nadvertisement\\nThe Herald notes that Freddy Guevara, the opposition-run National Assembly’s first vice president, announced on Twitter that Zapatero shared breakfast with López at his home, where he is currently under 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\"polarity\": -1, \"from\": 35, \"to\": 41, \"sentence\": \"The group, which repeatedly called Weldon a “racist,” then tried to throw his hat on the ground.\", \"id\": \"polusa_v1_4326467_-1_6_University of Florida student Daniel Weldon_35_41\"}\n{\"mention\": \"Pete Davidson\", \"polarity\": 0, \"from\": 92, \"to\": 105, \"sentence\": \"The congressman-elect also spoke about the recent comments made by Saturday Night Live host Pete Davidson, in which he called Crenshaw a “hitman in a porno movie.”\", \"id\": \"polusa_v1_4326579_-1_26_Pete Davidson_93_106\"}\n{\"mention\": \"Husby\", \"polarity\": -1, \"from\": 16, \"to\": 21, \"sentence\": \"Dagli described Husby as having self-appointed “morality police” who attempt to control women’s behaviour in the area.\", \"id\": \"polusa_v1_4326829_-1_13_Husby_16_21\"}\n{\"mention\": \"Rasmussen\", \"polarity\": 0, \"from\": 190, \"to\": 199, \"sentence\": \"The claims that President Donald Donald Trump is a traitor are made sincerely, not for 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hangups.\", \"id\": \"polusa_v1_4327644_-1_17_Keisling_1_9\"}\n{\"mention\": \"Bannon\", \"polarity\": 0, \"from\": 60, \"to\": 66, \"sentence\": \"Reporting on Monday’s rally, Axios quoted a source close to Bannon who said, “Steve is coming to Alabama to support President Trump against the Washington establishment and Mitch McConnell.”\", \"id\": \"polusa_v1_4327752_-1_7_Steve Bannon_61_67\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 21, \"to\": 23, \"sentence\": \"Indeed, if anything, he was more clear-eyed than the Bush administration about the long-term commitment that the war entailed; as he said, “I don’t know a single informed person who is suggesting you can take down Saddam and not be prepared to stay for two, four, five years to give the country a chance to be held together.”\", \"id\": \"polusa_v1_4327807_-1_24_Joe Biden_21_23\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 55, \"to\": 57, \"sentence\": \"Yet by 2008, after the war had turned south, and after he was done running just in Delaware, Biden sang a different tune.\", \"id\": \"polusa_v1_4327807_-1_25_Saddam_56_58\"}\n{\"mention\": \"Colyer\", \"polarity\": 0, \"from\": 41, \"to\": 47, \"sentence\": \"While Kobach holds strong at 37 percent, Colyer follows with 26 percent.\", \"id\": \"polusa_v1_4328162_-1_5_Jeff Colyer_41_47\"}\n{\"mention\": \"Steele\", \"polarity\": -1, \"from\": 35, \"to\": 41, \"sentence\": \"That the initial application notes Steele worked for a “named U.S. person” but does not name the controversial firm Fusion GPS or its founder Glenn Simpson.\", \"id\": \"polusa_v1_4328370_-1_20_Steele_36_42\"}\n{\"mention\": \"a “named U.S. person\", \"polarity\": -1, \"from\": 53, \"to\": 73, \"sentence\": \"That the initial application notes Steele worked for a “named U.S. person” but does not name the controversial firm Fusion GPS or its founder Glenn Simpson.\", \"id\": \"polusa_v1_4328370_-1_20_a “named U.S. person_54_74\"}\n{\"mention\": \"Ingraham\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Ingraham spoke of the enemies of President Donald Trump, from Antifa to Hollywood.\", \"id\": \"polusa_v1_4328599_-1_14_Ingraham_1_9\"}\n{\"mention\": \"MCALEENAN: 100 percent\", \"polarity\": 0, \"from\": 0, \"to\": 22, \"sentence\": \"MCALEENAN: 100 percent.\", \"id\": \"polusa_v1_4328666_-1_7_Secretary Kevin McAleenan_0_22\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 42, \"to\": 47, \"sentence\": \"Yes, in the wake of Dorsey’s meeting with Trump, Twitter wants the world—especially the world in and around San Francisco–to know that, too.\", \"id\": \"polusa_v1_4328823_-1_51_President Trump_43_48\"}\n{\"mention\": \"Buttigieg\", \"polarity\": -1, \"from\": 101, \"to\": 110, \"sentence\": \"Christians are supposed to strive to be like Christ and while we all fall short, through his actions Buttigieg has proven himself to be a lying bully and a total prick.\", \"id\": \"polusa_v1_4328974_-1_16_Pete Buttigieg_101_110\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 13, \"to\": 15, \"sentence\": \"This is what he told the Today Show Monday.\", \"id\": \"polusa_v1_4328974_-1_5_Pete Buttigieg_14_16\"}\n{\"mention\": \"Barr\", \"polarity\": 1, \"from\": 20, \"to\": 24, \"sentence\": \"7:54 PM: Trump says Barr’s election could make the difference between “unbelievable continued success” and two more years of fighting Democrats.\", \"id\": \"polusa_v1_4329134_-1_58_Barr_21_25\"}\n{\"mention\": \"Barr\", \"polarity\": 1, \"from\": 20, \"to\": 24, \"sentence\": \"7:54 PM: Trump says Barr’s election could make the difference between “unbelievable continued success” and two more years of fighting Democrats.\", \"id\": \"polusa_v1_4329134_-1_58_Andy Barr (R-KY) at Alumni Coliseum at Eastern Kentucky University (Richmond campus)_21_25\"}\n{\"mention\": \"Andy Barr\", \"polarity\": 1, \"from\": 59, \"to\": 68, \"sentence\": \"He says he came to Kentucky because he loves Kentucky and “Andy Barr is a great Congressman.”\", \"id\": \"polusa_v1_4329134_-1_67_Barr_59_68\"}\n{\"mention\": \"Papadopoulos\", \"polarity\": 0, \"from\": 176, \"to\": 188, \"sentence\": \"The report said that an FBI agent — a “seasoned counterintelligence investigator out of New York” had asked Halper, a trusted FBI informant, to set up a meeting in London with Papadopoulos.\", \"id\": \"polusa_v1_4329583_-1_21_Papadopoulos_177_189\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She should inspire everyone in the medical arena, doctors and patients alike.\", \"id\": \"polusa_v1_4330116_-1_13_McGrath_0_3\"}\n{\"mention\": \"they\", \"polarity\": 0, \"from\": 273, \"to\": 277, \"sentence\": \"“Joe Biden walked in the door tonight with more experience on big debates stages than just about anyone, but delivered an often fumbling performance that will likely be best remembered for his visible anger when Kamala Harris called him out on his history against busing,” they wrote.\", \"id\": \"polusa_v1_4330425_-1_12_Chamberlain and Simpson_274_278\"}\n{\"mention\": \"Elizabeth Warren\", \"polarity\": 1, \"from\": 7, \"to\": 23, \"sentence\": \"“While Elizabeth Warren delivered a dominant performance on Wednesday that will undoubtedly help her build on her growing momentum over the last few weeks, Kamala Harris’ pitch-perfect strong performance tonight will catapult her to a new level in the race,” they wrote.\", \"id\": \"polusa_v1_4330425_-1_5_Elizabeth Warren_8_24\"}\n{\"mention\": \"The iconic comic book publisher\", \"polarity\": 1, \"from\": 0, \"to\": 31, \"sentence\": \"The iconic comic book publisher leveraged its tentpole character to push for “what’s right” with a tweet, sent Wednesday, reminding fans that Superman is a “refugee.”\", \"id\": \"polusa_v1_4330683_-1_3_The iconic comic book publisher_1_32\"}\n{\"mention\": \"This #WorldRefugeeDay\", \"polarity\": 1, \"from\": 0, \"to\": 21, \"sentence\": \"This #WorldRefugeeDay, be like Superman and stand up for 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Christakis (@NAChristakis) January 19, 2019\\nAfter the criticism started to pile up, Sharlet doubled down, arguing that the Covington students are worse than the “violent anti-semitic bullies” that he knew as a child.\", \"id\": \"polusa_v1_4330731_-1_17_Dartmouth Professor Jeff Sharlet_98_105\"}\n{\"mention\": \"Wednesday\", \"polarity\": 0, \"from\": 37, \"to\": 46, \"sentence\": \"The U.S. House of Representatives on Wednesday gave victims of illegal alien crimes a bipartisan standing ovation on the floor of the chamber as House Minority Leader Kevin McCarthy read out the names of Americans killed by illegal aliens in a lengthy speech.\", \"id\": \"polusa_v1_4331092_-1_2_Wednesday_39_48\"}\n{\"mention\": \"Dan Crenshaw\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Dan Crenshaw (@RepDanCrenshaw) August 4, 2019\\nRed flag laws exist in California, Florida, Illinois, Maryland, Vermont, and other states where they are designed to flag individuals who are believed to be a 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re-election after Trump refused to endorse him and had since become opposed to his proposals:\\nBob Corker, who helped President O give us the bad Iran Deal & couldn't get elected dog catcher in Tennessee, is now fighting Tax Cuts….\", \"id\": \"polusa_v1_4332441_-1_8_Marco Rubio_1_3\"}\n{\"mention\": \"Lee Greenwood\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"Lee Greenwood Performs 'God Bless the USA' at Inauguration Show\", \"id\": \"polusa_v1_4332496_-1_0_Lee Greenwood_0_13\"}\n{\"mention\": \"the elder Le Pen\", \"polarity\": 1, \"from\": 112, \"to\": 128, \"sentence\": \"Last November a French court upheld the FN’s decision to strip him of his membership but in a small victory for the elder Le Pen it ruled he should be allowed to remain as the party’s honorary president.\", \"id\": \"polusa_v1_4332656_-1_12_the elder Le Pen_113_129\"}\n{\"mention\": \"Cohen\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Cohen pled guilty to arranging deals for 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2018\\nDaniels, the porn actress who alleges that she had an affair with Trump, is suing the president to release her from an NDA she signed in October of 2016.\", \"id\": \"polusa_v1_4333151_-1_10_CNN_46_49\"}\n{\"mention\": \"[Sen.] Mitch McConnell\", \"polarity\": 1, \"from\": 80, \"to\": 102, \"sentence\": \"“We’re going to get a lot of Senators and a lot of Congressmen elected, a lot … [Sen.] Mitch McConnell is here, he’s smiling so big, he loves those words.”\", \"id\": \"polusa_v1_4333499_-1_17_[Sen.] Mitch McConnell_80_102\"}\n{\"mention\": \"We\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"“We’re going to get a lot of Senators and a lot of Congressmen elected, a lot … [Sen.] Mitch McConnell is here, he’s smiling so big, he loves those words.”\", \"id\": \"polusa_v1_4333499_-1_17_OUR_1_3\"}\n{\"mention\": \"Cunningham\", \"polarity\": 0, \"from\": 65, \"to\": 75, \"sentence\": \"In an email with the subject line “Chris Steele,” Winer wrote to Cunningham:\\nHe was in my office catching up and it occurred to me there might be value for McClarty Global knowing him and his capabilities in terms of real time and longer term analysis of developments in that part of the world.\", \"id\": \"polusa_v1_4333622_-1_61_Cunningham_66_76\"}\n{\"mention\": \"California\", \"polarity\": 0, \"from\": 17, \"to\": 27, \"sentence\": \"Jerry Brown, and California Attorney General Xavier Becerra – the elected official who, perhaps more than any other, has made protection of criminal illegal aliens and “resistance” to President Donald Trump’s immigration agenda his signature policy.\", \"id\": \"polusa_v1_4333751_-1_11_California_17_27\"}\n{\"mention\": \"NBC\", \"polarity\": 0, \"from\": 95, \"to\": 98, \"sentence\": \"Kelly is set to headline both a Sunday show and a morning news show when she begins working at NBC next month, though the morning show is not expected to premiere until later this fall.\", \"id\": \"polusa_v1_4333948_-1_6_NBC_96_99\"}\n{\"mention\": \"Somerville\", \"polarity\": -1, \"from\": 29, \"to\": 39, \"sentence\": \"Unable to mount an argument, Somerville instead descends to insults and baseless slurs, calling Bannon an “anti-Semitic Catholic” who only collaborates with Jews in order to achieve the greater good of defeating Islam.\", \"id\": \"polusa_v1_4334816_-1_20_Huffington Post writer Michele Somerville_30_40\"}\n{\"mention\": \"The Deep State\", \"polarity\": -1, \"from\": 8, \"to\": 22, \"sentence\": \"Virgil: The Deep State Strikes Back: The Permanent Campaign Against Donald Trump\", \"id\": \"polusa_v1_4334893_-1_0_The Deep State_8_22\"}\n{\"mention\": \"it\", \"polarity\": 1, \"from\": 194, \"to\": 196, \"sentence\": \"Thus Trump rallied his support; on January 12, Politico Playbook, an e-mail tipsheet for DC insiders and wannabe insiders, had to grudgingly admit, “For most people who watched Trump yesterday, it was a pretty good performance.”\", \"id\": \"polusa_v1_4334893_-1_107_it_195_197\"}\n{\"mention\": \"Shaub\", \"polarity\": -1, \"from\": 34, \"to\": 39, \"sentence\": \"Yes, he’s a federal employee, but Shaub has turned his supposedly non-partisan office into a partisan machine, advancing his anti-Trump campaign including, even, on Twitter.\", \"id\": \"polusa_v1_4334893_-1_60_Shaub_34_39\"}\n{\"mention\": \"Harris\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Harris did not give an indication on Thursday whether he would run for the Republican nomination in the special election ordered by the NCSBE.\", \"id\": \"polusa_v1_4335775_-1_17_Harris_1_7\"}\n{\"mention\": \"ICE\", \"polarity\": 0, \"from\": 82, \"to\": 85, \"sentence\": \"In a February 2018 immigration debate, Donnelly voted for an amendment which told ICE to not deport migrants who had arrived in the United States before June 30, 2018.\", \"id\": \"polusa_v1_4336150_-1_10_ICE'_83_86\"}\n{\"mention\": \"her\", \"polarity\": -1, \"from\": 7, \"to\": 10, \"sentence\": \"I gave her every break, despite the fact that she was despised by everyone, and she went for some cheap money from a book.\", \"id\": \"polusa_v1_4336439_-1_13_Westerhout_7_10\"}\n{\"mention\": \"Madeleine Westerhout\", \"polarity\": 1, \"from\": 7, \"to\": 27, \"sentence\": \"“While Madeleine Westerhout has a fully enforceable confidentiality agreement, she is a very good person and I don’t think there would ever be reason to use it,” Trump wrote Saturday morning.\", \"id\": \"polusa_v1_4336439_-1_4_Westerhout_8_28\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 73, \"to\": 88, \"sentence\": \"The inquiry forced counterintelligence investigators to evaluate whether President Trump was a potential threat to national security, and they also sought to determine whether the president was deliberately working for Russia or had unintentionally been influenced by Moscow.\", \"id\": \"polusa_v1_4336504_-1_9_President Trump_74_89\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 219, \"to\": 225, \"sentence\": \"The inquiry forced counterintelligence investigators to evaluate whether President Trump was a potential threat to national security, and they also sought to determine whether the president was deliberately working for Russia or had unintentionally been influenced by Moscow.\", \"id\": \"polusa_v1_4336504_-1_9_Russia_220_226\"}\n{\"mention\": \"California\", \"polarity\": 0, \"from\": 167, \"to\": 177, \"sentence\": \"Apparently the governor is proposing to put taxpayer money where his mouth is, following up on his bold statement last January in his State of the State speech to the California legislature: “Let me be clear: We will defend everybody — every man, woman and child — who has come here for a better life and has contributed to the well-being of our state.”\", \"id\": \"polusa_v1_4336533_-1_4_California_168_178\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 24, \"to\": 29, \"sentence\": \"Governor Abbott thanked Trump and his administration for their 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\"polusa_v1_4337162_-1_13_Americans_86_95\"}\n{\"mention\": \"Walsh\", \"polarity\": 1, \"from\": 170, \"to\": 175, \"sentence\": \"Alongside other strong women on President Donald J. Trump’s team, like director of strategic communications, Hope Hicks, or counselor to the president, KellyAnne Conway, Walsh is instrumental in making the White House function.\", \"id\": \"polusa_v1_4337825_-1_3_Walsh_170_175\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump also emphasized the importance of the repatriation of remains of soldiers missing in action in the Korean War, which would start “immediately.”\", \"id\": \"polusa_v1_4337870_-1_15_President Donald Trump_0_6\"}\n{\"mention\": \"Coleman\", \"polarity\": 1, \"from\": 37, \"to\": 44, \"sentence\": \"On Thursday, the DCCC announced that Coleman, who is described as a “DCCC veteran,” will lead an engagement effort as “the DCCC’s first-ever Director of the Cycle of Engagement.”\", \"id\": \"polusa_v1_4338042_-1_4_Coleman_38_45\"}\n{\"mention\": \"Joni Ernst\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Joni Ernst jumped into the political fray Monday evening, confirming her belief that Trump's tweets were racist in nature.\", \"id\": \"polusa_v1_4338044_-1_3_Joni Ernst_0_10\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 87, \"to\": 92, \"sentence\": \"She reiterated that view when asked on another occasion by a CNN reporter if she found Trump’s comments racist.\", \"id\": \"polusa_v1_4338044_-1_8_— Donald J. Trump (@realDonaldTrump)_87_92\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 33, \"to\": 36, \"sentence\": \"“We wish we had of gotten rid of him sooner.\", \"id\": \"polusa_v1_4338057_-1_12_Landon_34_37\"}\n{\"mention\": \"West\", \"polarity\": 1, \"from\": 435, \"to\": 439, \"sentence\": \"Constantly bringing up the past keeps you stuck there — KANYE WEST (@kanyewest) April 22, 2018\\nwe have freedom of speech but not freedom of thought — KANYE WEST (@kanyewest) April 22, 2018\\nThe thought police want to suppress freedom of thought — KANYE WEST (@kanyewest) April 22, 2018\\nself victimization is a disease — KANYE WEST (@kanyewest) April 22, 2018\\nI love the way Candace Owens thinks — KANYE WEST (@kanyewest) April 21, 2018\\nWest’s commentary on freedom of thought received 100,000 likes, while his endorsement of Owens received over 80,000.\", \"id\": \"polusa_v1_4338345_-1_10_Kanye West_436_440\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 26, \"to\": 31, \"sentence\": \"Netanyahu will likely ask Trump to inaugurate the embassy at its new location in Arnona, Jerusalem, Channel 2 news reported on Saturday night.\", \"id\": \"polusa_v1_4338440_-1_12_President Donald Trump_27_32\"}\n{\"mention\": \"Swetnick\", \"polarity\": -1, \"from\": 56, \"to\": 64, \"sentence\": \"“Based on its investigations, WebTrends determined that Swetnick had engaged in inappropriate conduct, but that no corroborating evidence existed to support Swetnick’s allegations against her coworkers,” the complaint said.\", \"id\": \"polusa_v1_4338939_-1_15_Julie Swetnick_56_64\"}\n{\"mention\": \"Warren\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Warren also spoke about “racial justice” and her proposition to build three million housing units across the country.\", \"id\": \"polusa_v1_4338989_-1_16_Elizabeth Warren (D-MA)_1_7\"}\n{\"mention\": \"MILO\", \"polarity\": 1, \"from\": 40, \"to\": 44, \"sentence\": \"The office of Chancellor Dirks defended MILO’s right to speak in their response to the professors, citing the United States Constitution as the reason why the college cannot ban MILO from appearing based on his political views.\", \"id\": \"polusa_v1_4339011_-1_13_Breitbart Senior Editor MILO_41_45\"}\n{\"mention\": \"Judith Butler\", \"polarity\": 0, \"from\": 211, \"to\": 224, \"sentence\": \"The following professors signed the letter in an attempt to stifle MILO’s right to speak:\\nElizabeth Abel, Professor, Department of English Wendy Brown, Class of 1936 First Chair, Department of Political Science Judith Butler, Maxine Elliot Professor, Department of Comparative Literature Ian Duncan, Professor, Department of English Donna Jones, Associate Professor, Department of English David Landreth, Associate Professor, Department of English Saba Mahmood, Professor, Department of Anthropology Linda Rugg, Professor, Department of Scandinavian and Associate Dean of Arts and Humanities Elena Schneider, Assistant Professor, Department of History Susan Schweik, Professor, Department of English Estelle Tarica, Associate Professor, Department of Spanish and Portuguese Katrin Wehrheim, Associate Professor, Department of Mathematics Damon Young, Assistant Professor, Departments of French and Film and Media Studies Gregory Levine, Associate Professor, Department of History of Art Lauren Williams, Professor, Department of Mathematics Jon Wilkening, Associate Professor, Vice Chair for Graduate Affairs, Mathematics Janet Sorensen, Associate Professor, English Leslie Salzinger, Associate Professor, Gender and Women’s Studies Khalid Kadir, Lecturer, International and Area Studies Tamara Roberts, Associate Professor, Music Clélia Donovan, Lecturer, Spanish and Portuguese Elisa Tamarkin, Associate Professor, English Julia Bryan-Wilson, Associate Professor, Modern and Contemporary Art Jeffrey Skoller, Associate Professor, Film & Media Déborah Blocker, Associate Professor, French, with an affiliation in Italian Studies Rachel Morello-Frosch, Professor, Department of Environmental Science, Policy and Management & School of Public health Katherine Snyder, Associate Professor, English Mark Goble, Associate Professor, English Alberto Grunbaum, Professor, Department of Mathematics Dan O’Neill, Associate Professor, East Asian Languages and Cultures Soraya Tlatli, Associate Professor, Department of French Barbara A. Barnes, Lecturer, Department of Gender and Women’s Studies Colleen Lye, Associate Professor, English Charles Hirschkind, Associate Professor, Anthropology Saba Mahmood, Professor, Anthropology Ivonne del Valle, Associate Professor, Spanish and Portuguese Daniel G. Chatman, Associate Professor, City and Regional Planning Patricia Penn Hilden, Professor, Department of Ethnic Studies Katherine Sherwood, Professor Emerita, Department of Art Practice Charis Thompson, Professor, Department of Gender and Women’s Studies Ayse Agis, Continuing Lecturer, Gender and Women’s Studies Minoo Moallem, Gender and Women’s Studies Lawrence Cohen, Sarah Kailath Professor of India Studies, Department of Anthropology Emiliano Gomez, Lecturer and Academic Coordinator, Department of Mathematics Paola Bacchetta, Associate Professor, Gender and Women’s Studies Ian Agol, Professor, Department of Mathematics Joanna Picciotto, Associate Professor, English Laura C. Nelson, Associate Professor, Gender & Women’s Studies Cori Hayden, Associate Professor, Anthropology Hung-Hsi Wu, Emeritus Professor of Mathematics Geoffrey G. O’Brien, Associate Professor, English Scott Saul, Professor, English Kevis Goodman, Associate Professor, English Mary Ann Smart, Gladyce Arata Terrill Professor, Music Katherine Snyder, Associate Professor, English Stephen A. Rosenbaum, John & Elizabeth Boalt Lecturer, School of Law Jake Kosek, Associate Professor, Geography Victoria Robinson, Ethnic Studies Celeste Langan, Associate Professor, English Hertha D. Sweet Wong, Associate Professor and Vice-Chair, Department of English Alastair Iles, Associate Professor of Environmental Policy and Societal Change Anne-Lise François, Associate Professor, English and Comparative Literature Davitt Moroney, Professor, Music; University Organist\\nJean-Paul Bourdier, Professor, Architecture Department Natalia Brizuela, Associate Professor, Spanish & Portuguese Line Mikkelsen, Associate Professor, Linguistics Darcy Grimaldo Grigsby, Professor, History of Art Shannon Steen, Associate Professor, Theater, Dance, and Performance Studies Morris W. Hirsch, Professor Emeritus, Mathematics Jenny Harrison Professor, Mathematics James Vernon, Professor, History Debarati Sanyal, Professor, French Christine Rosen, Associate Professor, Haas School of Business Waldo E. Martin, Jr., Morrison Professor of American History and Citizenship Robin Einhorn, Preston Hotchkis Professor in the History of the United States Kristin Hanson, Associate Professor, English Patricia Baquedano-Lopez, Associate Professor of Education Joseph Wolf, Professor Emeritus, Mathematics You-tien Hsing, Professor, Geography Glynda Hull, Professor, Education Richard B. Norgaard, Professor Emeritus of Energy and Resources Ellen L. Simms, Professor of Integrative Biology Katherine Snyder, Associate Professor, Department of English Kathleen Donegan, Associate Professor, Department of English and Associate Dean of Arts and Humanities Trinh T. Minh-ha, Professor of Rhetoric and of Gender & Women’s Studies Suzanne Guerlac, Professor, Department of French Mel Y. Chen, Associate Professor, Department of Gender and Women’s Studies Margaret W. Conkey, Department of Anthropology Darcy Grimaldo Grigsby, Professor, History of Art Mariane C Ferme, Professor, Department of Anthropology Lyn Hejinian, John F Hotchkis Professor of English Michael Watts, Professor Emeritus, Geography Antonio Montalban, Associate Professor, Mathematics Samera Esmeir, Associate Professor, Rhetoric Louise Fortmann, Professor Emerita, Dept of Environmental Science, Policy and Management Joseph Lavery, Assistant Professor, Dept. of English Lynn Huntsinger, Professor, Dept Environmental Science, Policy, and Management Ramona Naddaff, Associate Professor, Rhetoric Daniel Boyarin, Taubman Professor of Talmudic Culture, Near Eastern Studies and Rhetoric Gillian Hart, Professor Emerita, Geography Charles C. Pugh, Professor Emeritus, Mathematics Miryam Sas, Professor and Chair, Comparative Literature: Professor of Film & Media Mark Anderson, Professor of Architecture Darieck Scott, Associate Professor, African American Studies Dept Juana María Rodríguez, Professor, Gender and Women’s Studies Nadia Ellis, Associate Professor, English\\nCharlie Nash is a reporter for Breitbart Tech.\", \"id\": \"polusa_v1_4339011_-1_44_Judith Butler_212_225\"}\n{\"mention\": \"former convict Ray Hinton\", \"polarity\": 1, \"from\": 26, \"to\": 51, \"sentence\": \"Jones in 2015 represented former convict Ray Hinton in a successful bid that saw him freed after nearly 30 years on death row when new ballistics tests raised questions about the evidence used to convict him.\", \"id\": \"polusa_v1_4339347_-1_46_former convict Ray Hinton_26_51\"}\n{\"mention\": \"Jim Acosta\", \"polarity\": -1, \"from\": 40, \"to\": 50, \"sentence\": \"Like the hate network that employs him, Jim Acosta is a national joke and failure propped up by 89 million suckers who subsidize fake news through their cable bills.\", \"id\": \"polusa_v1_4339498_-1_18_Jim Acosta_41_51\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 35, \"to\": 38, \"sentence\": \"Like the hate network that employs him, Jim Acosta is a national joke and failure propped up by 89 million suckers who subsidize fake news through their cable bills.\", \"id\": \"polusa_v1_4339498_-1_18_’m_36_39\"}\n{\"mention\": \"Acosta\", \"polarity\": -1, \"from\": 145, \"to\": 151, \"sentence\": \"Let me offer up a little context…\\nMark Levin’s Unfreedom of the Press, a book critical of fake news, a book that serves as the exact opposite of Acosta’s little screed, currently sits at #3 on Amazon’s Top 100, and Levin’s book was released a month ago.\\nAcosta is also losing to Cozy White Cottage: 100 Ways to Love the Feeling of Being Home (#11).\", \"id\": \"polusa_v1_4339498_-1_8_Jim Acosta_146_152\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Hillary Clinton campaign spokesman Brian Fallon and communications director Nick Merrill attacked Weinstein accuser Asia Argento's boyfriend.\", \"id\": \"polusa_v1_4339560_-1_1_Hillary Clinton_2_17\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 75, \"to\": 80, \"sentence\": \"Brennan repeatedly criticized Republicans for failing to speak out against Trump’s decisions that he felt were endangering the country.\", \"id\": \"polusa_v1_4339843_-1_12_President Trump_76_81\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He was named one of the “most influential” people in news media in 2016.\", \"id\": \"polusa_v1_4340147_-1_13_Joel B. Pollak_0_2\"}\n{\"mention\": \"Estala\", \"polarity\": -1, \"from\": 35, \"to\": 41, \"sentence\": \"The neighbor also told police that Estala put his mouth over a fence post and stuck his tongue in and out through a hole in the fence.\", \"id\": \"polusa_v1_4340180_-1_6_Estala_36_42\"}\n{\"mention\": \"NBC News\", \"polarity\": 0, \"from\": 10, \"to\": 18, \"sentence\": \"But in an NBC News analysis on what Biden is weighing ahead of what would be his last shot at residing at 1600 Pennsylvania Avenue reveals the very things that have made him endearing to many Americans could keep him out of the 2020 race.\", \"id\": \"polusa_v1_4340306_-1_3_NBC News_11_19\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 4, \"to\": 6, \"sentence\": \"But he’s also a grandfather and a father trying to keep his family together.\", \"id\": \"polusa_v1_4340306_-1_9_Former Vice President Joe Biden_4_6\"}\n{\"mention\": \"Reid Hoffman\", \"polarity\": 1, \"from\": 43, \"to\": 55, \"sentence\": \"LinkedIn co-founder and venture capitalist Reid Hoffman is joining forces with a group of Obama administration officials to launch an initiative aimed at storing “all of the progressive community’s voter data,” according to a report released Monday.\", \"id\": \"polusa_v1_4340364_-1_2_Reid Hoffman_45_57\"}\n{\"mention\": \"Judge Kavanaugh\", \"polarity\": -1, \"from\": 18, \"to\": 33, \"sentence\": \"“When it comes to Judge Kavanaugh, there’s not an ounce of fairness left in Senate Democrats.\", \"id\": \"polusa_v1_4340530_-1_5_Judge Kavanaugh_19_34\"}\n{\"mention\": \"Kerrey\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Kerrey moved on to academia and now to an investment bank, but hasn’t lost the willingness to break ranks with his party.\", \"id\": \"polusa_v1_4340540_-1_4_Kerrey_0_7\"}\n{\"mention\": \"Matt Rivitz's\", \"polarity\": -1, \"from\": 75, \"to\": 88, \"sentence\": \"Far left website Salon credited Jared Holt of Right Wing Watch, along with Matt Rivitz's anti-conservative harassment campaign Sleeping Giants, for catalyzing the purge of Alex Jones and Infowars from major tech platforms earlier this week.\", \"id\": \"polusa_v1_4341391_-1_1_Matt Rivitz's_77_90\"}\n{\"mention\": \"Haley\", \"polarity\": 0, \"from\": 153, \"to\": 158, \"sentence\": \"“When the Human Rights Council treats Israel worse than North Korea, Iran and Syria, it is the council itself that is foolish and unworthy of its name,” Haley continued.\", \"id\": \"polusa_v1_4341747_-1_6_UN Envoy Nikki Haley_154_159\"}\n{\"mention\": \"Kimmel\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Kimmel has still not apologized for engaging in the only kind of bigotry still accepted by our self-appointed elites — identity-based attacks on Republicans, including Republican immigrants.\", \"id\": \"polusa_v1_4342132_-1_19_Jimmy Kimmel_1_7\"}\n{\"mention\": \"Snoop\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Snoop has never been a fan of Trump.\", \"id\": \"polusa_v1_4342345_-1_14_Snoop_1_6\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 30, \"to\": 35, \"sentence\": \"Snoop has never been a fan of Trump.\", \"id\": \"polusa_v1_4342345_-1_14_Donald Trump's_31_36\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Donald Trump Does Not Want to Watch Ryan Gosling Moon Landing Movie 'First Man'\", \"id\": \"polusa_v1_4342440_-1_0_Donald Trump_0_12\"}\n{\"mention\": \"Pelosi\", \"polarity\": 0, \"from\": 72, \"to\": 78, \"sentence\": \"Adriano Espaillat (D-NY), one of the lawmakers who signed the letter to Pelosi, told CBS News that Democrats should move “expeditiously” in January to pass legislation to shield illegal immigrants and TPS refugees from deportation, without funding a wall on America’s southern border.\", \"id\": \"polusa_v1_4342748_-1_13_Nancy Pelosi_72_78\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 134, \"to\": 137, \"sentence\": \"Standing just 155 centimetres (five foot, one inch) tall and weighing 43 kilograms (six stone, 10 pounds), her speed and agility make her a match for almost any opponent.\", \"id\": \"polusa_v1_4342847_-1_4_Diana_135_138\"}\n{\"mention\": \"Harvey Weinstein\", \"polarity\": -1, \"from\": 72, \"to\": 88, \"sentence\": \"Hillary Clinton reacted to the abuse scandal embroiling Hollywood mogul Harvey Weinstein by saying the American people elected someone guilty of sexual assault to the presidency.\", \"id\": \"polusa_v1_4342962_-1_4_Harvey Weinstein_74_90\"}\n{\"mention\": \"Seattle Mayor Ed Murray\", \"polarity\": 0, \"from\": 0, \"to\": 23, \"sentence\": \"Seattle Mayor Ed Murray responded to Trump’s immigration enforcement orders calling it the “worst days for immigrants in America since Japanese Internment.”\", \"id\": \"polusa_v1_4343071_-1_1_Seattle Mayor Ed Murray_0_25\"}\n{\"mention\": \"David Cameron\", \"polarity\": -1, \"from\": 36, \"to\": 49, \"sentence\": \"Though I’ve never had much time for David Cameron — at least not since our dope-smoking days at uni — I sat through this documentary feeling almost sorry for him.\", \"id\": \"polusa_v1_4343713_-1_16_David Cameron_37_50\"}\n{\"mention\": \"this documentary\", \"polarity\": 0, \"from\": 116, \"to\": 132, \"sentence\": \"Though I’ve never had much time for David Cameron — at least not since our dope-smoking days at uni — I sat through this documentary feeling almost sorry for him.\", \"id\": \"polusa_v1_4343713_-1_16_the BBC’s documentary Inside Europe_117_133\"}\n{\"mention\": \"Gerald Hebert\", \"polarity\": -1, \"from\": 17, \"to\": 30, \"sentence\": \"This is the same Gerald Hebert who made similar racially charged accusations against Jeff Sessions when he was nominated to be a federal district court judge, just like Tom Farr.\", \"id\": \"polusa_v1_4343810_-1_47_Gerald Hebert_18_31\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 40, \"to\": 43, \"sentence\": \"Shocking statements flow like wine from him.\", \"id\": \"polusa_v1_4343877_-1_13_Billy Bush_40_43\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 30, \"to\": 32, \"sentence\": \"“I felt that, in that moment, he was being typically Donald, which is performing and shocking,” he added.\", \"id\": \"polusa_v1_4343877_-1_15_Billy Bush_31_33\"}\n{\"mention\": \"Donald\", \"polarity\": -1, \"from\": 53, \"to\": 59, \"sentence\": \"“I felt that, in that moment, he was being typically Donald, which is performing and shocking,” he added.\", \"id\": \"polusa_v1_4343877_-1_15_Donald_54_60\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 115, \"to\": 127, \"sentence\": \"SIGN UP FOR OUR NEWSLETTER\\nFormer Today host Billy Bush has broken his silence seven months after the now-infamous Donald Trump “Access Hollywood tape” cost him his job, explaining in a tell-all interview that watching the tape left him “totally and completely gutted” but that he had ultimately become a “better man” as a result.\", \"id\": \"polusa_v1_4343877_-1_2_Donald Trump_117_129\"}\n{\"mention\": \"McSally\", \"polarity\": 1, \"from\": 64, \"to\": 71, \"sentence\": \"McSally garnered 48 percent support to Sinema’s 46, a surge for McSally from a prior poll, but still a statistical tie with a four percent margin of error.\", \"id\": \"polusa_v1_4344411_-1_3_Martha McSally_65_72\"}\n{\"mention\": \"them\", \"polarity\": 1, \"from\": 409, \"to\": 413, \"sentence\": \"Some members of the press were allowed into the building to witness the surprise, and Trump assistant Cliff Sims filmed a video of the president emerging from behind a series of panels:\\nSIGN UP FOR OUR NEWSLETTER\\nYou never know what surprises may await you on a @WhiteHouse tour! pic.twitter.com/VNLpoXRZs4 — Cliff Sims (@CSims45) March 7, 2017\\nSome in the crowd screamed with delight as President Trump gave them his signature “thumbs up” salute.\", \"id\": \"polusa_v1_4344525_-1_3_Some in the crowd_410_414\"}\n{\"mention\": \"Fischer\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Fischer went on, “My outlet is not left-wing or right-wing.\", \"id\": \"polusa_v1_4345303_-1_17_Ford Fischer_0_8\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 42, \"to\": 47, \"sentence\": \"Clinton added on Monday that she believes Trump attacked The Squad because the lawmakers “brought attention to the inhumane conditions they saw at this administration’s detention camps.”\", \"id\": \"polusa_v1_4345456_-1_13_Trump_43_48\"}\n{\"mention\": \"Epstein\", \"polarity\": 0, \"from\": 31, \"to\": 38, \"sentence\": \"Pastrana explained that he met Epstein in Ireland during the International Achievement Summit of 2002 in Dublin.\", \"id\": \"polusa_v1_4345778_-1_8_Epstein_32_39\"}\n{\"mention\": \"Li\", \"polarity\": 0, \"from\": 50, \"to\": 52, \"sentence\": \"The CUPP blasted the decision as “absurd” because Li had not delivered the offending speech yet and was merely advertised on a poster.\", \"id\": \"polusa_v1_4346313_-1_15_Li_51_53\"}\n{\"mention\": \"Taiwan\", \"polarity\": 0, \"from\": 50, \"to\": 56, \"sentence\": \"The South China Morning Post explained Li entered Taiwan on a tourist permit, which under Taiwanese law does not allow visitors to engage in professional activities or give political speeches.\", \"id\": \"polusa_v1_4346313_-1_4_Taiwan_51_57\"}\n{\"mention\": \"Christopher Columbus\", \"polarity\": 0, \"from\": 128, \"to\": 148, \"sentence\": \"The murals by Luigi Gregori that adorn the ceremonial entrance to Notre Dame’s Main Building depict the life and exploration of Christopher Columbus.\", \"id\": \"polusa_v1_4346473_-1_6_Christopher Columbus_129_149\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 61, \"to\": 66, \"sentence\": \"Tancredo: Mandatory E-Verify for Employment Should be Donald Trump's Top Immigration Priority\", \"id\": \"polusa_v1_4346571_-1_0_President Trump_61_66\"}\n{\"mention\": \"Dixon\", \"polarity\": 1, \"from\": 31, \"to\": 36, \"sentence\": \"A memorial fund was set up for Dixon’s family shortly after his death.\", \"id\": \"polusa_v1_4346586_-1_12_Dixon_31_36\"}\n{\"mention\": \"Farrakhan\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Farrakhan is also on record praising Adolf Hitler saying: “The Jews don’t like Farrakhan, so they call me Hitler.\", \"id\": \"polusa_v1_4347406_-1_12_Louis Farrakhan_0_9\"}\n{\"mention\": \"Adolf Hitler\", \"polarity\": -1, \"from\": 37, \"to\": 49, \"sentence\": \"Farrakhan is also on record praising Adolf Hitler saying: “The Jews don’t like Farrakhan, so they call me Hitler.\", \"id\": \"polusa_v1_4347406_-1_12_Adolf Hitler_37_49\"}\n{\"mention\": \"Sarsour\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Sarsour wrote:\\nKind, compassionate, humble, active listener — that’s Roger Waters.\", \"id\": \"polusa_v1_4347620_-1_3_Women's March leader Linda Sarsour_0_8\"}\n{\"mention\": \"Morrisey\", \"polarity\": 0, \"from\": 43, \"to\": 51, \"sentence\": \"Jim Justice to the stage, and Justice says Morrisey is “a little behind right now” and asks the crowd to vote for him.\", \"id\": \"polusa_v1_4347714_-1_48_GOP Senate candidate Patrick Morrisey_43_51\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 61, \"to\": 66, \"sentence\": \"Following the public backlash from the photo, Griffin blamed Trump for the outrage, saying:\\n“Trump knows what would be perceived as something hysterical and he loves hysteria.\", \"id\": \"polusa_v1_4347824_-1_10_Kathy Griffin Attacks Melania Trump: ‘Feckless Complicit Piece of Sh*t’_62_67\"}\n{\"mention\": \"Griffin\", \"polarity\": 0, \"from\": 46, \"to\": 53, \"sentence\": \"Following the public backlash from the photo, Griffin blamed Trump for the outrage, saying:\\n“Trump knows what would be perceived as something hysterical and he loves hysteria.\", \"id\": \"polusa_v1_4347824_-1_10_Kathy Griffin_47_54\"}\n{\"mention\": \"Ted Kennedy\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"Ted Kennedy (D-MA) on the fateful night he left an innocent young woman to die in order to save his political career.\", \"id\": \"polusa_v1_4347896_-1_3_Ted Kennedy_0_11\"}\n{\"mention\": \"an innocent young woman\", \"polarity\": 1, \"from\": 48, \"to\": 71, \"sentence\": \"Ted Kennedy (D-MA) on the fateful night he left an innocent young woman to die in order to save his political career.\", \"id\": \"polusa_v1_4347896_-1_3_an innocent young woman_48_71\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 11, \"to\": 13, \"sentence\": \"But again, he’s not Joe Sr., Joe Jr., John, or Bobby — he’s Teddy, and his public relations mishaps begin to pile up.\", \"id\": \"polusa_v1_4347896_-1_44_Ted Kennedy_11_13\"}\n{\"mention\": \"Teddy\", \"polarity\": -1, \"from\": 184, \"to\": 189, \"sentence\": \"His disabled father (Bruce Dern) and the mercenaries who protect the Kennedy brand at all costs (Ted Sorensen, Robert McNamara, etc.) had a plan to salvage the situation, but one that Teddy’s fumbling has already defeated.\", \"id\": \"polusa_v1_4347896_-1_47_Teddy_184_189\"}\n{\"mention\": \"Dartmouth\", \"polarity\": -1, \"from\": 36, \"to\": 45, \"sentence\": \"Seven women filed a lawsuit against Dartmouth College in New Hampshire on Thursday for allowing professors William Kelley, Paul Whalen, and Todd Heatherton to allegedly harass female students.\", \"id\": \"polusa_v1_4348049_-1_3_Dartmouth_37_46\"}\n{\"mention\": \"Paul Whalen\", \"polarity\": -1, \"from\": 123, \"to\": 134, \"sentence\": \"Seven women filed a lawsuit against Dartmouth College in New Hampshire on Thursday for allowing professors William Kelley, Paul Whalen, and Todd Heatherton to allegedly harass female students.\", \"id\": \"polusa_v1_4348049_-1_3_Paul Whalen_124_135\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 65, \"to\": 72, \"sentence\": \"Streisand spent much of the presidential campaign working to get Clinton elected and bashing then-Republican candidate Donald Trump.\", \"id\": \"polusa_v1_4348263_-1_7_Hillary Clinton's_66_73\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Mueller said last week that the report he created for the Department of Justice, which shows that Trump or his campaign did not collude with the Russian government “speaks for itself.”\", \"id\": \"polusa_v1_4348360_-1_8_Robert Mueller_0_8\"}\n{\"mention\": \"Jones\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Jones, for his part, has already denounced the interview as “fake news” and said it was purposeful hit job on him.\", \"id\": \"polusa_v1_4348649_-1_33_Jones_1_6\"}\n{\"mention\": \"CNN\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"CNN and Andrew Kaczynski gave a misleading defense after printing that CNN may reveal a meme maker's identity if the man engages in \\\"ugly behavior.\\\"\", \"id\": \"polusa_v1_4348739_-1_1_CNN_2_5\"}\n{\"mention\": \"Ahmed\", \"polarity\": 0, \"from\": 246, \"to\": 251, \"sentence\": \"No, this absurd propaganda is by one of the Times’ resident shills for Islam, Atossa Araxia Abrahmian, coming in form of a review of Journey Into Europe: Islam, Immigration, and Identity, the latest installment in Islamic studies professor Akbar Ahmed’s series on Muslims around the world.\", \"id\": \"polusa_v1_4348858_-1_8_Ahmed_246_251\"}\n{\"mention\": \"Bajrang Dal\", \"polarity\": -1, \"from\": 30, \"to\": 41, \"sentence\": \"India’s Daily O addressed the Bajrang Dal problem in an editorial dripping with sarcasm, beginning with the observation that lonely singles have the consolation of knowing they won’t be thrashed by a gang of “sexually-frustrated, culture-spewing, self-righteous scumbags” on Valentine’s Day:\\nThese hate-loving detectives travel in packs with hockey sticks and lead pipes.\", \"id\": \"polusa_v1_4348896_-1_7_Bajrang Dal_31_42\"}\n{\"mention\": \"Jones\", \"polarity\": 1, \"from\": 28, \"to\": 33, \"sentence\": \"Brennan’s letter, signed by Jones, was in support of the Democracy Restoration Act, which was introduced in 2011 by Rep.\", \"id\": \"polusa_v1_4348977_-1_6_Jones_29_34\"}\n{\"mention\": \"Stephen King\", \"polarity\": 0, \"from\": 2, \"to\": 14, \"sentence\": \"— Stephen King (@StephenKing) July 9, 2017\\nKing, however, wasn’t the only celebrity to call for Trump’s removal from office Friday.\", \"id\": \"polusa_v1_4349006_-1_12_Stephen King_2_14\"}\n{\"mention\": \"Maduro\", \"polarity\": -1, \"from\": 66, \"to\": 72, \"sentence\": \"As the Los Angeles Times reports, “opponents of President Nicolas Maduro flooded the streets of Caracas… for what they’ve dubbed the ‘mother of all marches’ against the embattled socialist leader.”\", \"id\": \"polusa_v1_4349056_-1_18_Venezuela's Maduro_66_72\"}\n{\"mention\": \"Caracas\", \"polarity\": 0, \"from\": 96, \"to\": 103, \"sentence\": \"As the Los Angeles Times reports, “opponents of President Nicolas Maduro flooded the streets of Caracas… for what they’ve dubbed the 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\"polusa_v1_4350197_-1_13_Salvini_1_8\"}\n{\"mention\": \"Blair\", \"polarity\": -1, \"from\": 35, \"to\": 40, \"sentence\": \"Instead of standing for something, Blair ran on the “Cool Britannia” mantra, eschewing substance for style, diverting from debate and embracing governance by charisma.\", \"id\": \"polusa_v1_4351516_-1_48_Prime Minister Tony Blair_35_40\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 290, \"to\": 293, \"sentence\": \"A report by think tank Quilliam has found that more than eight out of ten men convicted of grooming gang offences have an 'Asian' background, while victims are \\\"almost exclusively white girls\\\". https://t.co/9llGk0zVRS — Jack Montgomery ن (@JackBMontgomery) December 10, 2017\\nThe woman said she hoped Aslam would “go to prison for a long time” — but Sheriff John Rafferty handed him a sentence only one year long.\", \"id\": \"polusa_v1_4351562_-1_11_Shopkeeper Rana Aslam_291_294\"}\n{\"mention\": \"The president\", \"polarity\": 1, 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26, \"sentence\": \"But I don’t quite have his social media firepower.\", \"id\": \"polusa_v1_4355990_-1_36_President Trump_23_26\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 50, \"to\": 55, \"sentence\": \"Asked whether Tlaib’s’s call for President Donald Trump to be impeached hurts the Democrats’ “hurts the case,” Pelosi replied: “The enthusiasm that our members have helps the case, any case….We try to build our consensus on how we go forward.\", \"id\": \"polusa_v1_4356063_-1_6_President Trump_50_55\"}\n{\"mention\": \"Sarsour\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Sarsour, who describes herself as a feminist despite being an advocate for Sharia Law, has also previously declared “jihad” against the Trump administration, and has called on Muslims in the United States to actively not assimilate into American society, but instead act “to please Allah and only Allah.”\", \"id\": \"polusa_v1_4356166_-1_18_progressive activist Linda 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\"id\": \"polusa_v1_4360708_-1_8_the United States_113_130\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 49, \"to\": 54, \"sentence\": \"Several leaders of American manufacturers joined Trump for the event, highlighting the jobs they had created in the United States.\", \"id\": \"polusa_v1_4360708_-1_8_President Donald Trump_50_55\"}\n{\"mention\": \"the FBI\", \"polarity\": 0, \"from\": 106, \"to\": 113, \"sentence\": \"Republicans asked Mueller several times why Mifsud had not been prosecuted for making false statements to the FBI, when others — including Papadopoulos, former National Security Advisor Michael Flynn, and former Trump campaign manager Paul Manafort — had been.\", \"id\": \"polusa_v1_4360722_-1_22_FBI_107_114\"}\n{\"mention\": \"Murkowski\", \"polarity\": 0, \"from\": 9, \"to\": 18, \"sentence\": \"In 2015, Murkowski joined Sen.\", \"id\": \"polusa_v1_4360849_-1_15_Lisa Murkowski_10_19\"}\n{\"mention\": \"Farrow\", \"polarity\": -1, \"from\": 23, \"to\": 29, \"sentence\": \"Some did find evidence Farrow had coached Dylan to make the allegations.\", \"id\": \"polusa_v1_4360896_-1_18_Farrow_23_29\"}\n{\"mention\": \"Dylan\", \"polarity\": -1, \"from\": 42, \"to\": 47, \"sentence\": \"Some did find evidence Farrow had coached Dylan to make the allegations.\", \"id\": \"polusa_v1_4360896_-1_18_Dylan_42_47\"}\n{\"mention\": \"Woody Allen\", \"polarity\": -1, \"from\": 51, \"to\": 62, \"sentence\": \"Twenty-seven years later, the 1991 breakup between Woody Allen and Mia Farrow still somehow manages to get even uglier.\", \"id\": \"polusa_v1_4360896_-1_3_Woody Allen_52_63\"}\n{\"mention\": \"Cruz\", \"polarity\": 0, \"from\": 125, \"to\": 129, \"sentence\": \"And it is a particularly hurtful argument that it can be directed at someone particularly when it’s countered by the facts,” Cruz said.\", \"id\": \"polusa_v1_4361501_-1_47_Cruz_125_129\"}\n{\"mention\": \"Colbert\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Colbert’s ratings have risen steadily since Inauguration Day.\", \"id\": \"polusa_v1_4361791_-1_32_Stephen Colbert_1_8\"}\n{\"mention\": \"Morrisey\", \"polarity\": 1, \"from\": 106, \"to\": 114, \"sentence\": \"Now that Bossie, Trump’s ex-Deputy Campaign Manager from his successful 2016 campaign, is aligning behind Morrisey, the same type of dynamic is emerging in West Virginia.\", \"id\": \"polusa_v1_4361877_-1_23_conservative change agent Patrick Morrisey_107_115\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 17, \"to\": 22, \"sentence\": \"Now that Bossie, Trump’s ex-Deputy Campaign Manager from his successful 2016 campaign, is aligning behind Morrisey, the same type of dynamic is emerging in West Virginia.\", \"id\": \"polusa_v1_4361877_-1_23_Trump_18_23\"}\n{\"mention\": \"Epstein\", \"polarity\": -1, \"from\": 129, \"to\": 136, \"sentence\": \"\\\"Subsequently, the U.S. Attorney’s Office produced a 53-page indictment that was abandoned after secret negotiations between Mr. Epstein’s lawyers and Mr. Acosta.\", \"id\": \"polusa_v1_4362359_-1_13_Jeffrey Epstein_130_137\"}\n{\"mention\": \"Krischer\", \"polarity\": 0, \"from\": 227, \"to\": 235, \"sentence\": \"\\\"As the state attorney for Palm Beach County for 16 years [1993-2009], which included the entire period of the Epstein investigation, I can emphatically state that Mr. Acosta’s recollection of this matter is completely wrong,\\\" Krischer began.\", \"id\": \"polusa_v1_4362359_-1_9_Former Palm Beach County State Attorney Barry Krischer_228_236\"}\n{\"mention\": \"Weldon\", \"polarity\": 0, \"from\": 37, \"to\": 43, \"sentence\": \"It’s always wise to be cautious, but Weldon is a former linebacker for the Florida Gators.\", \"id\": \"polusa_v1_4362495_-1_9_Weldon_38_44\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": -1, \"from\": 15, \"to\": 24, \"sentence\": \"Harris accused Kavanaugh of choosing his words carefully and said, “This is a dog whistle for going after birth control.”\", \"id\": \"polusa_v1_4363220_-1_14_Judge Brett Kavanaugh_16_25\"}\n{\"mention\": \"EVIDENCE ROGER STONE\", \"polarity\": -1, \"from\": 23, \"to\": 43, \"sentence\": \"MUELLER CLAIMS TO HAVE EVIDENCE ROGER STONE COMMUNICATED WITH WIKILEAKS\\nOn Instagram, Stone said that the post has been “misinterpreted” and denied he tried to threaten the judge.\", \"id\": \"polusa_v1_4363846_-1_10_Roger Stone_24_44\"}\n{\"mention\": \"the first lady\", \"polarity\": 1, \"from\": 48, \"to\": 62, \"sentence\": \"@Potus and I enjoyed working with @NORADSanta,\\\" the first lady tweeted following the calls.\", \"id\": \"polusa_v1_4363972_-1_9_President Trump and First Lady Melania Trump_48_62\"}\n{\"mention\": \"Kim\", \"polarity\": -1, \"from\": 86, \"to\": 89, \"sentence\": \"Though China has long been the North's main trading partner and diplomatic protector, Kim's nuclear and missile tests have alienated Chinese leaders, who supported last month's U.N. sanctions that slash North Korean revenue by banning sales of coal and iron ore.\", \"id\": \"polusa_v1_4364046_-1_3_Kim_87_90\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 5, \"to\": 11, \"sentence\": \"Cody Wilson, man behind controversial 3-D printed gun, accused of sex assault\", \"id\": \"polusa_v1_4364201_-1_0_Wilson_5_11\"}\n{\"mention\": \"His\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"His 51-year-old wife spoke recently about her husband’s political future.\", \"id\": \"polusa_v1_4365467_-1_9_92-year-old President Robert Mugabe_1_4\"}\n{\"mention\": \"DCCC\", \"polarity\": 1, \"from\": 52, \"to\": 56, \"sentence\": \"Monday’s numbers, first reported by NBC News, shows DCCC besting its previous record of $4.15 million in August 2015.\", \"id\": \"polusa_v1_4365820_-1_3_DCCC_53_57\"}\n{\"mention\": \"Paul\", \"polarity\": 0, \"from\": 65, \"to\": 69, \"sentence\": \"Brennan should be asked to testify under oath in Congress ASAP,\\\" Paul wrote.\", \"id\": \"polusa_v1_4366294_-1_14_Senator Rand Paul, R-Ky_65_69\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 62, \"to\": 67, \"sentence\": \"Old school Republican Gillespie has been stepping gingerly on Trump's coattails — not fully embracing the man but generally supporting his policies and campaigning in rural counties where Trump's base is strong.\", \"id\": \"polusa_v1_4366652_-1_19_President Trump_63_68\"}\n{\"mention\": \"Macron\", \"polarity\": -1, \"from\": 61, \"to\": 67, \"sentence\": \"The latest public opinion polls at the end of July have seen Macron's popularity rate at its lowest level since he was elected in May 2017.\", \"id\": \"polusa_v1_4368539_-1_8_French President Emmanuel Macron_62_68\"}\n{\"mention\": \"Goochland County Sheriff James Agnew\", \"polarity\": 0, \"from\": 2, \"to\": 38, \"sentence\": \"— Goochland County Sheriff James Agnew\\nHe said small bite marks were found on the body and the wounds didn’t puncture Stephens’ skull, ruling out that a larger animal, such as a bear, was to blame for the attack.\", \"id\": \"polusa_v1_4368745_-1_14_Goochland County Sheriff James Agnew_2_38\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 20, \"to\": 25, \"sentence\": \"Publicly, at least, Trump's aides take his impulsiveness in stride.\", \"id\": \"polusa_v1_4369190_-1_42_President Donald Trump_21_26\"}\n{\"mention\": \"the Mueller investigation\", \"polarity\": -1, \"from\": 36, \"to\": 61, \"sentence\": \"DiGenova also on Sunday argued that the Mueller investigation has become a bad faith probe in large part because of how federal agents treated former Trump campaign official Paul Manafort and Michael Cohen, who was the Trump personal lawyer who negotiated a $130,00 payout to porn actress Stormy Daniels who alleges she had a tryst with Trump.\", \"id\": \"polusa_v1_4370545_-1_10_a “bad faith” investigation_37_62\"}\n{\"mention\": \"Mrs. Trump\", \"polarity\": 1, \"from\": 0, \"to\": 10, \"sentence\": \"Mrs. Trump said she has spent the past year listening to and learning from parents, medical professionals, teachers, leaders in the field of technology and social media and many others, and that she was ready for more.\", \"id\": \"polusa_v1_4371113_-1_9_Melania Trump_0_11\"}\n{\"mention\": \"the President\", \"polarity\": 1, \"from\": 328, \"to\": 341, \"sentence\": \"And when Mueller didn’t reach a conclusion on allegations that the president engaged in obstruction of justice to interfere in the Mueller investigation, a careful review by Attorney General William Barr and Deputy Attorney General Rod Rosenstein concluded that evidence gathered by Mueller “is not sufficient to establish that the President committed an obstruction-of-justice offense,” Mueller wrote in a letter to Congress.\", \"id\": \"polusa_v1_4371325_-1_28_President Trump_329_342\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 71, \"to\": 86, \"sentence\": \"It’s also a one-way ticket back to the minority and four more years of President Trump.\", \"id\": \"polusa_v1_4371325_-1_55_President Trump_71_86\"}\n{\"mention\": \"Maduro\", \"polarity\": -1, \"from\": 51, \"to\": 57, \"sentence\": \"Pence urged the Security Council to act to end the Maduro regime and recognize Interim President Juan Guaido.\", \"id\": \"polusa_v1_4371422_-1_7_Venezuelan dictator Nicolas Maduro_52_58\"}\n{\"mention\": \"Pence\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Pence urged the Security Council to act to end the Maduro regime and recognize Interim President Juan Guaido.\", \"id\": \"polusa_v1_4371422_-1_7_Vice President Pence_0_6\"}\n{\"mention\": \"Doug Jones\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Doug Jones stand in contrast to statements made last week by Secretary of State Mike Pompeo and President Trump, who both vowed to keep Hoda Muthana off U.S. soil.\", \"id\": \"polusa_v1_4371464_-1_5_Doug Jones_0_10\"}\n{\"mention\": \"the 76-year-old Abdul-Mahdi\", \"polarity\": 1, \"from\": 60, \"to\": 87, \"sentence\": 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\"polusa_v1_4372811_-1_8_Joe Arpaio_18_28\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Wilson was reportedly charged with fleeing officers, retail theft and obstructing an officer.\", \"id\": \"polusa_v1_4373187_-1_11_John Wilson_0_7\"}\n{\"mention\": \"Scherer\", \"polarity\": 0, \"from\": 23, \"to\": 30, \"sentence\": \"Jeannine Jacobson told Scherer that Cruz can waive his half, giving the entirety to his brother.\", \"id\": \"polusa_v1_4374086_-1_22_Circuit Judge Elizabeth Scherer_23_30\"}\n{\"mention\": \"Prime Minister Malcolm Turnbull\", \"polarity\": -1, \"from\": 54, \"to\": 85, \"sentence\": \"— Donald J. Trump (@realDonaldTrump) February 2, 2017\\nPrime Minister Malcolm Turnbull was left scrambling to defend his country's allegiance to the U.S. after The Washington Post published a report on Thursday detailing a tense exchange that allegedly took place during the Australian leader's first telephone call with Trump since he became president.\", \"id\": \"polusa_v1_4374500_-1_12_Prime Minister Malcolm Turnbull_54_85\"}\n{\"mention\": \"Turnbull\", \"polarity\": -1, \"from\": 69, \"to\": 77, \"sentence\": \"The newspaper said Trump dubbed it \\\"the worst deal ever\\\" and accused Turnbull of seeking to export the \\\"next Boston bombers\\\" — a reference to Tamerlan and Dzhokhar Tsarnaev, who were born in Kyrgyzstan and set off explosives at the 2013 Boston marathon.\", \"id\": \"polusa_v1_4374500_-1_14_Prime Minister Malcolm Turnbull_70_78\"}\n{\"mention\": \"Schneiderman\", \"polarity\": -1, \"from\": 46, \"to\": 58, \"sentence\": \"According to the article, Manning Barish said Schneiderman \\\"would be 'shaking me and grabbing my face' while demanding that she repeat such things as 'I'm a little wh---.'\\\" On another occasion, Manning Barish says that Schneiderman told her \\\"If you ever left me, I'd kill you.\\\"\", \"id\": \"polusa_v1_4374681_-1_18_the powerful Democratic N.Y. Attorney General Eric Schneiderman_47_59\"}\n{\"mention\": \"Schneiderman\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Schneiderman also asked her to \\\"call him Master, and he’d slap me until I did.\\\"\", \"id\": \"polusa_v1_4374681_-1_28_Schneiderman_0_12\"}\n{\"mention\": \"Schneiderman\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Schneiderman also asked her to \\\"call him Master, and he’d slap me until I did.\\\"\", \"id\": \"polusa_v1_4374681_-1_28_the powerful Democratic N.Y. Attorney General Eric Schneiderman_0_12\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He must resign from office and be held accountable for his crimes.\\\"\", \"id\": \"polusa_v1_4374681_-1_43_Schneiderman_1_3\"}\n{\"mention\": \"Moyer\", \"polarity\": 0, \"from\": 147, \"to\": 152, \"sentence\": \"Asked whether the FBI would have been able to establish probable cause if the application “did not have the Christopher Steele information in it,” Moyer responded: \\\"So I think it's a close call, like 50/50, 51/49.\", \"id\": \"polusa_v1_4375379_-1_4_senior FBI lawyer Sally Moyer_148_153\"}\n{\"mention\": \"An 11-year-old pit bull named Sadie\", \"polarity\": 1, \"from\": 0, \"to\": 35, \"sentence\": \"An 11-year-old pit bull named Sadie has been credited for saving her family from danger after she likely sniffed out a gas leak in the basement of their Tuckahoe, New York, home.\", \"id\": \"polusa_v1_4375753_-1_1_An 11-year-old pit bull named Sadie_2_37\"}\n{\"mention\": \"Sadie\", \"polarity\": 1, \"from\": 30, \"to\": 35, \"sentence\": \"An 11-year-old pit bull named Sadie has been credited for saving her family from danger after she likely sniffed out a gas leak in the basement of their Tuckahoe, New York, home.\", \"id\": \"polusa_v1_4375753_-1_1_Sadie_32_37\"}\n{\"mention\": \"Sadie\", \"polarity\": 0, \"from\": 5, \"to\": 10, \"sentence\": \"“Did Sadie sense danger?\", \"id\": \"polusa_v1_4375753_-1_8_Sadie_6_11\"}\n{\"mention\": \"recently freed Puerto Rican nationalist Oscar López Rivera\", \"polarity\": -1, \"from\": 35, \"to\": 93, \"sentence\": \"A host of celebrations in honor of recently freed Puerto Rican nationalist Oscar López Rivera has outraged the families of those who lost relatives in a string of bombings during 1970s and 80s linked to his group, even as many Puerto Ricans hail him as a patriot and political prisoner.\", \"id\": \"polusa_v1_4376214_-1_2_recently freed Puerto Rican nationalist Oscar López Rivera_37_95\"}\n{\"mention\": \"Oscar\", \"polarity\": -1, \"from\": 75, \"to\": 80, \"sentence\": \"A host of celebrations in honor of recently freed Puerto Rican nationalist Oscar López Rivera has outraged the families of those who lost relatives in a string of bombings during 1970s and 80s linked to his group, even as many Puerto Ricans hail him as a patriot and political prisoner.\", \"id\": \"polusa_v1_4376214_-1_2_“Oscar_77_82\"}\n{\"mention\": \"Deaton\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Deaton drove away with the woman still in the car, but she managed to escape.\", \"id\": \"polusa_v1_4377357_-1_13_Deaton_0_6\"}\n{\"mention\": \"Jesus Christ\", \"polarity\": 1, \"from\": 103, \"to\": 115, \"sentence\": \"There is no one in the church who ought to be more fired up and passionate about sharing the Gospel of Jesus Christ with as many people as possible than the pastor.\", \"id\": \"polusa_v1_4377627_-1_35_Jesus_103_115\"}\n{\"mention\": \"Waas\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Waas said police arrested Alexander M. 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\\\"reckless and shows bad judgment,\\\" according to the Washington Post.\", \"id\": \"polusa_v1_4379464_-1_4_primary opponent Jennifer Wexton_29_35\"}\n{\"mention\": \"Concha\", \"polarity\": 0, \"from\": 57, \"to\": 63, \"sentence\": \"Referencing former President Bill Clinton's impeachment, Concha asserted his belief that should the same happen to Trump, it would make him a sympathetic figure and cast a vindictive light on the Democratic party.\", \"id\": \"polusa_v1_4379486_-1_7_media reporter Joe Concha_57_63\"}\n{\"mention\": \"Herrera-Dempsey\", \"polarity\": 0, \"from\": 69, \"to\": 84, \"sentence\": \"Stewart has been charged with aggravated murder for fatally shooting Herrera-Dempsey in Dublin and with murder for killing Ballard in Columbus, police said.\", \"id\": \"polusa_v1_4379580_-1_13_Herrera-Dempsey_70_85\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 1, \"from\": 200, \"to\": 212, \"sentence\": \"She added: “Whether you are talking about Pennsylvania, North Carolina, Ohio, Florida, Michigan, people are going to look at their lives in 2020 and say 'is stuff better for me now than it was before Donald Trump took office or will we give Joe Biden a chance to do nothing like we saw during the Obama years?'”\\nCLICK HERE FOR THE FOX NEWS APP\\nThe Associated Press contributed to this report.\", \"id\": \"polusa_v1_4381157_-1_23_Lara Trump_201_213\"}\n{\"mention\": \"Fico\", \"polarity\": 0, \"from\": 7, \"to\": 11, \"sentence\": \"Kiska, Fico's rival, called earlier Sunday for substantial changes in the country's coalition government or for an early election because of a \\\"huge\\\" distrust of the public in the state.\", \"id\": \"polusa_v1_4381408_-1_4_Slovak Prime Minister Robert Fico_8_12\"}\n{\"mention\": \"Turnbull\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Turnbull on Tuesday said foreign interference in politics would be outlawed under updated treason and espionage laws.\", \"id\": \"polusa_v1_4382232_-1_3_Australian Prime Minister Malcolm Turnbull_0_9\"}\n{\"mention\": \"Manafort\", \"polarity\": 1, \"from\": 42, \"to\": 50, \"sentence\": \"Trump also said he had “such respect” for Manafort and called him a “brave man.”\", \"id\": \"polusa_v1_4383521_-1_24_Paul Manafort_43_51\"}\n{\"mention\": \"Sen.\", \"polarity\": 0, \"from\": 87, \"to\": 91, \"sentence\": \"Related Image Expand / Collapse\\nCollins issued her apology after she was heard telling Sen.\", \"id\": \"polusa_v1_4384177_-1_14_Sen._88_92\"}\n{\"mention\": \"Bernie Sanders\", \"polarity\": -1, \"from\": 16, \"to\": 30, \"sentence\": \"Socialists like Bernie Sanders focus nearly all of their time talking about redistributing wealth, but what they never tell you is that research shows that even if the world’s wealth were totally redistributed, it would result in all people being relatively poor.\", \"id\": \"polusa_v1_4384973_-1_40_Bernie Sanders_17_31\"}\n{\"mention\": \"Rao\", \"polarity\": -1, \"from\": 36, \"to\": 39, \"sentence\": 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\"Haley\", \"polarity\": 0, \"from\": 57, \"to\": 62, \"sentence\": \"Along with Grenell, other names being floated to replace Haley include U.S. Ambassador to Russia Jon Hunstman, Acting Under Secretary for Public Diplomacy and Public Affairs Heather Nauert, former deputy national security adviser Dina Powell, and even first daughter Ivanka Trump.\", \"id\": \"polusa_v1_4488675_-1_9_Haley_58_63\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 65, \"to\": 67, \"sentence\": \"UK'S LEFT-WING LABOUR PARTY ENGULFED BY ANTI-SEMITISM CRISIS\\nBut he was criticized last year when a picture emerged of him attending a wreath-laying ceremony in 2014 that honored perpetrators of the 1972 Munich terror attack against Israeli athletes, although he said he was there to honor those killed in a 1985 Israeli air strike.\", \"id\": \"polusa_v1_4489769_-1_15_Corbyn_66_68\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 139, \"to\": 154, \"sentence\": \"House Foreign Affairs 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his agents in the world – not by the world’s normal bullying methods, but by following the royal way of Jesus.\", \"id\": \"polusa_v1_4492812_-1_74_Jesus_110_115\"}\n{\"mention\": \"Peters\", \"polarity\": -1, \"from\": 42, \"to\": 48, \"sentence\": \"A warrant, according to AJC, alleged that Peters didn’t tell anyone Stewart had died for a month.\", \"id\": \"polusa_v1_4493859_-1_9_Peters_43_49\"}\n{\"mention\": \"Stewart\", \"polarity\": 0, \"from\": 68, \"to\": 75, \"sentence\": \"A warrant, according to AJC, alleged that Peters didn’t tell anyone Stewart had died for a month.\", \"id\": \"polusa_v1_4493859_-1_9_aunt_69_76\"}\n{\"mention\": \"President Trump\", \"polarity\": 1, \"from\": 20, \"to\": 35, \"sentence\": \"Ivanka also praised President Trump's first foreign trip, during which he visited Saudi Arabia, Israel and Italy.\", \"id\": \"polusa_v1_4494200_-1_16_President Trump_21_36\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 106, \"to\": 109, \"sentence\": \"Batrice described Gabbard as a close friend, Politico reported, and said \\\"it’s been an honor to work with her over the last few years.\", \"id\": \"polusa_v1_4494352_-1_10_Tsuji_107_110\"}\n{\"mention\": \"Geert Wilders\", \"polarity\": 1, \"from\": 108, \"to\": 121, \"sentence\": \"“To avoid the risk of victims of Islamic violence, I have decided not to let the cartoon contest go ahead,” Geert Wilders said in a written statement, noting he did not want others endangered by the contest he had planned for November.\", \"id\": \"polusa_v1_4494949_-1_3_Geert Wilders_109_122\"}\n{\"mention\": \"Schumer\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Schumer says the president should focus \\\"on the real solution — anti-terrorism funding\\\" — an area that Schumer says Trump has proposed cutting in his most recent budget.\", \"id\": \"polusa_v1_4496007_-1_80_Chuck Schumer_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 184, \"to\": 191, \"sentence\": \"\\\"[Trump] was quite successful in referencing a nostalgia that would give hope, comfort, settle grievances, for millions of people who were upset about gains that were made by others,” Clinton tap danced.\", \"id\": \"polusa_v1_4496075_-1_34_Hillary Clinton_184_191\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 69, \"to\": 76, \"sentence\": \"But when Goodlatte asked whether that language was changed to ensure Clinton could not be held liable under the Espionage Act, Wray deferred to the ongoing IG probe and would not comment.\", \"id\": \"polusa_v1_4496404_-1_15_Clinton_70_77\"}\n{\"mention\": \"Shanahan\", \"polarity\": 0, \"from\": 35, \"to\": 43, \"sentence\": \"CLICK HERE TO GET THE FOX NEWS APP\\nShanahan and Kilmeade also discuss the U.S. Patriot missile system.\", \"id\": \"polusa_v1_4496609_-1_21_Patrick Shanahan_36_44\"}\n{\"mention\": \"Fox\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"Fox told The Associated Press separately by phone that Duterte's anti-drug 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\"polusa_v1_4502838_-1_2_Alexandria Ocasio-Cortez_0_24\"}\n{\"mention\": \"Sanford\", \"polarity\": 0, \"from\": 9, \"to\": 16, \"sentence\": \"Although Sanford was able to win a congressional seat in 2012, he lost the primary in 2018 after publicly criticizing the president.\", \"id\": \"polusa_v1_4503984_-1_14_Mark Sanford, R-S.C._10_17\"}\n{\"mention\": \"Warmbier\", \"polarity\": 1, \"from\": 116, \"to\": 124, \"sentence\": \"- Fred Warmbier, father of U.S. student held in North Korea for 15 months\\n“I beg that you see how I am only human,” Warmbier said at his trial.\", \"id\": \"polusa_v1_4505643_-1_16_Warmbier_116_124\"}\n{\"mention\": \"the president\", \"polarity\": 1, \"from\": 59, \"to\": 72, \"sentence\": \"White House press secretary Sarah Huckabee Sanders tweeted the president will “meet with those on the front lines of the national security and humanitarian crisis.”\", \"id\": \"polusa_v1_4506763_-1_22_\\\"President Trump_59_72\"}\n{\"mention\": \"Justice Kavanaugh\", \"polarity\": 0, \"from\": 29, \"to\": 46, \"sentence\": \"And I repeated that story to Justice Kavanaugh when I first greeted him here,\\\" Sotomayor said.\", \"id\": \"polusa_v1_4507651_-1_13_Brett Kavanaugh_29_46\"}\n{\"mention\": \"Engaging Trump\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Engaging Trump has rewards.\", \"id\": \"polusa_v1_4508329_-1_1_Engaging Trump_0_16\"}\n{\"mention\": \"James Devine\", \"polarity\": 0, \"from\": 74, \"to\": 86, \"sentence\": \"“We are in a war with selfish, foolish & narcissistic rich people,” wrote James Devine on Twitter.\", \"id\": \"polusa_v1_4509449_-1_3_James Devine_75_87\"}\n{\"mention\": \"former Prime Minister Alain Juppe\", \"polarity\": 0, \"from\": 71, \"to\": 104, \"sentence\": \"MACRON'S PARLIAMENTARY CANDIDATES GATHER IN PARIS\\nPhilippe is close to former Prime Minister Alain Juppe.\", \"id\": \"polusa_v1_4509668_-1_11_former Prime Minister Alain Juppe_72_105\"}\n{\"mention\": \"Philippe\", \"polarity\": 1, \"from\": 12, \"to\": 20, \"sentence\": \"Reacting to Philippe's appointment, Juppe called the new prime minister \\\"a man of great talent\\\" with \\\"all the qualities to handle the difficult job.\\\"\", \"id\": \"polusa_v1_4509668_-1_12_Edouard Philippe_12_20\"}\n{\"mention\": \"Kim\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"Kim is expected to meet President Donald Trump in May or early June.\", \"id\": \"polusa_v1_4512193_-1_12_Kim_0_4\"}\n{\"mention\": \"Levin\", \"polarity\": 0, \"from\": 45, \"to\": 50, \"sentence\": \"CLICK HERE TO GET THE FOX NEWS APP\\nFollowing Levin's rebuttal, Lee seemed to reverse course and claimed she never actually made an official diagnosis of the president, despite her book having various mental health observations about the commander-in-chief.\", \"id\": \"polusa_v1_4512856_-1_18_Mark Levin_46_51\"}\n{\"mention\": \"Sophia\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Sophia is getting older, so she wouldn’t hear it,” he said in July 2017.\", \"id\": \"polusa_v1_4513777_-1_17_Sophia_0_6\"}\n{\"mention\": \"The quartet -- George \\\"Billy\\\" Wagner III, 47; his wife, 48-year-old Angela Wagner; and George's sons, George Wagner, 27, and Edward \\\"Jake\\\" Wagner, 26 --\", \"polarity\": -1, \"from\": 0, \"to\": 152, \"sentence\": \"The quartet -- George \\\"Billy\\\" Wagner III, 47; his wife, 48-year-old Angela Wagner; and George's sons, George Wagner, 27, and Edward \\\"Jake\\\" Wagner, 26 -- spent \\\"some significant time in Alaska\\\" in the two years before their arrest, officials said.\", \"id\": \"polusa_v1_4513777_-1_4_The quartet -- George \\\"Billy\\\" Wagner III, 47; his wife, 48-year-old Angela Wagner; and George's sons, George Wagner, 27, and Edward \\\"Jake\\\" Wagner, 26 --_0_152\"}\n{\"mention\": \"Lewinsky\", \"polarity\": -1, \"from\": 165, \"to\": 173, \"sentence\": \"Hillary Clinton, who went on to be elected to the Senate and served as President Obama’s secretary of state, said 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murder Tuesday after the body of Tibbetts, a 20-year-old University of Iowa student, was discovered in a cornfield about 12 miles southeast of Brooklyn, where she was last seen running.\", \"id\": \"polusa_v1_4609343_-1_6_suspect Cristhian Rivera_1_7\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 15, \"sentence\": \"Hillary Clinton added that she had worked closely with Netanyahu on a \\\"range of issues.\\\"\", \"id\": \"polusa_v1_4609999_-1_28_Hillary Clinton_1_16\"}\n{\"mention\": \"President Trump\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"President Trump's Memorial Day tweets\", \"id\": \"polusa_v1_4612936_-1_0_President Trump_0_15\"}\n{\"mention\": \"Ibrahim\", \"polarity\": -1, \"from\": 27, \"to\": 34, \"sentence\": \"WPTZ-TV reports police say Ibrahim was vandalizing vehicles in the parking lot when the woman confronted him.\", \"id\": \"polusa_v1_4614529_-1_4_32-year-old Burlington resident Abukar Ibrahim_28_35\"}\n{\"mention\": \"the woman\", \"polarity\": 1, \"from\": 84, \"to\": 93, \"sentence\": \"WPTZ-TV reports police say Ibrahim was vandalizing vehicles in the parking lot when the woman confronted him.\", \"id\": \"polusa_v1_4614529_-1_4_a woman who was delivering meals for homeless people at a Vermont motel_85_94\"}\n{\"mention\": \"the two men\", \"polarity\": 0, \"from\": 47, \"to\": 58, \"sentence\": \"The person in touch with Kadirov's family says the two men knew each other only from their days as fellow drivers for the ride-sharing app Uber and were not close friends.\", \"id\": \"polusa_v1_4614698_-1_14_the two men_48_59\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 99, \"to\": 101, \"sentence\": \"\\\"In terms of readiness, it's actually, I believe, so far improving our readiness for deployments,\\\" he said.\", \"id\": \"polusa_v1_4615955_-1_29_Mattis_100_102\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He says among those killed was a senior 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\"id\": \"polusa_v1_4637248_-1_10_Gianno Caldwell_33_41\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She has pleaded not guilty to aiding and abetting her husband and obstructing the investigation.\", \"id\": \"polusa_v1_4638034_-1_14_Salman_0_3\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He is highly biblical.\", \"id\": \"polusa_v1_4638082_-1_17_Donald Trump_0_2\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He said his job, and the job of his staff, was to care for whoever comes through that hospital.\", \"id\": \"polusa_v1_4639995_-1_45_Cohen_0_2\"}\n{\"mention\": \"Mr. Henry\", \"polarity\": 1, \"from\": 89, \"to\": 98, \"sentence\": \"While we most remember him for seven little words, “Give me liberty, or give me death!,” Mr. Henry only cared to be remembered for his 1765 Stamp Act Resolves that set the colonies ablaze for Independence.\", \"id\": \"polusa_v1_4640432_-1_15_Founding Father Patrick Henry_90_99\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 193, \"to\": 208, \"sentence\": \"Democrats have lost the high ground with President Trump on Russia – the one parallel they used to separate their own bold claims of patriotism in the 2016 election – and once again, they have Hillary Clinton to thank for it.\", \"id\": \"polusa_v1_4643592_-1_24_Clinton_194_209\"}\n{\"mention\": \"Kennedy\", \"polarity\": 1, \"from\": 72, \"to\": 79, \"sentence\": \"During a rally in North Dakota on Wednesday, Trump praised the retiring Kennedy as \\\"a very special guy\\\" and \\\"a great man,\\\" telling the crowd he was \\\"very honored\\\" Kennedy chose to retire while Trump was in office because \\\"he felt confident in me to make the right choice and carry on his great legacy.\\\"\", \"id\": \"polusa_v1_4644232_-1_13_Kennedy_73_80\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 45, \"to\": 50, \"sentence\": 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that she takes her last breath from behind bars and she meets the Lord from behind bars,\\\" LaHood said Wednesday.\", \"id\": \"polusa_v1_4658202_-1_12_Bexar County District Attorney Nico LaHood_111_119\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 118, \"to\": 123, \"sentence\": \"Luntz denied the accusations at the time, saying he was focused only on conducting accurate focus groups, noting that Trump \\\"launches an attack on everyone who is even remotely critical.\\\"\", \"id\": \"polusa_v1_4658361_-1_19_Donald Trump_119_124\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 118, \"to\": 123, \"sentence\": \"Luntz denied the accusations at the time, saying he was focused only on conducting accurate focus groups, noting that Trump \\\"launches an attack on everyone who is even remotely critical.\\\"\", \"id\": \"polusa_v1_4658361_-1_19_then-candidate Trump_119_124\"}\n{\"mention\": \"Cummings\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Cummings writes to Ross, \\\"Unfortunately, your actions are part of a pattern.\", \"id\": \"polusa_v1_4659374_-1_6_Chairman Cummings_1_9\"}\n{\"mention\": \"Secretary-General Antonio Guterres\", \"polarity\": 1, \"from\": 0, \"to\": 34, \"sentence\": \"Secretary-General Antonio Guterres says it's unacceptable and appalling that more than 8,000 children were killed and injured in conflicts across the world last year and is urging combatants to do more to protect boys and girls.\", \"id\": \"polusa_v1_4659492_-1_1_Secretary-General Antonio Guterres_0_36\"}\n{\"mention\": \"Vice President Mike Pence\", \"polarity\": 0, \"from\": 30, \"to\": 55, \"sentence\": \"History was made Tuesday when Vice President Mike Pence cast the tie-breaking vote in the Senate to confirm Betsy DeVos as secretary of education.\", \"id\": \"polusa_v1_4660110_-1_2_Vice President Mike Pence_32_57\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 15, \"to\": 20, \"sentence\": \"Marc Thiessen: Trump revoking 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\"Elizabeth\", \"polarity\": 0, \"from\": 75, \"to\": 84, \"sentence\": \"That means to prove a kidnapping took place, prosecutors will have to show Elizabeth was unlawfully removed or had her freedom restricted\\nEstranged wife speaks out\\nCummins' estranged wife, Jill Cummins, was \\\"very emotional\\\" when she learned both were found safe, her attorney, Michael Cox, said.\", \"id\": \"polusa_v1_4665269_-1_50_Elizabeth_76_85\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He loved them all,\\\" Wild said.\", \"id\": \"polusa_v1_4665721_-1_12_Kerry_0_2\"}\n{\"mention\": \"Putin\", \"polarity\": 1, \"from\": 16, \"to\": 21, \"sentence\": \"A great day for Putin, a good one for Trump\", \"id\": \"polusa_v1_4666756_-1_0_Putin_16_21\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 17, \"to\": 22, \"sentence\": \"Story highlights Trump called Scarborough \\\"crazy\\\" and Brzezinski \\\"dumb as a rock\\\"\\nRepublican and Democratic lawmakers rebuked Trump's attacks on the hosts earlier this week\\n'Please just stop.\", \"id\": \"polusa_v1_4668559_-1_2_A defiant President Donald Trump_19_24\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 23, \"to\": 28, \"sentence\": \"\\\"Duterte is a lot like Trump, he's sort of an unpredictable character and clearly the leaders who work best with Trump are the ones who are sort of willing to bury their ego and do things that appeal to Trump's ego,\\\" Connelly said.\", \"id\": \"polusa_v1_4669415_-1_29_President Trump_24_29\"}\n{\"mention\": \"Chief of staff John Kelly\", \"polarity\": 0, \"from\": 92, \"to\": 117, \"sentence\": \"Story highlights Steve Bannon favors the restructuring with Miller in a communications role\\nChief of staff John Kelly is eyeing his former Homeland Security spokesperson, David Lapan\\nWashington (CNN) White House senior policy adviser Stephen Miller is being considered for an elevated communications role, a White House official tells CNN.\", \"id\": \"polusa_v1_4669533_-1_2_Chief of staff John Kelly_94_119\"}\n{\"mention\": \"John Kennedy, R-Louisiana\", \"polarity\": 0, \"from\": 0, \"to\": 25, \"sentence\": \"John Kennedy, R-Louisiana.\", \"id\": \"polusa_v1_4669681_-1_8_John Kennedy, R-Louisiana_0_25\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 108, \"to\": 113, \"sentence\": \"Even the United Kingdom's foreign minister, Boris Johnson, who was once considered his country's version of Trump, called the executive order \\\" divisive and wrong .\\\"\\nTrump, who shows no signs of acting as an ordinary president, is no doubt thrilling some of his supporters.\", \"id\": \"polusa_v1_4670966_-1_10_Donald Trump_109_114\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 80, \"to\": 83, \"sentence\": \"Bergdahl tearfully apologized this week to the service members who searched for him after he deserted.\", \"id\": \"polusa_v1_4672318_-1_31_Retired Navy SEAL Chief Petty Officer James Hatch_81_84\"}\n{\"mention\": \"Private Emmanuel Mensah\", \"polarity\": 1, \"from\": 1, \"to\": 24, \"sentence\": \"\\\"Private Emmanuel Mensah was a first-generation immigrant, a soldier and a New Yorker.\", \"id\": \"polusa_v1_4673744_-1_6_Private Emmanuel Mensah_2_25\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 27, \"to\": 32, \"sentence\": \"Following the meeting with Trump, Gou made a lengthy post on Facebook where he called Trump an \\\"old friend,\\\" adding that they had met for 50 minutes.\", \"id\": \"polusa_v1_4676347_-1_5_Donald Trump_28_33\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 65, \"to\": 70, \"sentence\": \"-- Meanwhile, former Secretary of State Rex Tillerson criticized Trump in another arena: foreign affairs.\", \"id\": \"polusa_v1_4676645_-1_7_US President Donald Trump_66_71\"}\n{\"mention\": \"House Minority Leader Nancy Pelosi\", \"polarity\": 1, \"from\": 23, \"to\": 57, \"sentence\": \"President Trump called House Minority Leader Nancy Pelosi tonight to congratulate her for winning the House, her chief of staff, Drew Hammill, tweeted.\", \"id\": \"polusa_v1_4677519_-1_2_House Minority Leader Nancy Pelosi_25_59\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 20, \"to\": 35, \"sentence\": \"It is shameful that President Trump did not quickly and publicly thank those heroes and their families for giving our country what Abraham Lincoln called \\\"the last full measure of devotion.\\\"\", \"id\": \"polusa_v1_4678127_-1_15_Donald Trump_21_36\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"President Trump is a master of the technique: diversion through distraction and division.\", \"id\": \"polusa_v1_4678127_-1_57_President Trump_0_15\"}\n{\"mention\": \"Kim Jong Un\", \"polarity\": -1, \"from\": 19, \"to\": 30, \"sentence\": \"\\\"That doesn't make Kim Jong Un a smart cookie -- that makes him a murderer.\\\"\\n.@jaketapper responds to @POTUS: \\\"Equatingbrutality and despotism with leadership is not an American value\\\" https://t.co/MGeHJJixJP — The Lead CNN (@TheLeadCNN) May 1, 2017\\nAs Tapper noted, Kim is not the only \\\"brutal dictator\\\" or despot Trump reached out to over the weekend.\", \"id\": \"polusa_v1_4678786_-1_6_Kim Jong Un_20_31\"}\n{\"mention\": \"Kelly\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Kelly comes in with high expectations that his general's sense of hierarchy can bring order to a President who has long thrived on chaos and countless opinions.\", \"id\": \"polusa_v1_4679198_-1_27_Kelly_1_6\"}\n{\"mention\": \"ElZaidy\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"ElZaidy said Gadhafi had been following developments in Libya during his captivity and that he wanted to work on reconciliation and fighting terrorism in Libya.\", \"id\": \"polusa_v1_4679717_-1_21_Khaled ElZaidy_0_8\"}\n{\"mention\": \"Pompeo\", \"polarity\": 0, \"from\": 10, \"to\": 16, \"sentence\": \"\\\"Director Pompeo and has family stayed at an Agency-owned facility for three days over Christmas 2017,\\\" wrote Trapani.\", \"id\": \"polusa_v1_4680811_-1_36_Pompeo_11_17\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 68, \"to\": 73, \"sentence\": \"Muslims wary of being 'tokenized'\\nDuring his presidential campaign, Trump angered many American Muslims by making incendiary statements such as \\\"I think Islam hates us\\\" and promising to temporarily ban Muslim immigration as a counterterrorism measure.\", \"id\": \"polusa_v1_4681625_-1_37_President Trump_69_74\"}\n{\"mention\": \"Yousafzai\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"Yousafzai, the youngest recipient of the Nobel Peace Prize, is expected to meet Prime Minister Shahid Khaqan Abbasi while she is in Islamabad, where the city is on high alert for security due to her visit.\", \"id\": \"polusa_v1_4681979_-1_4_20-year-old Malala Yousafzai_1_10\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 168, \"to\": 171, \"sentence\": \"\\\"What it describes is a professional law enforcement person, who is Jim Comey, who comes up against a president who knows no limits in terms of a proper relationship,\\\" she told CNN's Dana Bash at an event for the CNN series Badass Women of Washington\\nComey took Washington by surprise earlier Wednesday when he allowed the intelligence committee to post his prepared remarks on the committee's website , one day before he's set to testify in a widely-anticipated hearing about his firing by President Donald Trump last month.\", \"id\": \"polusa_v1_4683430_-1_6_Feinstein_169_172\"}\n{\"mention\": \"Balber\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Balber said his client hasn't been interviewed yet and that special counsel Robert Mueller's investigators have not reached out about Emin and Aras Agalarov, whom he also represents.\", \"id\": \"polusa_v1_4684418_-1_6_Balber_1_7\"}\n{\"mention\": \"Anne Hidalgo\", \"polarity\": -1, \"from\": 58, \"to\": 70, \"sentence\": \"In a Facebook post on Tuesday , Klemp accused Paris Mayor Anne Hidalgo of hypocrisy for recognizing her work, citing poor conditions faced by migrants in the French capital.\", \"id\": \"polusa_v1_4686289_-1_3_Anne Hidalgo_59_71\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 9, \"to\": 14, \"sentence\": \"Colwell: Pence received a somewhat lukewarm response from the graduates when his honorary degree was presented just before the speech.\", \"id\": \"polusa_v1_4687064_-1_14_Mike Pence's_10_15\"}\n{\"mention\": \"Pashteen\", \"polarity\": 1, \"from\": 10, \"to\": 18, \"sentence\": \"On Sunday Pashteen will address what could be his largest crowd yet, in Karachi, home to the country's largest urban Pashtun population.\", \"id\": \"polusa_v1_4687698_-1_16_Pashteen_11_19\"}\n{\"mention\": \"Donald Trump for president\", \"polarity\": 0, \"from\": 32, \"to\": 58, \"sentence\": \"Donnelly, whose state voted for Donald Trump for president in 2016, is up for re-election this year.\", \"id\": \"polusa_v1_4689216_-1_8_Donald Trump for president_33_59\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She inspires me to join her on this journey.\", \"id\": \"polusa_v1_4691853_-1_77_Michelle_1_4\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 144, \"to\": 149, \"sentence\": \"Before Friday, Corker had been outspoken with his critiques of the President in the wake of the Charlottesville violence, saying in August that Trump has not been \\\"able to demonstrate the stability nor some of the competence that he needs to demonstrate in order to be successful.\\\"\", \"id\": \"polusa_v1_4693881_-1_11_Donald Trump_145_150\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 27, \"to\": 32, \"sentence\": \"August 17, 2017 -- Corker: Trump hasn't demonstrated the stability or competence to be successful\\nCorker slammed Trump's handling of the racially motivated protests in Charlottesville, charging that the President \\\"has not demonstrated he understands the character of this nation.\\\"\", \"id\": \"polusa_v1_4693881_-1_30_Donald Trump_28_33\"}\n{\"mention\": \"Bob Corker\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Bob Corker met with the President at the White House on Friday afternoon.\", \"id\": \"polusa_v1_4693881_-1_3_Bob Corker_0_10\"}\n{\"mention\": \"Harris\", \"polarity\": 1, \"from\": 25, \"to\": 31, \"sentence\": \"2. Now what for Kamala?: Harris, the California senator, was utterly impressive in Thursday's debate -- commanding a stage and looking more presidential than anyone else on it.\", \"id\": \"polusa_v1_4694303_-1_43_Harris'_26_32\"}\n{\"mention\": \"Jackman\", \"polarity\": 1, \"from\": 118, \"to\": 125, \"sentence\": \"The nation's police and defense forces are working together to ensure a safe and secure environment for the Carnival, Jackman said in video provided by CNN affiliate CNC3 Television.\", \"id\": \"polusa_v1_4695246_-1_6_Jackman_119_126\"}\n{\"mention\": \"Cohen\", \"polarity\": -1, \"from\": 194, \"to\": 199, \"sentence\": \"Stormy Daniels will be interviewed by federal prosecutors from the Southern District of New York on Monday as part of their probe into President Donald Trump's former personal attorney, Michael Cohen, according to a source familiar with the investigation.\", \"id\": \"polusa_v1_4695606_-1_1_Cohen_196_201\"}\n{\"mention\": \"Russian President Vladimir Putin\", \"polarity\": -1, \"from\": 87, \"to\": 119, \"sentence\": \"A GOP lawmaker said he is ashamed that a fellow lawmaker is a Republican after he used Russian President Vladimir Putin's \\\"talking points\\\" to dismiss President Bashar al-Assad's latest actions in the Syrian Civil War.\", \"id\": \"polusa_v1_4697694_-1_1_Russian President Vladimir Putin_89_121\"}\n{\"mention\": \"Tajani\", \"polarity\": 1, \"from\": 28, \"to\": 34, \"sentence\": \"After securing his victory, Tajani suggested that there is neither a need to press ahead with \\\"more\\\" European integration, nor to destroy this successful supranational political project to deal with the current crisis in European politics.\", \"id\": \"polusa_v1_4697739_-1_15_Tajani_29_35\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 26, \"to\": 31, \"sentence\": \"But that's not because of Trump.\", \"id\": \"polusa_v1_4698082_-1_147_President Donald Trump_26_31\"}\n{\"mention\": \"Teddy Roosevelt, the first president to travel abroad\", \"polarity\": 1, \"from\": 0, \"to\": 53, \"sentence\": \"Teddy Roosevelt, the first president to travel abroad, visited Panama City in November 1906.\", \"id\": \"polusa_v1_4698296_-1_7_Teddy Roosevelt, the first president to travel abroad_0_54\"}\n{\"mention\": \"Rodman\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Rodman also endorsed Trump for president in 2016.\", \"id\": \"polusa_v1_4699418_-1_58_former NBA star Dennis Rodman_0_6\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 57, \"to\": 60, \"sentence\": \"With her worldview forever altered by understanding that she wasn't alone, the more Stein learned, the more she felt compelled to leave the cloistered community she had been raised in, and whose religious practices she had long begun to question.\", \"id\": \"polusa_v1_4702797_-1_42_25-year-old Abby Stein_58_61\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 49, \"to\": 52, \"sentence\": \"\\\"We thank everyone around the world who has kept him and our family in their thoughts and prayers.\", \"id\": \"polusa_v1_4703277_-1_35_\\\"Otto Warmbier_49_52\"}\n{\"mention\": \"Mueller\", \"polarity\": -1, \"from\": 46, \"to\": 53, \"sentence\": \"Here's where things get a little trickier for Mueller.\", \"id\": \"polusa_v1_4705936_-1_20_Robert Mueller's_47_54\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 22, \"to\": 26, \"sentence\": \"Baker Kline, who said Bush told her a version of the \\\"David Cop-a-Feel\\\" joke as he groped her, had also been reluctant to share her story publicly.\", \"id\": \"polusa_v1_4706062_-1_46_he (Bush)_23_27\"}\n{\"mention\": \"Trump, himself\", \"polarity\": -1, \"from\": 80, \"to\": 94, \"sentence\": \"Story highlights The 100 days measure is linked to President Franklin Roosevelt\\nTrump, himself, talked repeatedly about his first 100 days when he was campaigning\\nWashington (CNN) President Donald Trump tweeted Friday about the \\\"ridiculous standard\\\" by which he will be judged on his accomplishments during his first 100 days in office.\", \"id\": \"polusa_v1_4706407_-1_2_Trump, himself_81_96\"}\n{\"mention\": \"him\", \"polarity\": 0, \"from\": 21, \"to\": 24, \"sentence\": \"\\\"I would've directed him to do it if I thought he wasn't doing it.\\\"\", \"id\": \"polusa_v1_4706598_-1_8_\\\"Mike_21_24\"}\n{\"mention\": \"Gianforte\", \"polarity\": -1, \"from\": 21, \"to\": 30, \"sentence\": \"JUST WATCHED Jacobs: Gianforte statement worse than assault Replay More Videos ...\", \"id\": \"polusa_v1_4706627_-1_23_Gianforte_22_31\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 22, \"sentence\": \"President Donald Trump's decision to knock London Mayor Sadiq Khan on Monday didn't come out of nowhere.\", \"id\": \"polusa_v1_4708423_-1_1_President Donald Trump_0_24\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 91, \"to\": 96, \"sentence\": \"\\\"The President is to this day the moral leader of the country,\\\" Kaufman said, warning that Trump's propensity to personally attack his opponents would lower the tone further in the wider political debate.\", \"id\": \"polusa_v1_4710514_-1_43_Donald Trump's_92_97\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She's regarded as the front-runner in the race to replace Gov.\", \"id\": \"polusa_v1_4713065_-1_6_South Dakota's Kristi Noem_0_3\"}\n{\"mention\": \"Adam Schiff\", \"polarity\": -1, \"from\": 9, \"to\": 20, \"sentence\": \"Now that Adam Schiff is starting to blame President Obama for Russian meddling in the election, he is probably doing so as yet another excuse that the Democrats, lead by their fearless leader, Crooked Hillary Clinton, lost the 2016 election.\", \"id\": \"polusa_v1_4713403_-1_54_Adam Schiff_10_21\"}\n{\"mention\": \"the President\", \"polarity\": -1, \"from\": 39, \"to\": 52, \"sentence\": \"Flake's prepared speech goes on to say the President's actions should be \\\"a great source of shame\\\" for the Senate and the members of the Republican Party.\", \"id\": \"polusa_v1_4713505_-1_8_President Donald Trump_40_53\"}\n{\"mention\": \"assault Wong\", \"polarity\": -1, \"from\": 109, \"to\": 121, \"sentence\": \"As they arrived, protesters at Taipei's Taoyuan International Airport also screamed insults and attempted to assault Wong.\", \"id\": \"polusa_v1_4714985_-1_11_Joshua Wong_110_122\"}\n{\"mention\": \"George W. Bush's\", \"polarity\": 0, \"from\": 13, \"to\": 29, \"sentence\": \"JUST WATCHED George W. Bush's dog Barney dies Replay More Videos ...\", \"id\": \"polusa_v1_4717187_-1_81_the White House President George H.W. Bush_14_30\"}\n{\"mention\": \"Weinstein\", \"polarity\": -1, \"from\": 152, \"to\": 161, \"sentence\": \"The New York Police Department and the Manhattan District Attorney's office traded public finger-pointing on Tuesday in response to questions about why Weinstein was not charged with a crime after a 2015 sting operation recorded him making potentially incriminating comments to a young woman.\", \"id\": \"polusa_v1_4719033_-1_5_movie mogul Harvey Weinstein_153_162\"}\n{\"mention\": \"Ocasio-Cortez\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"Ocasio-Cortez argued that America must \\\"live up to\\\" the value of freedom by ensuring economic freedom through wage stability.\", \"id\": \"polusa_v1_4719848_-1_25_Alexandria Ocasio-Cortez_1_14\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 22, \"to\": 25, \"sentence\": \"\\\"I just know whatever she was doing, she was so distracted she didn't even apply her brakes at all before crashing full-force into my mom.\\\"\", \"id\": \"polusa_v1_4719854_-1_67_Mucci_22_25\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 72, \"to\": 75, \"sentence\": \"(Witnesses say the woman drove into Mucci's mom's car and never braked, she said.)\", \"id\": \"polusa_v1_4719854_-1_68_Mucci_72_75\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 20, \"to\": 22, \"sentence\": \"And there is no way he would have left.\\\"\", \"id\": \"polusa_v1_4719989_-1_70_Mike Rippey_20_22\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump flew to Texas on Tuesday to meet with state officials and disaster response coordinators in a moment that called for the empathy and humanity befitting an ongoing, large-scale tragedy.\", \"id\": \"polusa_v1_4720836_-1_11_Donald Trump's_0_5\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 244, \"to\": 246, \"sentence\": \"However, with the important caveats that the Court has only been given a few days to study this complex matter and the states may not have fully developed all arguments, it initially appears the Administration has the stronger legal position,\\\" he wrote.\", \"id\": \"polusa_v1_4720920_-1_41_\\\" acting Assistant Attorney General Chad A. Readler_244_246\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 165, \"to\": 170, \"sentence\": \"Rex Tillerson, a secretary of state not known for his eagerness to talk with the media, stepped in front of cameras earlier this month to reaffirm his commitment to Trump after multiple outlets reported that he called the President a \\\"moron\\\" after a meeting earlier this summer.\", \"id\": \"polusa_v1_4723381_-1_12_President Donald Trump_165_170\"}\n{\"mention\": \"Kelly\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Kelly brought more structure to the West Wing and cleaned house, getting rid of several Trump aides who, in his view, were working against the President or providing little benefit.\", \"id\": \"polusa_v1_4723381_-1_30_Kelly_0_5\"}\n{\"mention\": \"Michael A. Nutter\", \"polarity\": 1, \"from\": 0, \"to\": 17, \"sentence\": \"Michael A. Nutter is a CNN contributor, a Columbia University/SIPA professor of professional practice in urban and public policy and the former mayor of Philadelphia.\", \"id\": \"polusa_v1_4723840_-1_5_Michael Nutter_0_18\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump is picking the wrong battle on health care\", \"id\": \"polusa_v1_4726089_-1_0_President Trump_0_5\"}\n{\"mention\": \"Grimm\", \"polarity\": -1, \"from\": 80, \"to\": 85, \"sentence\": \"Indeed, when you compare the presidential vote patterns to the results in 2014, Grimm's performance was among the weakest among Republican incumbents.\", \"id\": \"polusa_v1_4728650_-1_82_Michael Grimm_81_86\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 78, \"to\": 83, \"sentence\": \"Story highlights Trump called the Democrats \\\"hypocrites\\\" for their outrage at Comey's dismissal\\nThe President also suggested he might cancel White House press briefings\\nTrump also denied reports that he asked Comey to pledge his loyalty to him\\n(CNN) President Donald Trump defended the timing of his firing of FBI Director James Comey in an interview Saturday night on Fox News, saying, \\\"There's really no right time to do it.\\\"\", \"id\": \"polusa_v1_4732510_-1_2_FBI Director James Comey_80_85\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 149, \"to\": 156, \"sentence\": \"He disclosed that he is cooperating with the special counsel's office and became the first person inside the Trump's administration to be charged in Mueller's probe.\", \"id\": \"polusa_v1_4732521_-1_4_Mueller_150_157\"}\n{\"mention\": \"Rex Tillerson\", \"polarity\": 1, \"from\": 13, \"to\": 26, \"sentence\": \"Thank you to Rex Tillerson for his service!\", \"id\": \"polusa_v1_4733748_-1_7_Rex Tillerson_13_26\"}\n{\"mention\": \"Barron Trump\", \"polarity\": 1, \"from\": 1, \"to\": 13, \"sentence\": \"\\\"Barron Trump deserves the chance every child does -- to be a kid,\\\" Clinton wrote on her Facebook and Twitter accounts Sunday.\", \"id\": \"polusa_v1_4734400_-1_5_Barron Trump_2_14\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 19, \"to\": 24, \"sentence\": \"Vicente Fox blasts Trump after 'animals' comment\", \"id\": \"polusa_v1_4734744_-1_0_President Donald Trump_19_24\"}\n{\"mention\": \"Rosenstein\", \"polarity\": 1, \"from\": 3, \"to\": 13, \"sentence\": \"If Rosenstein is the man everyone says he is , I believe he will appoint a qualified, independent prosecutor to take over this mess of an investigation.\", \"id\": \"polusa_v1_4740575_-1_43_Rosenstein_3_13\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 72, \"to\": 77, \"sentence\": \"Inclined as he is to vent on Twitter and in calls to friendly TV hosts, Trump is certainly tempted to answer now and at length, even though it could imperil his future and that of the people around him.\", \"id\": \"polusa_v1_4741537_-1_9_President Donald Trump_73_78\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 12, \"to\": 14, \"sentence\": \"Inclined as he is to vent on Twitter and in calls to friendly TV hosts, Trump is certainly tempted to answer now and at length, even though it could imperil his future and that of the people around him.\", \"id\": \"polusa_v1_4741537_-1_9_the man who occupies the Oval Office_13_15\"}\n{\"mention\": \"Saltz\", \"polarity\": 0, \"from\": 197, \"to\": 202, \"sentence\": \"\\\"I want people to recognize and to treat their children if something comes along, because they can make life more enjoyable and help their functioning, but I want them to look for their strength,\\\" Saltz said.\", \"id\": \"polusa_v1_4744686_-1_55_Saltz_198_203\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 9, \"to\": 14, \"sentence\": \"Even so, Trump couldn't bring himself to say he was wrong.\", \"id\": \"polusa_v1_4751249_-1_22_President Trump_10_15\"}\n{\"mention\": \"Weldon\", \"polarity\": -1, \"from\": 29, \"to\": 35, \"sentence\": \"Officials said she told them Weldon had held her captive in his home for the last month and raped her several times.\", \"id\": \"polusa_v1_4751341_-1_7_Stewart Weldon_30_36\"}\n{\"mention\": \"Sessions\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Sessions has drawn fire from Democrats who say his steadfast support of President Donald Trump's candidacy raises questions about whether he will be an independent attorney general.\", \"id\": \"polusa_v1_4753354_-1_9_Jeff Sessions_1_9\"}\n{\"mention\": \"Garland\", \"polarity\": 0, \"from\": 65, \"to\": 72, \"sentence\": \"Gorsuch in his 2002 essay referred to the lengthy nominations of Garland and Roberts to the US Court of Appeals in Washington DC.\", \"id\": \"polusa_v1_4754302_-1_11_Merrick Garland_66_73\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He had special words for the school's Muslim students:\\n\\\"We care about you.\", \"id\": \"polusa_v1_4755932_-1_34_Principal John Bier_1_3\"}\n{\"mention\": \"Murdoch\", \"polarity\": -1, \"from\": 102, \"to\": 109, \"sentence\": \"In the end, despite Trump's expression of support, dozens of advertisers dropped O'Reilly's show, and Murdoch's sons forced the host out.\", \"id\": \"polusa_v1_4757863_-1_35_\\\" the Australian-born Murdoch_103_110\"}\n{\"mention\": \"Jeffrey Sachs\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"Jeffrey Sachs is a professor and director of the Center for Sustainable Development at Columbia University.\", \"id\": \"polusa_v1_4758756_-1_2_Jeffrey Sachs_0_15\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 15, \"to\": 17, \"sentence\": \"One week after he screamed at people speaking Spanish in a New York City cafe -- a rant captured on video that quickly went viral -- attorney Aaron Schlossberg says he's not a racist and is \\\"deeply sorry\\\" for his actions.\", \"id\": \"polusa_v1_4759298_-1_1_Attorney in rant that went viral_17_19\"}\n{\"mention\": \"attorney Aaron Schlossberg\", \"polarity\": -1, \"from\": 133, \"to\": 159, \"sentence\": \"One week after he screamed at people speaking Spanish in a New York City cafe -- a rant captured on video that quickly went viral -- attorney Aaron Schlossberg says he's not a racist and is \\\"deeply sorry\\\" for his actions.\", \"id\": \"polusa_v1_4759298_-1_1_attorney Aaron Schlossberg_135_161\"}\n{\"mention\": \"the Dallas Morning News\", \"polarity\": 0, \"from\": 94, \"to\": 117, \"sentence\": \"Conaway did not immediately respond to CNN's request for a comment on the 2016 interview with the Dallas Morning News.\", \"id\": \"polusa_v1_4762540_-1_27_the Dallas Morning News_95_118\"}\n{\"mention\": \"New Hampshire\", \"polarity\": 0, \"from\": 37, \"to\": 50, \"sentence\": \"Those show the range of reactions in New Hampshire to President Donald Trump's characterization of the state as a \\\" drug-infested den\\\" while speaking to Mexican President Enrique Peña Nieto in January.\", \"id\": \"polusa_v1_4763424_-1_4_New Hampshire_38_51\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 54, \"to\": 76, \"sentence\": \"Those show the range of reactions in New Hampshire to President Donald Trump's characterization of the state as a \\\" drug-infested den\\\" while speaking to Mexican President Enrique Peña Nieto in January.\", \"id\": \"polusa_v1_4763424_-1_4_President Donald Trump_55_77\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 158, \"to\": 160, \"sentence\": \"Trump left the impromptu briefing room without taking questions, having delivered the first emergency foreign policy statement of his presidency,\\nBut even as he confronted one of the gravest matters of his office, Trump nonetheless found it impossible to resist dropping in on a nearby wedding reception, already underway in his treasured Grand Ballroom.\", \"id\": \"polusa_v1_4764095_-1_36_Abe_159_161\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump left the impromptu briefing room without taking questions, having delivered the first emergency foreign policy statement of his presidency,\\nBut even as he confronted one of the gravest matters of his office, Trump nonetheless found it impossible to resist dropping in on a nearby wedding reception, already underway in his treasured Grand Ballroom.\", \"id\": \"polusa_v1_4764095_-1_36_Trump_0_6\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 36, \"to\": 41, \"sentence\": \"Doug Mills/The New York Times/Redux\\nTrump received a heaping of praise from Republican leaders Wednesday following the passage of the GOP tax bill, and some of the strongest praise came from Vice President Mike Pence.\", \"id\": \"polusa_v1_4766164_-1_16_President Donald Trump_37_42\"}\n{\"mention\": \"James Comey\", \"polarity\": -1, \"from\": 69, \"to\": 80, \"sentence\": \"When will people start saying, \\\"thank you, Mr. President, for firing James Comey?\\\"\", \"id\": \"polusa_v1_4772500_-1_16_James 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Alexander is a CNN law enforcement analyst and deputy mayor of Rochester, New York.\", \"id\": \"polusa_v1_4772649_-1_2_Sheriff Joe Arpaio_58_64\"}\n{\"mention\": \"Reschenthaler\", \"polarity\": -1, \"from\": 16, \"to\": 29, \"sentence\": \"A spokesman for Reschenthaler's campaign for did not return multiple requests for comment.\", \"id\": \"polusa_v1_4778866_-1_11_Guy Reschenthaler_17_30\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He faces up to five years in prison and a $250,000 fine.\", \"id\": \"polusa_v1_4779811_-1_18_Francis_0_2\"}\n{\"mention\": \"Amundson\", \"polarity\": -1, \"from\": 67, \"to\": 75, \"sentence\": \"After he was interviewed by federal investigators in October 2013, Amundson deleted all correspondence between himself and Francis from his private email account, the statement said.\", \"id\": \"polusa_v1_4779811_-1_9_\\\"Amundson_68_76\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 6, \"to\": 8, \"sentence\": 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operatives claim to have compromising personal and financial information about Trump, multiple US officials with direct knowledge of the briefings.\", \"id\": \"polusa_v1_4785748_-1_11_President-elect Donald Trump_1_6\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 29, \"to\": 32, \"sentence\": \"To prove how deeply personal she thinks it is, the Wisconsin politician provided her own story: \\\"For me, I was a child who had a very serious illness and then was labeled as a kid with a pre-existing condition.\", \"id\": \"polusa_v1_4787991_-1_5_Democratic Senator Tammy Baldwin_30_33\"}\n{\"mention\": \"the Pentagon\", \"polarity\": 0, \"from\": 396, \"to\": 408, \"sentence\": \"Story highlights Defense Secretary James Mattis announced an advisory panel would make recommendations on implementation of Trump's directive\\nTransgender troops have been openly serving in the military since June 2016\\nWashington (CNN) Transgender members of the military will be able to re-enlist for 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was affected by the concussion, end of story, done,\\\" Wuco said.\", \"id\": \"polusa_v1_4916581_-1_48_Hillary Clinton_44_51\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 80, \"to\": 92, \"sentence\": \"Now that he's about to assume office, the real costs of the \\\"great, great\\\" wall Donald Trump promised to build during his campaign are beginning to settle in -- and threaten to divide the President-elect and thrifty Republicans on Capitol Hill.\", \"id\": \"polusa_v1_4929705_-1_1_Donald Trump_82_94\"}\n{\"mention\": \"the real costs of the \\\"great, great\\\" wall Donald Trump\", \"polarity\": -1, \"from\": 38, \"to\": 92, \"sentence\": \"Now that he's about to assume office, the real costs of the \\\"great, great\\\" wall Donald Trump promised to build during his campaign are beginning to settle in -- and threaten to divide the President-elect and thrifty Republicans on Capitol Hill.\", \"id\": \"polusa_v1_4929705_-1_1_the real costs of the \\\"great, great\\\" wall Donald Trump_40_94\"}\n{\"mention\": \"Karadzic\", \"polarity\": -1, \"from\": 13, \"to\": 21, \"sentence\": \"Like Mladic, Karadzic had been hiding in plain sight in Serbia.\", \"id\": \"polusa_v1_4934223_-1_44_Karadzic_13_21\"}\n{\"mention\": \"Daniels'\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Daniels' friend and fellow adult film actress Alana Evans, who has publicly tried to corroborate Daniels' claims of an affair, also said she will file her own defamation claims by the end of the month.\", \"id\": \"polusa_v1_4935121_-1_23_Daniels_0_8\"}\n{\"mention\": \"Aya\", \"polarity\": 1, \"from\": 44, \"to\": 47, \"sentence\": \"President Donald Trump hailed the return of Aya Hijazi, an Egyptian-American aid worker, in the Oval Office on Friday, telling the American charity worker she showed \\\"great strength\\\" in her ordeal.\", \"id\": \"polusa_v1_4938074_-1_1_Aya_46_49\"}\n{\"mention\": \"Spicer\", \"polarity\": 0, \"from\": 33, \"to\": 39, 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\"from\": 139, \"to\": 141, \"sentence\": \"\\\"If @RepMarkMeadows, @Jim_Jordan and @Raul_Labrador would get on board we would have both great healthcare and massive tax cuts & reform,\\\" he tweeted.\", \"id\": \"polusa_v1_52866909_-1_3_President Trump_140_142\"}\n{\"mention\": \"Jay Inslee\", \"polarity\": 1, \"from\": 0, \"to\": 10, \"sentence\": \"Jay Inslee Says Washington State Is A 'Template For Success' For The U.S.\\nEnlarge this image toggle caption Karen Ducey/Getty Images Karen Ducey/Getty Images\\nWashington Gov.\", \"id\": \"polusa_v1_52869138_-1_3_Jay Inslee_0_10\"}\n{\"mention\": \"incumbent President Jokowi Widodo and a former Suharto-era general\", \"polarity\": 0, \"from\": 201, \"to\": 267, \"sentence\": \"Indonesia's Presidential Race Shows Islamic Fundamentalism Is Gaining Traction Indonesia, the world's most populous Muslim country, is set to go to the polls Wednesday, when voters will choose between incumbent President Jokowi Widodo and a former Suharto-era 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Back in 2001, Burningham offered to donate his stem cells to his sister for a transplant.\", \"id\": \"polusa_v1_52894537_-1_5_Grant Burningham_125_135\"}\n{\"mention\": \"Jim Hoy\", \"polarity\": 0, \"from\": 22, \"to\": 29, \"sentence\": \"Doctors told Toni and Jim Hoy their young son needed intensive, specialized care away from home — institutional services that cost at least $100,000 a year.\", \"id\": \"polusa_v1_52894894_-1_1_Jim Hoy_24_31\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": 0, \"from\": 124, \"to\": 133, \"sentence\": \"\\\"I believe it is vital that the President be able to focus on his never-ending tasks with as few distractions as possible,\\\" Kavanaugh wrote.\", \"id\": \"polusa_v1_52895117_-1_23_Nominee Judge Brett Kavanaugh_125_134\"}\n{\"mention\": \"Jimmy Carter\", \"polarity\": 0, \"from\": 47, \"to\": 59, \"sentence\": \"President Donald Trump called former President Jimmy Carter for the first time this weekend.\", \"id\": \"polusa_v1_52896375_-1_4_Jimmy 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to poison him.\", \"id\": \"polusa_v1_55174895_-1_25_Michael Christopher Mejia's_82_87\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 148, \"to\": 151, \"sentence\": \"His grandmother also called probation saying that was afraid for her safety, that Mejia was still doing drugs and that he was paranoid and claiming she was trying to poison him.\", \"id\": \"polusa_v1_55174895_-1_25_His grandmother_148_151\"}\n{\"mention\": \"Jason Kessler\", \"polarity\": -1, \"from\": 92, \"to\": 105, \"sentence\": \"\\\"Heather Heyer was a fat, disgusting Communist,\\\" said the tweet on the account belonging to Jason Kessler .\", \"id\": \"polusa_v1_55176954_-1_2_Jason Kessler_93_106\"}\n{\"mention\": \"Heyer\", \"polarity\": -1, \"from\": 9, \"to\": 14, \"sentence\": \"\\\"Heather Heyer was a fat, disgusting Communist,\\\" said the tweet on the account belonging to Jason Kessler .\", \"id\": \"polusa_v1_55176954_-1_2_Heyer_10_15\"}\n{\"mention\": \"Abbas\", \"polarity\": 1, \"from\": 18, 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Miranda, Jr., that is raising money and giving aid to the victims in the island.\", \"id\": \"polusa_v1_55304922_-1_10_'Hamilton' creator Lin-Manuel Miranda_125_132\"}\n{\"mention\": \"Ex-FBI official McCabe\", \"polarity\": -1, \"from\": 0, \"to\": 22, \"sentence\": \"Ex-FBI official McCabe speaks out, comes under fire from both Trump and DOJ\", \"id\": \"polusa_v1_55306356_-1_0_Ex-FBI official McCabe_0_22\"}\n{\"mention\": \"McCabe\", \"polarity\": -1, \"from\": 79, \"to\": 85, \"sentence\": \"White House press secretary Sarah Sanders, meanwhile, said in a statement that McCabe \\\"was fired in total disgrace from the FBI because he lied to investigators on multiple occasions, including under oath.\\\"\", \"id\": \"polusa_v1_55306356_-1_29_McCabe_80_86\"}\n{\"mention\": \"McCabe\", \"polarity\": -1, \"from\": 79, \"to\": 85, \"sentence\": \"White House press secretary Sarah Sanders, meanwhile, said in a statement that McCabe \\\"was fired in total disgrace from the FBI because he 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their honeymoon and a month later \\\"physically prevented me from leaving the house.\\\"\", \"id\": \"polusa_v1_55307379_-1_17_Rob Porter_32_38\"}\n{\"mention\": \"Willoughby\", \"polarity\": 0, \"from\": 137, \"to\": 147, \"sentence\": \"The allegations surfaced Tuesday against Rob Porter, an influential senior aide in the Trump administration, from two ex-wives: Jennifer Willoughby and Colbie Holderness.\", \"id\": \"polusa_v1_55307379_-1_3_Willoughby_138_148\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 46, \"to\": 49, \"sentence\": \"Some in the White House were quick to jump to his defense.\", \"id\": \"polusa_v1_55307379_-1_8_Rob Porter_46_49\"}\n{\"mention\": \"Josue\", \"polarity\": 0, \"from\": 72, \"to\": 77, \"sentence\": \"There was no DNA from Jackson found on Josue's clothing and no DNA from Josue on Jackson's clothing, he said.\", \"id\": \"polusa_v1_55307876_-1_10_Josue_72_77\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 31, \"to\": 38, \"sentence\": \"\\\"I worked as hard as I could,\\\" Sanders said Sunday.\", \"id\": \"polusa_v1_55308047_-1_10_Bernie Sanders_32_39\"}\n{\"mention\": \"Japanese\", \"polarity\": 0, \"from\": 60, \"to\": 68, \"sentence\": \"Trump awards sumo trophy as Tokyo charm offensive continues\\nJapanese Prime Minister Shinzo Abe is courting Trump with three things close to his heart: wrestling matches, burgers and golf.\", \"id\": \"polusa_v1_55314060_-1_2_Japanese_62_70\"}\n{\"mention\": \"Shinzo Abe\", \"polarity\": 1, \"from\": 84, \"to\": 94, \"sentence\": \"Trump awards sumo trophy as Tokyo charm offensive continues\\nJapanese Prime Minister Shinzo Abe is courting Trump with three things close to his heart: wrestling matches, burgers and golf.\", \"id\": \"polusa_v1_55314060_-1_2_Shinzo Abe_86_96\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 48, \"to\": 56, \"sentence\": \"But, three different sources told NBC News that Smollett’s brief experience with the criminal justice system hardly qualifies as a diverted case.\", \"id\": \"polusa_v1_55315159_-1_21_actor Jussie Smollett_49_57\"}\n{\"mention\": \"NBC News\", \"polarity\": 0, \"from\": 34, \"to\": 42, \"sentence\": \"But, three different sources told NBC News that Smollett’s brief experience with the criminal justice system hardly qualifies as a diverted case.\", \"id\": \"polusa_v1_55315159_-1_21_NBC News_35_43\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Smollett also declared himself exonerated — though he was not — and as a victim of both a hate crime and a system with a poor track record of treating people of color with fairness.\", \"id\": \"polusa_v1_55315159_-1_7_Smollett_0_8\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Smollett also declared himself exonerated — though he was not — and as a victim of both a hate crime and a system with a poor track record of treating people of color with fairness.\", \"id\": \"polusa_v1_55315159_-1_7_actor Jussie Smollett_0_8\"}\n{\"mention\": \"Wolf\", \"polarity\": -1, \"from\": 101, \"to\": 105, \"sentence\": \"After peppering her speech with several swear words as well as references to sex acts and genitalia, Wolf was criticized by an uneasy alliance of both supposedly free-speech obsessed conservatives and supposedly free-speech obsessed journalists.\", \"id\": \"polusa_v1_55315791_-1_12_comedian Michelle Wolf_101_105\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 5, \"to\": 10, \"sentence\": \"That Trump is ineffective and only out to enrich himself and his wealthy friends.\", \"id\": \"polusa_v1_55318659_-1_53_President Trump_5_10\"}\n{\"mention\": \"Zhang\", \"polarity\": -1, \"from\": 7, \"to\": 12, \"sentence\": \"Yujing Zhang, the Chinese citizen arrested at Mar-a-Lago while President Trump was visiting Florida in March, was indicted Friday on two counts.\", \"id\": \"polusa_v1_55319200_-1_1_Zhang_9_14\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 48, \"to\": 51, \"sentence\": \"Federal authorities told a judge on Monday that she lied repeatedly to Secret Service agents while carrying computer malware unlike anything a government analyst had ever seen.\", \"id\": \"polusa_v1_55319200_-1_7_Zhang_48_51\"}\n{\"mention\": \"Secret Service\", \"polarity\": 0, \"from\": 71, \"to\": 85, \"sentence\": \"Federal authorities told a judge on Monday that she lied repeatedly to Secret Service agents while carrying computer malware unlike anything a government analyst had ever seen.\", \"id\": \"polusa_v1_55319200_-1_7_Secret Service_71_85\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 88, \"to\": 93, \"sentence\": \"Shortly after Trump took office in January, Yates informed the White House she believed Flynn had misled senior administration officials about his communications with the Russian ambassador to the U.S., and warned that Flynn was potentially vulnerable to Russian blackmail, current and former U.S. officials told the Washington Post.\", \"id\": \"polusa_v1_55320007_-1_7_Michael Flynn_89_94\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 89, \"to\": 92, \"sentence\": \"Gerald Herbert / AP file\\nThursday's hearing is Kraninger's first public appearance since her nomination.\", \"id\": \"polusa_v1_55323155_-1_17_Deputy Assistant Secretary for Policy Kathy Kraninger_89_92\"}\n{\"mention\": \"Foxx\", \"polarity\": -1, \"from\": 25, \"to\": 29, \"sentence\": \"Almost immediately after Foxx's office dismissed the charges, Chicago Mayor Rahm Emanuel blasted prosecutors saying it was a \\\"whitewash of justice.\\\"\", \"id\": \"polusa_v1_55323316_-1_16_Foxx_26_30\"}\n{\"mention\": \"Putin\", \"polarity\": -1, \"from\": 50, \"to\": 55, \"sentence\": \"Asked what she makes of criticism leveled against Putin, she responded: “I wouldn't draw him if I had even a hint of negativity toward him.\", \"id\": \"polusa_v1_55323916_-1_40_Putin_51_56\"}\n{\"mention\": \"Karpowitz\", \"polarity\": 0, \"from\": 10, \"to\": 19, \"sentence\": \"But Chris Karpowitz, a political science professor at Utah's Brigham Young University, said there is genuine consternation in Utah about Chaffetz, who nevertheless remains a popular political figure in the state.\", \"id\": \"polusa_v1_55325778_-1_26_Karpowitz_11_20\"}\n{\"mention\": \"Chaffetz\", \"polarity\": -1, \"from\": 55, \"to\": 63, \"sentence\": \"Now, however, there are \\\"plenty of warning signs\\\" that Chaffetz might have trouble with a well-funded Democrat like Kathryn Allen, who is vying for his seat, said Karpowitz.\", \"id\": \"polusa_v1_55325778_-1_32_Chaffetz_56_64\"}\n{\"mention\": \"Karpowitz\", \"polarity\": 0, \"from\": 163, \"to\": 172, \"sentence\": \"Now, however, there are \\\"plenty of warning signs\\\" that Chaffetz might have trouble with a well-funded Democrat like Kathryn Allen, who is vying for his seat, said Karpowitz.\", \"id\": \"polusa_v1_55325778_-1_32_Karpowitz_164_173\"}\n{\"mention\": \"Chaffetz\", \"polarity\": 1, \"from\": 21, \"to\": 29, \"sentence\": \"\\\"For nearly a decade Chaffetz has been a mainstay of Utah political life,\\\" the conservative Deseret News wrote in an editorial last month thanking him for his service.\", \"id\": \"polusa_v1_55325778_-1_8_Chaffetz_22_30\"}\n{\"mention\": \"Biden\", \"polarity\": 1, \"from\": 25, \"to\": 30, \"sentence\": \"ANALYSIS: At the debate, Biden revived his long-ago support for local school control.\", \"id\": \"polusa_v1_55328243_-1_1_Biden_27_32\"}\n{\"mention\": \"Kamala Harris\", \"polarity\": 0, \"from\": 4, \"to\": 17, \"sentence\": \"For Kamala Harris and Joe Biden, integration's painful past becomes the present\\nAnalysis: In the debate, Biden revived his long-ago support for local school control.\", \"id\": \"polusa_v1_55328243_-1_3_Kamala Harris_6_19\"}\n{\"mention\": \"Gianforte\", \"polarity\": -1, \"from\": 200, \"to\": 209, \"sentence\": \"Gianforte, 55, a technology entrepreneur, had been leading Democrat Rob Quist and Libertarian Mark Wicks in opinion polls before Wednesday night, when Ben Jacobs, a reporter for The Guardian, accused Gianforte of having \\\"body slammed\\\" him at a campaign event.\", \"id\": \"polusa_v1_55328355_-1_3_Gianforte_201_210\"}\n{\"mention\": \"Jacobs\", \"polarity\": 0, \"from\": 155, \"to\": 161, \"sentence\": \"Gianforte, 55, a technology entrepreneur, had been leading Democrat Rob Quist and Libertarian Mark Wicks in opinion polls before Wednesday night, when Ben Jacobs, a reporter for The Guardian, accused Gianforte of having \\\"body slammed\\\" him at a campaign event.\", \"id\": \"polusa_v1_55328355_-1_3_Jacobs_156_162\"}\n{\"mention\": \"LORI WALLACH\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"LORI WALLACH: But it's not middle class.\", \"id\": \"polusa_v1_55332357_-1_446_Lori Wallach_0_13\"}\n{\"mention\": \"CHRIS HAYES\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"CHRIS HAYES: Totally, yeah.\", \"id\": \"polusa_v1_55332357_-1_454_CHRIS HAYES_0_12\"}\n{\"mention\": \"Hotez\", \"polarity\": -1, \"from\": 52, \"to\": 57, \"sentence\": \"It’s not difficult to find personal attacks against Hotez on the internet, including blogs that outright call him a liar.\", \"id\": \"polusa_v1_55333427_-1_48_Hotez_53_58\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 101, \"to\": 104, \"sentence\": \"Montgomery County Sheriff's Office\\nIvey, 72, will be the second woman to be governor of Alabama when she is sworn in Monday evening, the sources said.\", \"id\": \"polusa_v1_55336076_-1_20_Robert Bentley_101_104\"}\n{\"mention\": \"Bob Menendez\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Bob Menendez has been dragged down by sky-high disapproval ratings after escaping a guilty verdict when his federal corruption trial ended in a mistrial last year.\", \"id\": \"polusa_v1_55336268_-1_5_Bob Menendez_0_12\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He had changed his story several times following Wall's disappearance.\", \"id\": \"polusa_v1_55339000_-1_16_Danish submarine inventor Peter Madsen_0_2\"}\n{\"mention\": \"King\", \"polarity\": -1, \"from\": 49, \"to\": 53, \"sentence\": \"Tuesday brought the latest spate of bad news for King—National Republican Congressional Committee chairman Steve Stivers disavowing him by declaring he must \\\"stand up against white supremacy and hate.\\\"\", \"id\": \"polusa_v1_55339755_-1_5_Steve King_50_54\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 56, \"to\": 71, \"sentence\": \"Bob Corker, R-Tenn., and Jeff Flake, R-Ariz., denounced President Trump, calling him unfit and devoid of moral leadership.\", \"id\": \"polusa_v1_55341496_-1_6_President Trump_56_71\"}\n{\"mention\": \"Corker\", \"polarity\": 0, \"from\": 80, \"to\": 86, \"sentence\": \"\\\"His governing model is to divide and to attempt to bully and to use untruths,” Corker said.\", \"id\": \"polusa_v1_55341496_-1_7_Corker_81_87\"}\n{\"mention\": \"Jim Acosta\", \"polarity\": 0, \"from\": 52, \"to\": 62, \"sentence\": \"CNN files lawsuit against Trump administration over Jim Acosta's press credentials\", \"id\": \"polusa_v1_55344385_-1_0_correspondent Jim Acosta_52_62\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 12, \"to\": 19, \"sentence\": \"On Tuesday, Sanders responded to the suit, saying that CNN has nearly 50 other pass holders and that \\\"Acosta is no more or less special than any other media outlet or reporter with respect to the First Amendment.\\\"\", \"id\": \"polusa_v1_55344385_-1_8_Sanders_13_20\"}\n{\"mention\": \"the president\", \"polarity\": -1, \"from\": 42, \"to\": 55, \"sentence\": \"Citing North Korea's blistering rhetoric, the president pulled out of the planned June 12 talks and also threatened military action.\", \"id\": \"polusa_v1_55345929_-1_8_Vice President Mike Pence_42_55\"}\n{\"mention\": \"North Korea's\", \"polarity\": -1, \"from\": 7, \"to\": 20, \"sentence\": \"Citing North Korea's blistering rhetoric, the president pulled out of the planned June 12 talks and also threatened military action.\", \"id\": \"polusa_v1_55345929_-1_8_North Korea_7_20\"}\n{\"mention\": \"Edwards\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Edwards used abuse and threats to force 39-year-old John Christopher Smith to work as a J&J Cafeteria cook from 2009 until 2014, authorities said.\", \"id\": \"polusa_v1_55346059_-1_5_Edwards_1_8\"}\n{\"mention\": \"McConnell\", \"polarity\": 0, \"from\": 23, \"to\": 32, \"sentence\": \"The bottom line: While McConnell and his allies aim to reduce Bannon's influence with Trump and with base Republican voters, he has no intention of backing down.\", \"id\": \"polusa_v1_55346170_-1_26_McConnell_24_33\"}\n{\"mention\": \"Chris\", \"polarity\": -1, \"from\": 26, \"to\": 31, \"sentence\": \"Because of this incident, Chris was arraigned on July 7 on one count of interfering with electronic communications, a felony, and one count of malicious destruction of a building under $200, a misdemeanor.\", \"id\": \"polusa_v1_55348041_-1_35_Chris_26_31\"}\n{\"mention\": \"Chris\", \"polarity\": -1, \"from\": 26, \"to\": 31, \"sentence\": \"Because of this incident, Chris was arraigned on July 7 on one count of interfering with electronic communications, a felony, and one count of malicious destruction of a building under $200, a misdemeanor.\", \"id\": \"polusa_v1_55348041_-1_35_Theresa Lockhart_26_31\"}\n{\"mention\": \"Theresa\", \"polarity\": 0, \"from\": 37, \"to\": 44, \"sentence\": \"Senior Deputy Police Chief Blue said Theresa’s case is open, ongoing and active.\", \"id\": \"polusa_v1_55348041_-1_61_Theresa_38_45\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 75, \"to\": 87, \"sentence\": \"Play Facebook\\nTwitter\\nGoogle Plus\\nEmbed Michael Moore explains how to stop Donald Trump 11:17 autoplay autoplay Copy this code to your website or blog\\nSeveral Republican congress members have faced raucous town halls during the last week.\", \"id\": \"polusa_v1_55349981_-1_6_Donald Trump's_76_88\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 52, \"to\": 54, \"sentence\": \"“The DOJ wanted to make this case about bathrooms,” he explained.\", \"id\": \"polusa_v1_55350100_-1_28_Nevins_53_55\"}\n{\"mention\": \"Steinfeld\", \"polarity\": 0, \"from\": 53, \"to\": 62, \"sentence\": \"Vrba told investigators he initially tried to poison Steinfeld, then described how he stabbed Steinfeld in the living room of Calderas' mobile home, Deputy Rowdy Douglas wrote in a probable cause statement.\", \"id\": \"polusa_v1_55350780_-1_29_Lee Steinfeld_54_63\"}\n{\"mention\": \"Freeman\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Freeman, a former mixed martial arts fighter from Florida, is now responsible for burying Manson's body, which has remained at the Kern County morgue since November.\", \"id\": \"polusa_v1_55351795_-1_12_Freeman_1_8\"}\n{\"mention\": \"Sheriff Arpaio\", \"polarity\": 1, \"from\": 43, \"to\": 57, \"sentence\": \"RELATED: Trump Strongly Hits At Pardon for Sheriff Arpaio\\nBeyond settling his personal scores with the media and the Arizona senators Trump did not disappoint in his immigration message.\", \"id\": \"polusa_v1_55354307_-1_14_Sheriff Arpaio_44_59\"}\n{\"mention\": \"Vega\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Vega said he is confident The Paint Spot will win the appeal.\", \"id\": \"polusa_v1_55358586_-1_49_Enriquez_1_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 57, \"to\": 62, \"sentence\": \"But if he loses, he said, Enriquez could be saddled with Trump legal fees and might face bankruptcy.\", \"id\": \"polusa_v1_55358586_-1_50_Donald Trump_57_62\"}\n{\"mention\": \"Vega\", \"polarity\": 1, \"from\": 184, \"to\": 188, \"sentence\": \"\\\"The Paint Spot is also owned by a proud small business owner... and he felt and we agreed that he was right factually and legally and therefore, we both decided to take on the risk,\\\" Vega said.\", \"id\": \"polusa_v1_55358586_-1_53_Enriquez_185_189\"}\n{\"mention\": \"Trump National\", \"polarity\": -1, \"from\": 163, \"to\": 177, \"sentence\": \"That businessman, Juan Carlos Enriquez, owner of The Paint Spot, won the first round of the legal skirmish last summer when a judge found a lien he slapped on the Trump National Doral golf resort was valid.\", \"id\": \"polusa_v1_55358586_-1_6_Donald Trump_164_178\"}\n{\"mention\": \"Duterte\", \"polarity\": 1, \"from\": 44, \"to\": 51, \"sentence\": \"But back at home, Heydarian said, many \\\"see Duterte as a caring and sincere leader, who actually wants to make the Philippines a better place by adopting an outside-of-the-box approach.\\\"\", \"id\": \"polusa_v1_55361755_-1_49_Rodrigo Duterte_45_52\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 105, \"to\": 107, \"sentence\": \"His brother \\\"will be the most dynamic 70-something-year-old you've ever met in your entire life,\\\" should he run, he said.\", \"id\": \"polusa_v1_55362630_-1_46_Frank Biden_105_107\"}\n{\"mention\": \"Gorsuch\", \"polarity\": -1, \"from\": 29, \"to\": 36, \"sentence\": \"Latino Legal Groups React to Gorsuch Nomination with Wariness, Concerns\", \"id\": \"polusa_v1_55363300_-1_0_Gorsuch_29_36\"}\n{\"mention\": \"Gorsuch\", \"polarity\": -1, \"from\": 29, \"to\": 36, \"sentence\": \"Latino Legal Groups React to Gorsuch Nomination with Wariness, Concerns\", \"id\": \"polusa_v1_55363300_-1_0_Supreme Court Nominee Neil Gorsuch_29_36\"}\n{\"mention\": \"Jan Jordan's\", \"polarity\": -1, \"from\": 54, \"to\": 66, \"sentence\": \"Pinellas County Sheriff Bob Gualtieri said that Capt. Jan Jordan's response during the Feb. 14 massacre was crippled by the county's radio system.\", \"id\": \"polusa_v1_55366297_-1_1_Jan Jordan's_56_68\"}\n{\"mention\": \"pro-Trump\", \"polarity\": 0, \"from\": 79, \"to\": 88, \"sentence\": \"Police used pepper spray to disperse hundreds of protesters gathered outside a pro-Trump dinner billed as 'DeploraBall' on the eve of his swearing-in.\", \"id\": \"polusa_v1_55375829_-1_1_pro-Trump_81_90\"}\n{\"mention\": \"Albright\", \"polarity\": 1, \"from\": 9, \"to\": 17, \"sentence\": \"Jonathan Albright, a Columbia University researcher who directs a center on digital forensics, told NBC News that the amount of anti-Semitic material posted to Instagram and tied to Soros was possibly the worst sample of hate speech he had seen on the popular photo-sharing app.\", \"id\": \"polusa_v1_55377849_-1_8_Albright_10_18\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 17, \"to\": 22, \"sentence\": \"President Donald Trump has made little progress on some of his key campaign promises in his first 100 days as president.\", \"id\": \"polusa_v1_55380678_-1_3_Donald Trump that divided a nation_19_24\"}\n{\"mention\": \"DOOCY\", \"polarity\": 0, \"from\": 47, \"to\": 52, \"sentence\": \"Here’s what Giuliani said on Fox this morning:\\nDOOCY: So you’re saying that Stephanie Clifford, made these allegations, told Donald trump’s lawyer—GUILIANI: And denied them.\", \"id\": \"polusa_v1_55380890_-1_40_DOOCY_48_53\"}\n{\"mention\": \"CHUCK TODD:\", \"polarity\": 0, \"from\": 80, \"to\": 91, \"sentence\": \"CHUCK ROSENBERG:\\nYeah, there's a difference between describing what you find --\\nCHUCK TODD:\\nYes.\", \"id\": \"polusa_v1_55389599_-1_406_CHUCK TODD:_80_93\"}\n{\"mention\": \"Mineta\", \"polarity\": 0, \"from\": 4, \"to\": 10, \"sentence\": \"And Mineta served as Commerce secretary for Clinton and Transportation secretary for George W. Bush until 2006.\", \"id\": \"polusa_v1_55395336_-1_91_Norman Y. Mineta_4_10\"}\n{\"mention\": \"Representative Hurd\", \"polarity\": 0, \"from\": 0, \"to\": 19, \"sentence\": \"Representative Hurd won his seat by under 1 percent of the vote, about three thousand votes, yet Hillary Clinton won the vote against Donald Trump in District 23.\", \"id\": \"polusa_v1_55395995_-1_22_Republican Will Hurd_0_19\"}\n{\"mention\": \"Kent\", \"polarity\": 0, \"from\": 36, \"to\": 40, \"sentence\": \"Satwinder Kaur Courtesy of Kaur for Kent campaign.\", \"id\": \"polusa_v1_55396423_-1_24_Kent_37_41\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 42, \"to\": 45, \"sentence\": \"As a lifetime member of the denomination, she said Owens’ election means that there will be a leading voice for justice and equality for all people.\", \"id\": \"polusa_v1_55397390_-1_60_Dr. Cynthia Hale, Pastor of Ray of Hope Christian Church in DeKalb County, Georgia_42_45\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 13, \"to\": 15, \"sentence\": \"\\\"I know that he's a guy that fights for the underdog, always has,\\\" Meadows said.\", \"id\": \"polusa_v1_55401947_-1_24_Jim Jordan_14_16\"}\n{\"mention\": \"\\\" Meadows\", \"polarity\": 0, \"from\": 65, \"to\": 74, \"sentence\": \"\\\"I know that he's a guy that fights for the underdog, always has,\\\" Meadows said.\", \"id\": \"polusa_v1_55401947_-1_24_\\\" Meadows_66_75\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 129, \"to\": 131, \"sentence\": \"Social media observers highlighted Sandmann's reaction to Phillips — a grin many took to be contemptuous — as lead evidence that he and his classmates were mocking Phillips.\", \"id\": \"polusa_v1_55405572_-1_11_he_130_132\"}\n{\"mention\": \"Cook\", \"polarity\": 0, \"from\": 198, \"to\": 202, \"sentence\": \"“While it was disappointing to miss our revenue guidance, we manage Apple for the long term, and this quarter’s results demonstrate that the underlying strength of our business runs deep and wide,” Cook said in a press release.\", \"id\": 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School graduate Charlie Zielinski_293_296\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 27, \"to\": 39, \"sentence\": \"I can’t necessarily affect Donald Trump.”\", \"id\": \"polusa_v1_59512115_-1_20_“Donald Trump_27_39\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": -1, \"from\": 120, \"to\": 129, \"sentence\": \"But McConnell and some others were especially incensed by a second allegation in which a student who attended Yale with Kavanaugh said he exposed himself at a drunken dormitory party, thrust his penis in her face and caused her to touch it without her consent as she pushed him away.\", \"id\": \"polusa_v1_59513735_-1_16_Kavanaugh_120_129\"}\n{\"mention\": \"Jabari Feazell\", \"polarity\": 0, \"from\": 90, \"to\": 104, \"sentence\": \"Cook County Sheriffs Office Edward D. Waits, 25, was charged in the August 2017 murder of Jabari Feazell.\", \"id\": \"polusa_v1_59514812_-1_6_20-year-old Jabari Feazell_91_105\"}\n{\"mention\": \"McGovern\", \"polarity\": 1, \"from\": 4, \"to\": 12, \"sentence\": \"And McGovern coordinated congressional campaigns for Mark Kirk and Bob Dold on the North Shore, as well as Kirk’s 2010 Senate victory.\", \"id\": \"polusa_v1_59515193_-1_8_John McGovern_4_12\"}\n{\"mention\": \"Quigley\", \"polarity\": 1, \"from\": 76, \"to\": 83, \"sentence\": \"This term, while exploring Russian interference in the 2016 election cycle, Quigley pushed to secure $380 million in assistance grants to help states protect their election systems from hacking.\", \"id\": \"polusa_v1_59515694_-1_26_Mike Quigley of Chicago_77_84\"}\n{\"mention\": \"Randy Hultgren\", \"polarity\": 1, \"from\": 0, \"to\": 14, \"sentence\": \"Randy Hultgren of Plano: a solid conservative who defeated his Democratic opponent by more than 18 percentage points in the 2016 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Cohan_65_70\"}\n{\"mention\": \"Johnson\", \"polarity\": 1, \"from\": 24, \"to\": 31, \"sentence\": \"Many signature items of Johnson’s legacy—from civil and voting rights to environmental protections and aid to public schools—are today under assault.\", \"id\": \"polusa_v1_79083139_-1_9_Johnson_24_31\"}\n{\"mention\": \"Ivanka Trump\", \"polarity\": -1, \"from\": 100, \"to\": 112, \"sentence\": \"| Win McNamee/Getty Images Before Ivanka's Oprah tweet, Trumps' harassment comments raised eyebrows\\nIvanka Trump acknowledged the viral #MeToo movement in a tweet Monday, but President Donald Trump's family members drew raised eyebrows in the past with their comments about sexual harassment in the workplace.\", \"id\": \"polusa_v1_79083545_-1_4_Ivanka Trump's_100_112\"}\n{\"mention\": \"Tillis\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Tillis still professes hope for tax reform, and for health care, and for comprehensive immigration reform.\", \"id\": 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\"polusa_v1_79084821_-1_1_Melanie Zanona_262_276\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 80, \"to\": 82, \"sentence\": \"That wall was “13,000 miles, folks, and they didn’t have Caterpillar tractors,” he said in a Super Tuesday speech in 2016.\", \"id\": \"polusa_v1_79084846_-1_50_President Donald Trump_80_82\"}\n{\"mention\": \"Manafort\", \"polarity\": -1, \"from\": 31, \"to\": 39, \"sentence\": \"An aggressive claim of bias by Manafort is unlikely to derail the prosecution that now threaten him with the prospect of spending the rest of his life behind bars.\", \"id\": \"polusa_v1_79084850_-1_14_Paul Manafort_32_40\"}\n{\"mention\": \"Manafort\", \"polarity\": -1, \"from\": 31, \"to\": 39, \"sentence\": \"An aggressive claim of bias by Manafort is unlikely to derail the prosecution that now threaten him with the prospect of spending the rest of his life behind bars.\", \"id\": \"polusa_v1_79084850_-1_14_Manafort_32_40\"}\n{\"mention\": \"NHTSA Deputy Administrator Heidi King\", \"polarity\": 0, \"from\": 108, \"to\": 145, \"sentence\": \"King takes the hot seat\\nWith help from Lauren Gardner, Brianna Gurciullo and Tanya Snyder\\nKING ON THE HILL: NHTSA Deputy Administrator Heidi King will be in the hot seat today as the Senate Commerce Committee considers her nomination for administrator, a position vacant since President Donald Trump’s inauguration.\", \"id\": \"polusa_v1_79084943_-1_2_NHTSA Deputy Administrator Heidi King_110_147\"}\n{\"mention\": \"Stephen Miller\", \"polarity\": -1, \"from\": 19, \"to\": 33, \"sentence\": \"Graham tees off on Stephen Miller over immigration\", \"id\": \"polusa_v1_79085332_-1_0_Stephen Miller_19_33\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 80, \"to\": 102, \"sentence\": \"| Getty Trump: Blumenthal lied about Vietnam, 'misrepresents' what Gorsuch said\\nPresident Donald Trump attacked the military record of Sen.\", \"id\": \"polusa_v1_79085363_-1_7_Trump_80_102\"}\n{\"mention\": \"Blumenthal\", \"polarity\": -1, \"from\": 15, \"to\": 25, \"sentence\": \"| Getty Trump: Blumenthal lied about Vietnam, 'misrepresents' what Gorsuch said\\nPresident Donald Trump attacked the military record of Sen.\", \"id\": \"polusa_v1_79085363_-1_7_Chris Cuomo_15_25\"}\n{\"mention\": \"The FRA\", \"polarity\": 1, \"from\": 18, \"to\": 25, \"sentence\": \"Rail\\nMONEY TRAIN: The FRA is offering more than $244 million in grant funding for capital rail projects under its Consolidated Rail Infrastructure and Safety Improvements program, the agency announced Wednesday.\", \"id\": \"polusa_v1_79085845_-1_25_The FRA_19_26\"}\n{\"mention\": \"Wednesday\", \"polarity\": 0, \"from\": 201, \"to\": 210, \"sentence\": \"Rail\\nMONEY TRAIN: The FRA is offering more than $244 million in grant funding for capital rail projects under its Consolidated Rail Infrastructure and Safety Improvements program, the agency announced Wednesday.\", \"id\": 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top diplomats are even in place How Trump created chaos at the airport with his unfair and inhumane order\", \"id\": \"allsides_1381_555_19_Eric Garcetti_131_144\"}\n{\"mention\": \"Lara\", \"polarity\": -1, \"from\": 47, \"to\": 51, \"sentence\": \"Trump’s daughter-in-law pushes his propaganda: Lara Trump launches “real news” show to praise the president\", \"id\": \"allsides_756_306_0_Lara Trump’s_47_51\"}\n{\"mention\": \"Reid\", \"polarity\": 0, \"from\": 6, \"to\": 10, \"sentence\": \"Harry Reid of Nevada and Michael Bennet of Colorado for the filibuster.\", \"id\": \"allsides_3465_1429_40_Reid_6_10\"}\n{\"mention\": \"Ms Donaldson\", \"polarity\": -1, \"from\": 94, \"to\": 106, \"sentence\": \"Image copyright PA Image caption Dr Neil Murray said he was \\\"really taken\\\" by how good a liar Ms Donaldson was.\", \"id\": \"polusa_v1_18308740_-1_11_Amanda Donaldson_95_107\"}\n{\"mention\": \"Macias\", \"polarity\": 0, \"from\": 22, \"to\": 28, \"sentence\": \"Talking to the media, 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Slager would face a murder penalty, members of Scott’s family addressed the court.\", \"id\": \"allsides_223_91_6_Michael Slager at a court hearing in 2016.Grace Beahm/AP A federal judge_27_33\"}\n{\"mention\": \"Adamu\", \"polarity\": 0, \"from\": 106, \"to\": 111, \"sentence\": \"Image copyright Situation RoomVerified account Image example New Police Acting Inspector General Abubakar Adamu dey resume work for Force Heaquarters as e take over from former IGP Ibrahim Idris\\n2019 general elections go be di biggest challenge for di new oga of Nigeria Police wey just start work as Acting Inspector General of Police.\", \"id\": \"polusa_v1_18117875_-1_2_Mohammed Adamu_108_113\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 86, \"to\": 89, \"sentence\": \"More from CBS: In the case of Amber Vinson, the Dallas nurse who flew commercially as she was becoming ill with Ebola, one health official said \\\"somebody dropped the ball.\\\"\", \"id\": \"allsides_4040_1678_8_Vinson_86_89\"}\n{\"mention\": \"Ryan\", \"polarity\": 0, \"from\": 151, \"to\": 155, \"sentence\": \"Mark Walker has \\\"stepped down\\\" from search committee to select new House chaplain\\nAsked if the move was something he'd been considering for some time, Ryan said, \\\"It's based upon feedback I've been getting for quite a while from members.\\\"\", \"id\": \"polusa_v1_4159893_-1_14_House Speaker Paul Ryan_151_155\"}\n{\"mention\": \"Earnest\", \"polarity\": 0, \"from\": 45, \"to\": 52, \"sentence\": \"It was that Pierson offered her resignation, Earnest said—as if these things happen in a vacuum.\", \"id\": \"allsides_4090_1699_11_White House spokesman Josh Earnest_45_52\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 15, \"to\": 20, \"sentence\": \"In addition of Obama and McDonough’s efforts, a U.S. official on Saturday released a DVD compilation of videos showing attack victims that the official said were shown to senators during Thursday's classified briefing.\", \"id\": \"allsides_5071_2140_33_President Obama_15_20\"}\n{\"mention\": \"Kelly\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Kelly said at least one Tsarnaev brother was photographed in Times Square last year, first on April 18 and then later on an unspecified day in November.\", \"id\": \"allsides_5469_2332_15_Police Commissioner Ray Kelly_0_5\"}\n{\"mention\": \"Bannon\", \"polarity\": 1, \"from\": 30, \"to\": 36, \"sentence\": \"When he left the White House, Bannon said he would work to help Trump and wage a populist campaign from the outside.\", \"id\": \"allsides_85_34_21_Steve Bannon_30_36\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 64, \"to\": 69, \"sentence\": \"When he left the White House, Bannon said he would work to help Trump and wage a populist campaign from the outside.\", \"id\": \"allsides_85_34_21_TRUMP_64_69\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"President Trump has made these choices recently that have led to the resignation of his secretary of defense and the head of the team that's charged with countering ISIS.\", \"id\": \"polusa_v1_52938649_-1_31_President Trump_0_15\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": 0, \"from\": 0, \"to\": 22, \"sentence\": \"President Donald Trump commented on rumors that his administration is looking into purchasing Greenland while speaking to reporters, outside of Marine One on Sunday.\", \"id\": \"polusa_v1_4399542_-1_1_President Donald Trump_0_24\"}\n{\"mention\": \"President Obama\", \"polarity\": 1, \"from\": 3, \"to\": 18, \"sentence\": \"So President Obama had to step into vacuum of national civil rights leadership and appeal for peace on the streets all the way from the White House.\", \"id\": \"allsides_3885_1610_26_President Obama_3_18\"}\n{\"mention\": \"His\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"His official cause of death was listed as basal bilateral 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\"sentence\": \"Obama mused that perhaps the United States was not ready for his modern presidency,\\n“Sometimes I wonder whether I was 10 or 20 years too early,” he said to his aides, who reassured him that he could have won a third term as president.\", \"id\": \"polusa_v1_4357806_-1_9_Former President Barack Obama_1_6\"}\n{\"mention\": \"Eugene\", \"polarity\": 1, \"from\": 17, \"to\": 23, \"sentence\": \"Graham’s father, Eugene Meyer, had bought the paper out of bankruptcy in 1933, and found his successor in Phil Graham, whom Kay married in 1940.\", \"id\": \"polusa_v1_79072037_-1_19_Eugene_17_23\"}\n{\"mention\": \"Graham\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Graham’s father, Eugene Meyer, had bought the paper out of bankruptcy in 1933, and found his successor in Phil Graham, whom Kay married in 1940.\", \"id\": \"polusa_v1_79072037_-1_19_Katharine Graham_0_6\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 4, \"to\": 11, \"sentence\": \"The Clinton campaign has tried to tamp down the controversy since it emerged this week in previews of the book “Clinton Cash: The Untold Story of How and Why Foreign Governments and Businesses Helped Make Bill and Hillary Rich.”\", \"id\": \"allsides_3315_1366_23_Clinton_4_11\"}\n{\"mention\": \"Luisa Ortega\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Luisa Ortega arrived in Colombia on Friday with her husband German Ferrer after Venezuelan authorities ordered his arrest for allegedly running an extortion ring out of the prosecutor's office.\", \"id\": \"polusa_v1_4641689_-1_3_Luisa Ortega_0_13\"}\n{\"mention\": \"Davis\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Davis said about 10 first responders from the police, fire and medical response departments were also taken to the hospital as a precautionary measure, but none had shown symptoms of illness.\", \"id\": \"polusa_v1_4386725_-1_12_Larry Davis_0_6\"}\n{\"mention\": \"Priebus\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Priebus, is a Washington veteran with deep ties to Republican leadership, particularly House Speaker Paul Ryan, The Associated Press reports.\", \"id\": \"allsides_1643_664_5_Republican National Committee chairman Reince Priebus his new chief of staff_0_7\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He was supported by Deputy Solicitor Gen. 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Kennedy_1_3\"}\n{\"mention\": \"Walsh\", \"polarity\": -1, \"from\": 105, \"to\": 110, \"sentence\": \"The charges of conspiracy, misconduct and obstruction of justice boil down to the accusation that March, Walsh and Gaffney falsified their reports about the October 2014 shooting and didn't interview witnesses who could have provided accounts they didn't want to record.\", \"id\": \"polusa_v1_115844517_-1_10_Joseph Walsh_106_111\"}\n{\"mention\": \"Amash\", \"polarity\": -1, \"from\": 16, \"to\": 21, \"sentence\": \"When Trump won, Amash remained hostile even as the president led on issues the two men had in common, such as tax cuts and criminal justice reform.\", \"id\": \"polusa_v1_4294478_-1_22_Amash_16_21\"}\n{\"mention\": \"Ms. Lynch\", \"polarity\": 1, \"from\": 79, \"to\": 88, \"sentence\": \"As we move forward with the confirmation process, I have every confidence that Ms. Lynch will receive a very fair, but thorough, vetting by the Judiciary Committee,” he said in a statement.“I look forward to learning more about her, how she will interact with Congress, and how she proposes to lead the department.”\", \"id\": \"allsides_3940_1637_32_\\\"Ms. Lynch_79_88\"}\n{\"mention\": \"Priebus\", \"polarity\": 1, \"from\": 12, \"to\": 19, \"sentence\": \"\\\"Bannon and Priebus will continue the effective leadership team they formed during the campaign, working as equal partners to transform the federal government, making it much more efficient, effective and productive,\\\" it said.\", \"id\": \"allsides_1643_664_14_Republican National Committee chairman Reince Priebus his new chief of staff_12_19\"}\n{\"mention\": \"Ginsburg\", \"polarity\": 0, \"from\": 29, \"to\": 37, \"sentence\": \"A February 6 event featuring Ginsburg and private equity titan and philanthropist David Rubenstein in New York City was also canceled.\", \"id\": \"polusa_v1_4300546_-1_4_Ruth Bader Ginsburg_29_37\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He also has a financial past that ranges from misguided to high-flying depending on who is doing the describing.\", \"id\": \"allsides_3137_1287_11_Marco Rubio_0_2\"}\n{\"mention\": \"Mr. Obama and Mr. Cameron\", \"polarity\": 1, \"from\": 0, \"to\": 25, \"sentence\": \"Mr. Obama and Mr. Cameron argued that NATO must transition to a “more effective security network that fosters stability around the world,” urging member nations to bolster military spending.\", \"id\": \"allsides_4186_1744_15_Mr. Obama and Mr. Cameron_0_25\"}\n{\"mention\": \"Joe Biden\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Joe Biden really wants to run for president\", \"id\": \"allsides_4585_1919_0_Joe Biden_0_9\"}\n{\"mention\": \"Rauner\", \"polarity\": 1, \"from\": 6, \"to\": 12, \"sentence\": \"Later Rauner said he preferred raising the national minimum (because raising the state minimum might give an advantage to neighboring states with lower minimums) but that he would support raising the state minimum if certain conditions were met.\", \"id\": \"allsides_3993_1659_26_Rauner_6_12\"}\n{\"mention\": \"Osama Bin Laden\", \"polarity\": -1, \"from\": 113, \"to\": 128, \"sentence\": \"On Monday morning, however, Trump doubled down on his remarks, tweeting that, \\\"Of course we should have captured Osama Bin Laden long before we did.\\\"\", \"id\": \"polusa_v1_55355520_-1_26_Osama Bin Laden_114_129\"}\n{\"mention\": \"Simpson\", \"polarity\": -1, \"from\": 9, \"to\": 16, \"sentence\": \"In 2010, Simpson was arrested one day before he was scheduled to fly to South Africa to undertake what he claimed were religious studies at a madrassa.\", \"id\": \"allsides_3275_1348_21_Elton Simpson_9_16\"}\n{\"mention\": \"Flynn\", \"polarity\": 0, \"from\": 18, \"to\": 23, \"sentence\": \"Around this time, Flynn spoke with Kislyak and urged him not to retaliate.\\n... while it's not clear what Sessions talked about\\nSessions spokeswoman Sarah Isgur Flores said that the then-senator met with Kislyak because of his position on the Senate Armed Services Committee.\", \"id\": \"polusa_v1_4255128_-1_12_Michael Flynn_18_23\"}\n{\"mention\": \"Nancy Pelosi\", \"polarity\": -1, \"from\": 10, \"to\": 22, \"sentence\": \"SEE ALSO: Nancy Pelosi sounds pessimistic note about Dems’ chances to take House The Secret Service is reeling from a new scandal after an intruder last month jumped the White House fence and made it into the executive mansion before he was apprehended.\", \"id\": \"allsides_4091_1700_7_Minority Leader Nancy Pelosi_10_22\"}\n{\"mention\": \"Riehl\", \"polarity\": -1, \"from\": 15, \"to\": 20, \"sentence\": \"At this point, Riehl is aware he has shot Deputy Parrish.\", \"id\": \"polusa_v1_113842673_-1_29_Matthew Riehl_16_21\"}\n{\"mention\": \"Deputy Parrish\", \"polarity\": 0, \"from\": 42, \"to\": 56, \"sentence\": \"At this point, Riehl is aware he has shot Deputy Parrish.\", \"id\": \"polusa_v1_113842673_-1_29_Deputy Parrish_43_57\"}\n{\"mention\": \"Lewandowski\", \"polarity\": -1, \"from\": 48, \"to\": 59, \"sentence\": \"Despite the appearance of a small incident, the Lewandowski case had big ramifications.\", \"id\": \"allsides_2314_941_17_Corey Lewandowski_48_59\"}\n{\"mention\": \"David Sorensen\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"David Sorensen denies his former wife's allegations he was violent and emotionally abusive.\", \"id\": \"polusa_v1_18565276_-1_3_David Sorensen_1_15\"}\n{\"mention\": \"Gianforte\", \"polarity\": 0, \"from\": 29, \"to\": 38, \"sentence\": \"But it’s being denied by the Gianforte campaign.\", \"id\": \"allsides_1052_420_7_Gianforte_29_38\"}\n{\"mention\": \"Josh Miller\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"Josh Miller has led an unsuccessful effort to legalize pot for the last four years.\", \"id\": \"polusa_v1_55169103_-1_30_Josh Miller_0_11\"}\n{\"mention\": \"Wynn\", \"polarity\": -1, \"from\": 41, \"to\": 45, \"sentence\": \"The RNC has been silent on the matter of Wynn’s donations since the WSJ report was published ― opening itself to charges of hypocrisy given that the party called on Democrats to return money that Harvey Weinstein donated to their campaigns over his years of activity in fundraising circles.\", \"id\": \"polusa_v1_3926717_-1_8_casino mogul Steve Wynn_42_46\"}\n{\"mention\": \"Tom Clancy’s\", \"polarity\": 0, \"from\": 124, \"to\": 136, \"sentence\": \"SIGN UP FOR OUR NEWSLETTER\\nTake on the Santa Blanca Cartel as elite special forces operators in the Wildlands of Bolivia in Tom Clancy’s Ghost Recon Wildlands.\", \"id\": \"polusa_v1_4287432_-1_2_Tom Clancy’s_126_138\"}\n{\"mention\": \"Kemp\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Kemp \\\"ran a great race in Georgia – he won,\\\" Trump wrote \\\"It is time to move on!\\\"\", \"id\": \"polusa_v1_4180752_-1_19_Brian Kemp_1_5\"}\n{\"mention\": \"Ms. Mikulski\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Ms. Mikulski was devoted to increasing the number of female Democrats in Congress, and maintaining an informal working group of women from both parties in the Senate, a rarefied group.\", \"id\": \"allsides_3525_1455_28_Ms. Mikulski_0_12\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 133, \"to\": 138, \"sentence\": \"#CNNSOTU https://t.co/apNFwVdKQZ pic.twitter.com/93OYgFCgl5 — State of the Union (@CNNSotu) January 13, 2019\\nJohnson speculated that Trump felt “burned earlier by leaks of other private conversations” between him and other world leaders, prompting his effort to keep interactions with Putin from members of his own administration.\", \"id\": \"polusa_v1_3975517_-1_15_President Donald Trump_133_138\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 31, \"to\": 34, \"sentence\": \"In particular, they pointed to his controversial decision to publicly announce the reopening of that inquiry shortly before election day in November.\", \"id\": 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\"allsides_261_106_1_U.S. Secretary of State Rex Tillerson_0_40\"}\n{\"mention\": \"House Speaker John Boehner (R-Ohio)\", \"polarity\": -1, \"from\": 29, \"to\": 64, \"sentence\": \"— President Barack Obama and House Speaker John Boehner (R-Ohio) finished another week without a fiscal cliff deal, not even agreeing on how the negotiations are going.\", \"id\": \"allsides_5978_2563_2_House Speaker John Boehner (R-Ohio)_29_64\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 117, \"to\": 122, \"sentence\": \"Seen in the Oval Office for a final time just before Trump swore in his Treasury Secretary Steven Mnuchin at 8 p.m., Flynn handed over his resignation letter to Trump shortly after the President requested he step down.\", \"id\": \"polusa_v1_4982381_-1_30_Michael Flynn_117_122\"}\n{\"mention\": \"#Piegate\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"#Piegate declared over as Sanders bakes a 'real' winner\", \"id\": 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reinstate Trump's ban.\", \"id\": \"allsides_1385_557_49_President Trump_69_74\"}\n{\"mention\": \"Benjamin Netanyahu\", \"polarity\": -1, \"from\": 9, \"to\": 27, \"sentence\": \"Israel’s Benjamin Netanyahu faces corruption indictments\", \"id\": \"polusa_v1_55055245_-1_0_Benjamin Netanyahu_9_27\"}\n{\"mention\": \"Harry\", \"polarity\": 0, \"from\": 27, \"to\": 32, \"sentence\": \"“I don’t know about that,” Harry said.\", \"id\": \"allsides_149_62_14_Harry_27_32\"}\n{\"mention\": \"Mr. Trump “\", \"polarity\": -1, \"from\": 46, \"to\": 57, \"sentence\": \"Representative Barbara Lee of California said Mr. Trump “has demeaned and insulted the African-American community, and we are going to have to really raise our voices and resist this if these views are going to be reflected in his policies.”\", \"id\": \"allsides_1445_583_30_Mr. Trump “_46_57\"}\n{\"mention\": \"Condoleezza Rice's\", \"polarity\": 1, \"from\": 61, \"to\": 79, \"sentence\": \"Graham and his allies denounced this 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55, \"to\": 57, \"sentence\": \"“Up at Camp David, we do skeet shooting all the time,” he told The New Republic in the interview, conducted Jan. 16, just after he unveiled his gun proposals.\", \"id\": \"allsides_5795_2482_4_Obama_55_57\"}\n{\"mention\": \"Holly Williams\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Holly Williams: Has America already ceded leadership in this industry--\\nMichael Dunne: No.\", \"id\": \"polusa_v1_113885769_-1_156_Holly Williams_0_15\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 1, \"from\": 40, \"to\": 49, \"sentence\": \"Surveys from Quinnipiac University show Mr. Trump more than doubling up Senator Marco Rubio of Florida in his home state.\", \"id\": \"allsides_2410_977_2_Donald J. 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Luis Alberto Rodríguez López-Callejas, Raul Castro's son-in-law.\", \"id\": \"polusa_v1_4699437_-1_46_Trump_0_11\"}\n{\"mention\": \"his\", \"polarity\": 0, \"from\": 46, \"to\": 49, \"sentence\": \"The opinions expressed in this commentary are his.\", \"id\": \"polusa_v1_4758038_-1_4_President Trump_46_49\"}\n{\"mention\": \"Robert Durst\", \"polarity\": -1, \"from\": 1, \"to\": 13, \"sentence\": \"“Robert Durst, Subject of HBO Documentary on Unsolved Killings, Is Arrested” (via @nytimes): http://t.co/0QIgyXtRai #TheJinx — HBO (@HBO) March 15, 2015 Catch up on the series everyone is talking about before the shocking finale.\", \"id\": \"allsides_3471_1432_77_Robert Durst_1_13\"}\n{\"mention\": \"Mnangagwa\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mnangagwa first took office in November after Mugabe resigned under military pressure, and narrowly won a July 30 election that the opposition alleged was rigged.\", \"id\": \"polusa_v1_4430084_-1_8_President Emmerson Mnangagwa_0_10\"}\n{\"mention\": \"Mugabe\", \"polarity\": -1, \"from\": 46, \"to\": 52, \"sentence\": \"Mnangagwa first took office in November after Mugabe resigned under military pressure, and narrowly won a July 30 election that the opposition alleged was rigged.\", \"id\": \"polusa_v1_4430084_-1_8_Robert Mugabe's_47_53\"}\n{\"mention\": \"Conway\", \"polarity\": 0, \"from\": 32, \"to\": 38, \"sentence\": \"White House counselor Kellyanne Conway’s husband took to the president’s favored social media platform to make the argument that the San Francisco-based court sees so many cases overturned because of the sheer volume of cases they oversee.\", \"id\": \"polusa_v1_4284566_-1_3_Attorney George Conway_33_39\"}\n{\"mention\": \"the president\", \"polarity\": 0, \"from\": 50, \"to\": 63, \"sentence\": \"I don't think it is more dangerous than alcohol,\\\" the president said.\", \"id\": \"allsides_4650_1948_3_President Obama_50_63\"}\n{\"mention\": \"Loa-Nunez\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Loa-Nunez posted a $250 cash bond on May 10 and then disappeared, according to reports.\", \"id\": \"polusa_v1_4304820_-1_16_Juana Loa-Nunez_0_10\"}\n{\"mention\": \"Todd Akin's\", \"polarity\": -1, \"from\": 71, \"to\": 82, \"sentence\": \"Romney released a statement late Tuesday saying: \\\"As I said yesterday, Todd Akin's comments were offensive and wrong and he should very seriously consider what course would be in the best interest of our country.\", \"id\": \"allsides_6341_2728_27_Akin_71_82\"}\n{\"mention\": \"Dolan\", \"polarity\": 0, \"from\": 9, \"to\": 14, \"sentence\": \"Cardinal Dolan Battles Andrew Cuomo over Abortion Law\", \"id\": \"polusa_v1_4325162_-1_0_New York Cardinal Timothy Dolan_9_14\"}\n{\"mention\": \"Baron\", \"polarity\": 1, \"from\": 4, \"to\": 9, \"sentence\": \"But Baron got a prize of his own in the Post.\", \"id\": \"polusa_v1_79087698_-1_91_Baron_4_9\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 13, \"to\": 35, \"sentence\": \"On Thursday, President Donald Trump blocked the release of hundreds of records on the 1963 assassination of President John F. 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\"sentence\": \"The truth is that we would probably have never heard Vikki’s story if she hadn’t died in prison, but Britain is full of Vikki Thompsons – thousands of young trans people up and down the country missing out on fulfilling their potential because of prejudice, ignorance and discrimination.\", \"id\": \"polusa_v1_38938696_-1_36_Vikki_54_59\"}\n{\"mention\": \"Raja Pervez Ashraf\", \"polarity\": 0, \"from\": 444, \"to\": 462, \"sentence\": \"__Aug. 18 2008: Musharraf resigns from his post as president under pressure;\\n__Sept. 6, 2008: Bhutto's husband Asif Ali Zardari becomes president;\\n__May 2, 2011: Osama bin Laden is killed in a U.S. Navy SEALs raid in the army garrison town of Abbottabad;\\n__June 19, 2012: Supreme Court disqualifies Gilani as prime minister for not complying with a court order to request a Swiss court reopen corruption cases against Zardari;\\n__June 22, 2012: Raja Pervez Ashraf becomes prime minister, completes his term on March 16, 2013;\\n__May 11, 2013: Sharif's party, the Pakistan Muslim League, overwhelmingly wins in general elections, he becomes prime minister for third time;\\n__ July 28, 2017: Sharif is disqualified from office by the Supreme Court on corruption charges stemming from so-called leaked Panama papers;\\n__Aug. 1, 2017 Sharif's confidant Shahid Khaqan Abbasi is sworn in as prime minister;\\n__May 31: Abbasi's government completes its term in office and elections are scheduled for July 25;\\n__July 6: Anti-graft tribunal convicts Sharif in absentia and sentences him to 10 years in prison, his daughter and son in-law are sentenced to lesser term;\\n__July 13: Sharif returns home from London where his ailing wife is in hospital; he and his daughter are arrested after landing and taken to a jail in Rawalpindi;\\n__July 25: Voting takes place for Pakistan's third straight civilian government.\", \"id\": \"polusa_v1_4537616_-1_6_Raja Pervez Ashraf_445_463\"}\n{\"mention\": \"Emanuel\", \"polarity\": -1, \"from\": 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\"id\": \"allsides_5889_2525_27_Mr. Boehner_0_2\"}\n{\"mention\": \"Irma\", \"polarity\": 0, \"from\": 63, \"to\": 67, \"sentence\": \"The agency is just beginning to sort through claims related to Irma, and doesn't have a dollar figure for Irma flood payouts yet.\", \"id\": \"polusa_v1_116916665_-1_16_Harvey_63_67\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He then added: “I’m an African-American.\", \"id\": \"allsides_1783_726_7_Cam Newton_0_2\"}\n{\"mention\": \"The president\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"The president has no further comment.\\\"\", \"id\": \"allsides_1164_465_8_President Trump_0_13\"}\n{\"mention\": \"Duncan\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Duncan, who arrived in the U.S. from Liberia Sept. 20, first sought medical care for fever and abdominal pain Sept. 25.\", \"id\": \"allsides_4051_1683_13_Duncan_0_6\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 30, 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\"After meetings with gun-safety and victims groups Wednesday, the vice president said he is \\\"determined\\\" to take \\\"urgent action\\\" to address gun violence.\", \"id\": \"allsides_5849_2506_3_Biden_85_87\"}\n{\"mention\": \"Aranda\", \"polarity\": -1, \"from\": 34, \"to\": 40, \"sentence\": \"Police said the suspect, Emmanuel Aranda, told them he went to the mall \\\"looking for someone to kill\\\" and chose the boy at random.\", \"id\": \"polusa_v1_113897170_-1_3_Aranda_34_40\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said he didn’t know if any friends or colleagues had received similar messages, but is hoping that law enforcement officials can track down the sender.\", \"id\": \"polusa_v1_3953594_-1_33_Gilliard_1_3\"}\n{\"mention\": \"him\", \"polarity\": 0, \"from\": 29, \"to\": 32, \"sentence\": \"Wikileaks started contacting him in late September of 2016.\", \"id\": \"allsides_326_131_16_Jr._29_32\"}\n{\"mention\": \"he\", 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  },
  {
    "path": "NewsSentiment/experiments/default/datasets/newsmtsc-rw/dev.jsonl",
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Martin, Jr., Morrison Professor of American History and Citizenship Robin Einhorn, Preston Hotchkis Professor in the History of the United States Kristin Hanson, Associate Professor, English Patricia Baquedano-Lopez, Associate Professor of Education Joseph Wolf, Professor Emeritus, Mathematics You-tien Hsing, Professor, Geography Glynda Hull, Professor, Education Richard B. Norgaard, Professor Emeritus of Energy and Resources Ellen L. Simms, Professor of Integrative Biology Katherine Snyder, Associate Professor, Department of English Kathleen Donegan, Associate Professor, Department of English and Associate Dean of Arts and Humanities Trinh T. Minh-ha, Professor of Rhetoric and of Gender & Women’s Studies Suzanne Guerlac, Professor, Department of French Mel Y. Chen, Associate Professor, Department of Gender and Women’s Studies Margaret W. Conkey, Department of Anthropology Darcy Grimaldo Grigsby, Professor, History of Art Mariane C Ferme, Professor, Department of Anthropology Lyn Hejinian, John F Hotchkis Professor of English Michael Watts, Professor Emeritus, Geography Antonio Montalban, Associate Professor, Mathematics Samera Esmeir, Associate Professor, Rhetoric Louise Fortmann, Professor Emerita, Dept of Environmental Science, Policy and Management Joseph Lavery, Assistant Professor, Dept. of English Lynn Huntsinger, Professor, Dept Environmental Science, Policy, and Management Ramona Naddaff, Associate Professor, Rhetoric Daniel Boyarin, Taubman Professor of Talmudic Culture, Near Eastern Studies and Rhetoric Gillian Hart, Professor Emerita, Geography Charles C. 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Blair_1_3\"}\n{\"mention\": \"Miller\", \"polarity\": 0, \"from\": 148, \"to\": 154, \"sentence\": \"\\\"As far as the truck rental goes, those interviews are being conducted and ... there was certainly nothing unusual enough to cause anyone to call,\\\" Miller said.\", \"id\": \"polusa_v1_4678416_-1_30_John Miller_149_155\"}\n{\"mention\": \"Priebus\", \"polarity\": -1, \"from\": 31, \"to\": 38, \"sentence\": \"Then Trump didn’t actually let Priebus be a real chief of staff So Priebus ended up being given the “buck stops here” job of chief of staff, but lacked the stature or experience to actually perform well in it.\", \"id\": \"allsides_775_313_30_Reince Priebus_31_38\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 5, \"to\": 10, \"sentence\": \"Then Trump didn’t actually let Priebus be a real chief of staff So Priebus ended up being given the “buck stops here” job of chief of staff, but lacked the stature or experience to actually perform well in it.\", \"id\": \"allsides_775_313_30_President Donald Trump_5_10\"}\n{\"mention\": \"The boy\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"The boy will appear in court in mid July to appeal his deportation.\", \"id\": \"polusa_v1_39106708_-1_20_Peters_1_8\"}\n{\"mention\": \"\\\" Mann\", \"polarity\": 0, \"from\": 118, \"to\": 124, \"sentence\": \"\\\"We learn about Columbus landing in 1492 and it’s as if nothing happened for over 100 years until the Pilgrims landed,\\\" Mann added.\", \"id\": \"allsides_2730_1110_62_Mann_118_124\"}\n{\"mention\": \"Johnson\", \"polarity\": 0, \"from\": 19, \"to\": 26, \"sentence\": \"The statement says Johnson is expected to meet with Vice President Mike Pence, national security adviser John Bolton and other senior administration officials as well as congressional foreign policy leaders.\", \"id\": \"polusa_v1_4536416_-1_7_Johnson_20_27\"}\n{\"mention\": \"Handel\", \"polarity\": 0, \"from\": 50, \"to\": 56, \"sentence\": \"CNN declared the race a runoff between Ossoff and Handel shortly after midnight.\", \"id\": \"polusa_v1_4293344_-1_5_the GOP’s Karen Handel_51_57\"}\n{\"mention\": \"Ossoff\", \"polarity\": 0, \"from\": 39, \"to\": 45, \"sentence\": \"CNN declared the race a runoff between Ossoff and Handel shortly after midnight.\", \"id\": \"polusa_v1_4293344_-1_5_thirty-year-old Democratic candidate Jon Ossoff_40_46\"}\n{\"mention\": \"Stockton\", \"polarity\": 0, \"from\": 33, \"to\": 41, \"sentence\": \"An online search for churches in Stockton did not find the Tabernacle, the church said.\", \"id\": \"polusa_v1_18552887_-1_1_Stockton_35_43\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Obama task force urges overhaul of NSA spy tactics, keeps NSA director and chief cyber commander job as one\", \"id\": \"allsides_4757_2000_0_Obama_0_5\"}\n{\"mention\": \"MORGAN\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"MORGAN: Yes, we- we've been--\\nMARGARET BRENNAN: Okay.\", \"id\": \"polusa_v1_113906558_-1_81_MORGAN: So what- what I would say is facts matter all the way around_1_7\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He noted that trains were the mode of transportation that first carried Bush to his service as a naval aviator in World War II and back home again.\", \"id\": \"polusa_v1_116023500_-1_26_company spokesman Tom Lange_0_2\"}\n{\"mention\": \"Assad\", \"polarity\": -1, \"from\": 67, \"to\": 72, \"sentence\": \"The Obama administration has attempted to steer clear of attacking Assad’s regime because they argue it could embroil the U.S. in direct conflict with Russia and Iran.\", \"id\": \"allsides_2078_846_11_Assad_67_72\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He asked Trump to call on Republicans to repeal Obamacare in early July if they cannot reach an agreement on a comprehensive plan by then.\", \"id\": \"allsides_889_358_6_Ben Sasse (R-NE)_0_2\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 29, \"to\": 31, \"sentence\": \"For the second day in a row, he accused groups like the Club for Growth, Heritage Action and Americans for Prosperity of reflexively opposing a reasonable plan to try to raise their profiles and improve their fund-raising.\", \"id\": \"allsides_4761_2001_10_Speaker John A. Boehner of Ohio_29_31\"}\n{\"mention\": \"Schiff\", \"polarity\": -1, \"from\": 60, \"to\": 66, \"sentence\": \"At an explosive rally in Michigan on Thursday, Trump mocked Schiff as having the \\\"smallest, thinnest neck I've ever seen,\\\" and someone who is \\\"not a long-ball hitter.\\\"\", \"id\": \"polusa_v1_4544269_-1_13_Schiff_61_67\"}\n{\"mention\": \"Vanitzian\", \"polarity\": 0, \"from\": 54, \"to\": 63, \"sentence\": \"“She had quite the following,” said her sister Alysia Vanitzian.\", \"id\": \"polusa_v1_55036659_-1_4_Vanitzian_55_64\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 36, \"to\": 41, \"sentence\": \"As Nancy Bobo, 60, stood with other Obama supporters, she wondered aloud where the supporters of Mr. Romney were.\", \"id\": \"allsides_6186_2658_40_Obama_36_41\"}\n{\"mention\": \"Hurricane Irma\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"Hurricane Irma poses special risks for Florida senior citizens\", \"id\": \"polusa_v1_113884850_-1_0_Hurricane Irma_0_14\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 95, \"to\": 97, \"sentence\": \"Over the course of his acclaimed surgical career at Johns Hopkins Medical Center in Baltimore, he earned the moniker “Gentle Ben.”\", \"id\": \"allsides_2788_1137_5_Ben Carson_95_97\"}\n{\"mention\": \"Gianforte\", \"polarity\": -1, \"from\": 3, \"to\": 12, \"sentence\": \"As Gianforte moved on top of Jacobs, he began yelling something to the effect of, “I'm sick and tired of this!”\", \"id\": \"polusa_v1_4397972_-1_10_Montana GOP House candidate Greg Gianforte_3_12\"}\n{\"mention\": \"Maxwell\", \"polarity\": -1, \"from\": 50, \"to\": 57, \"sentence\": \"Image copyright Metropolitan Police Image caption Maxwell pleaded guilty to a number of terrorism offences\\nHis wi-fi password was \\\"tiocfaidh1\\\" - a derivation of the Irish republican phrase \\\"tiocfaidh ar la\\\", or \\\"our day will come\\\".\", \"id\": \"polusa_v1_18176649_-1_15_Marine Ciarán Maxwell '_51_58\"}\n{\"mention\": \"Kasich\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Kasich, meanwhile, has taken a less confrontational approach in the race, casting himself as a uniting force and touting his economic record as governor.\", \"id\": \"allsides_2510_1022_45_Kasich_0_6\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 77, \"to\": 92, \"sentence\": \"Things could get really ugly Already, in recent days, reports indicated that President Trump is musing about firing Mueller as special counsel, and Trump allies in the media argued that he should do so.\", \"id\": \"allsides_954_384_19_President Trump_77_92\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She was the first lawmaker to visit federal prisons housing migrant children who were taken from their parents or carers during Trump’s family separation initiative.\", \"id\": \"polusa_v1_79082992_-1_22_Jayapal_0_3\"}\n{\"mention\": \"Lewandowski\", \"polarity\": 1, \"from\": 50, \"to\": 61, \"sentence\": \"“In a call on Saturday with a Fox News executive, Lewandowski stated that Megyn had a ‘rough couple of days after that last debate’ and he ‘would hate to have her go through that again,’” a Fox News statement said late Tuesday.\", \"id\": \"allsides_2551_1039_35_Trump’s campaign manager Corey Lewandowski_50_61\"}\n{\"mention\": \"Michael Hayden\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Michael Hayden on Trump: If someone else said that outside the hall, he’d be in the back of a police wagon https://t.co/4DFkNks2Kj — The Situation Room (@CNNSitRoom) August 9, 2016 “It suggests either a very bad taste reference to political assassination and an attempt at humor or an incredible insensitivity … to the prevalence of a political assassination inside of American history and how that is a topic that we don’t ever come close to, even when we think we’re trying to be light-hearted,” the ex-CIA leader said.\", \"id\": \"allsides_1916_779_13_former CIA Director Michael Hayden_0_14\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 116, \"to\": 121, \"sentence\": \"\\\"When he says, ‘Let’s make America great again,' that is code for, ‘Let’s take America backwards.’” How to approach Trump is only one part of the equation Clinton now confronts as she moves from the primary to the general.\", \"id\": \"allsides_2112_859_43_Donald Trump_116_121\"}\n{\"mention\": \"Jeff Sessions\", \"polarity\": 1, \"from\": 90, \"to\": 103, \"sentence\": \"And everything he was accused of, I’ve never seen, so I am basing on what my knowledge of Jeff Sessions is and I think he’ll be fair and very deliberate in what he does [as attorney general].”\", \"id\": \"allsides_1370_550_26_Jeff Sessions_90_103\"}\n{\"mention\": \"President Ortega\", \"polarity\": -1, \"from\": 223, \"to\": 239, \"sentence\": \"Read more about Nicaragua's crisis:\\nThe demonstrators in the Central American country first rallied against planned changes to the country's social security system, but the protests soon escalated to include the demand for President Ortega to resign.\", \"id\": \"polusa_v1_18467544_-1_10_President Ortega_224_240\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump, in asking his supporters to get out and vote for Blackburn, assured the crowd that Blackburn is \\\"a vote for me and everything we stand for.\\\"\", \"id\": \"polusa_v1_116002830_-1_34_Rick Klein\\nPresident Donald Trump_0_5\"}\n{\"mention\": \"Warren\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Warren took to Twitter to tip her hat to Booker's selfie game after the two posed together with a young woman while campaigning last month in South Carolina.\", \"id\": \"polusa_v1_4168551_-1_26_Elizabeth Warren_1_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 27, \"to\": 32, \"sentence\": \"But it doesn't matter that Trump said something insane and destructive.\", \"id\": \"allsides_2219_903_46_Donald Trump_27_32\"}\n{\"mention\": \"LUCAS\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"LUCAS: Basically, a case like Cohen's is very politically charged.\", \"id\": \"polusa_v1_52866424_-1_55_RYAN LUCAS_0_6\"}\n{\"mention\": \"Mimms\", \"polarity\": 0, \"from\": 212, \"to\": 217, \"sentence\": \"Former New York Times assistant managing editor Jim Roberts quoted McAuliffe as saying: “There are too many guns on the street…we worry about this every day for all of our citizens,” and BuzzFeed DC editor Sarah Mimms tweeted:\\nVA Gov.\", \"id\": \"polusa_v1_4323387_-1_4_Mimms_213_218\"}\n{\"mention\": \"McAuliffe\", \"polarity\": 1, \"from\": 67, \"to\": 76, \"sentence\": \"Former New York Times assistant managing editor Jim Roberts quoted McAuliffe as saying: “There are too many guns on the street…we worry about this every day for all of our citizens,” and BuzzFeed DC editor Sarah Mimms tweeted:\\nVA Gov.\", \"id\": \"polusa_v1_4323387_-1_4_Terry McAuliffe_68_77\"}\n{\"mention\": \"Mr. Rubio\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Rubio was on the hot seat to prove that despite his short political career and lack of major accomplishments in the Senate, he has what it takes to be president.\", \"id\": \"allsides_2514_1024_4_Marco Rubio_0_9\"}\n{\"mention\": \"Kaepernick\", \"polarity\": -1, \"from\": 67, \"to\": 77, \"sentence\": \"Simply put, President Trump is right to say that sports stars like Kaepernick aren’t helping the nation’s racial divide when they take a knee in protest of America’s cops.\", \"id\": \"allsides_553_220_22_Kaepernick_67_77\"}\n{\"mention\": \"President Trump\", \"polarity\": 1, \"from\": 12, \"to\": 27, \"sentence\": \"Simply put, President Trump is right to say that sports stars like Kaepernick aren’t helping the nation’s racial divide when they take a knee in protest of America’s cops.\", \"id\": \"allsides_553_220_22_President Trump_12_27\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 120, \"to\": 129, \"sentence\": \"“And remember, Meryl Streep introduced Hillary Clinton at her convention, and a lot of these people supported Hillary,” Mr. Trump said, referring to Ms. Streep’s remarks at the Democratic National Convention last summer on behalf of his opponent, Mrs. Clinton.\", \"id\": \"allsides_1464_590_16_Donald Trump_120_129\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 44, \"to\": 49, \"sentence\": \"The U.S. may have the arsenal to deliver on Trump’s threat to deliver fire and fury to North Korea, but Kim has a hostage in millions South Koreans who would be killed before Kim’s weaponry would be neutralized.\", \"id\": \"polusa_v1_3895161_-1_8_Donald Trump_45_50\"}\n{\"mention\": \"Kim\", \"polarity\": -1, \"from\": 104, \"to\": 107, \"sentence\": \"The U.S. may have the arsenal to deliver on Trump’s threat to deliver fire and fury to North Korea, but Kim has a hostage in millions South Koreans who would be killed before Kim’s weaponry would be neutralized.\", \"id\": \"polusa_v1_3895161_-1_8_Kim_105_108\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 113, \"to\": 120, \"sentence\": \"Trump called Streep \\\"one of the most over-rated actresses in Hollywood\\\" in a tweet Monday morning calling her a \\\"Hillary flunky who lost big.\\\"\", \"id\": \"allsides_1465_590_2_Hillary_113_120\"}\n{\"mention\": \"Kenneth Feld\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Kenneth Feld became visibly emotional while discussing the decision with a reporter.\", \"id\": \"allsides_1448_584_46_Juliette Feld_0_12\"}\n{\"mention\": \"Séamus Lawless\", \"polarity\": 1, \"from\": 0, \"to\": 14, \"sentence\": \"Séamus Lawless, 39, from Bray, was part of a team of climbers who reached the peak on Thursday.\", \"id\": \"polusa_v1_17946888_-1_3_Irish climber Seamus Lawless_1_15\"}\n{\"mention\": \"Kelly\", \"polarity\": -1, \"from\": 54, \"to\": 59, \"sentence\": \"\\\"I was blind-sided,\\\" Christie said Thursday, claiming Kelly \\\"lied\\\" to him when he asked senior staffers weeks ago about the lane closures.\", \"id\": \"allsides_4683_1963_14_Kelly_54_59\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 94, \"to\": 97, \"sentence\": \"Obama, who was elected as the first black editor of the Harvard Law Review in 1990, sought in his article to imbue his case with personal meaning, writing that his push toward eliminating mandatory minimum sentences and offering clemency to non-violent drug offenders was informed by his own history.\", \"id\": \"polusa_v1_4721255_-1_11_President-elect Donald Trump_95_98\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 6, \"to\": 11, \"sentence\": \"After Trump retweeted the report, she was asked about the information included in the article.\", \"id\": \"polusa_v1_115999710_-1_10_President Trump_6_11\"}\n{\"mention\": \"Chakrabarti\", \"polarity\": -1, \"from\": 301, \"to\": 312, \"sentence\": \"In March it was alleged there were no “walls of separation” in the 3,500 square feet of office space in Knoxville, Tennessee that in 2017 and 2018 housed two political action committees (PACs), two private consulting firms, and at least 12 congressional campaigns committees, all controlled or run by Chakrabarti.\", \"id\": \"polusa_v1_4321693_-1_15_Saikat Chakrabarti_302_313\"}\n{\"mention\": \"Katherine\", \"polarity\": 0, \"from\": 113, \"to\": 122, \"sentence\": \"Whether or not one person interrupted another depends on whom you ask, according to new research from Stanford’s Katherine Hilton, a doctoral candidate in linguistics.\", \"id\": \"polusa_v1_38903408_-1_7_Katherine_113_122\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 212, \"to\": 214, \"sentence\": \"“As all-important as the fight against racial discrimination was then, and remains today, know this: My commitment to confronting discrimination based on sexual orientation or gender identity runs just as deep,” he said.\", \"id\": \"allsides_4582_1918_12_Mr. Holder_212_214\"}\n{\"mention\": \"Smith\", \"polarity\": -1, \"from\": 20, \"to\": 25, \"sentence\": \"Lofchie objected to Smith's appointment as vice chairwoman of the Public Health, Safety and Transportation Committee, which he also was appointed to.\", \"id\": \"polusa_v1_59616265_-1_16_Patty Smith_21_26\"}\n{\"mention\": \"\\\" Page\", \"polarity\": 1, \"from\": 29, \"to\": 35, \"sentence\": \"It is to end the injustice,' \\\" Page told WCCO-TV in January.\", \"id\": \"polusa_v1_52945992_-1_47_Alan Page_29_35\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 1, \"to\": 3, \"sentence\": \"“He’s going to be on the Supreme Court with a huge taint and a big asterisk after his name,” Hirono said on ABC’s “This Week.”\", \"id\": \"polusa_v1_79070405_-1_6_Supreme Court Justice Brett Kavanaugh_2_4\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 76, \"to\": 78, \"sentence\": \"\\\"The science has clearly hardened since the Climate Change Act was agreed,\\\" he said.\", \"id\": \"polusa_v1_18326787_-1_16_Business Secretary Greg Clark_77_79\"}\n{\"mention\": \"Thomas\", \"polarity\": 1, \"from\": 33, \"to\": 39, \"sentence\": \"The painting is part of a series Thomas created that reimagines historical figures socializing in various contexts.\", \"id\": \"polusa_v1_55293450_-1_10_artist Andy Thomas_34_40\"}\n{\"mention\": \"Dana Perino\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Dana Perino currently hosts FOX News Channel’s (FNC) The Daily Briefing with Dana Perino (weekdays 2-3PM/ET) and also serves as co-host of The Five (weekdays 5-6PM/ET).\", \"id\": \"allsides_2729_1110_17_Dana Perino_0_11\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 151, \"to\": 155, \"sentence\": \"More immediately, the Republicans’ third debate, on Wednesday night, now looms as a potentially decisive moment for several candidates — above all Mr. Bush, whose performances have been lackluster so far, and whose staid, sober manner is proving an ill fit with voter discontent with long-serving elected officials.\", \"id\": \"allsides_2797_1141_14_Mr. Bush_151_155\"}\n{\"mention\": \"Chuck Schumer\", \"polarity\": -1, \"from\": 35, \"to\": 48, \"sentence\": \"(WASHINGTON) — Top Senate Democrat Chuck Schumer has pulled back an offer of $25 billion for President Donald Trump’s long-promised southern border wall, as lawmakers scrambled to figure out how to push a deal to protect 700,000 or more so-called Dreamer immigrants from deportation.\", \"id\": \"allsides_51_20_2_Chuck Schumer_37_50\"}\n{\"mention\": \"Kane County\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Kane County Associate Judge Linda S. Abrahamson accepted the plea.\", \"id\": \"polusa_v1_59509547_-1_3_Kane County_1_12\"}\n{\"mention\": \"\\\" Trump\", \"polarity\": 0, \"from\": 52, \"to\": 59, \"sentence\": \"\\\"After they made the alliance, their numbers tanked,\\\" Trump said Monday.\", \"id\": \"allsides_2243_912_32_Donald Trump in Indiana_52_59\"}\n{\"mention\": \"Kris Kobach\", \"polarity\": 0, \"from\": 27, \"to\": 38, \"sentence\": \"Facebook Twitter Pinterest Kris Kobach, vice-chair of the Presidential Advisory Commission on Election Integrity, at Trump International Golf Course.\", \"id\": \"polusa_v1_39161922_-1_11_Kris Kobach_28_39\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She pointed to the recent announcement by Netflix that the company would be providing up to a year of paid parental leave to argue that businesses know what's best for themselves.\", \"id\": \"allsides_2980_1219_8_Fiorina, a former chief executive of Hewlett-Packard_0_3\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 58, \"to\": 60, \"sentence\": \"\\\"This crisis is too important for us to wait any longer,\\\" he said.\", \"id\": \"polusa_v1_113878890_-1_19_Michael Bennet_58_60\"}\n{\"mention\": \"Dolan\", \"polarity\": -1, \"from\": 4, \"to\": 9, \"sentence\": \"But Dolan mischaracterized Bannon’s actual comments, as a look at the transcript of Bannon’s interview with CBS’s Charlie Rose on that topic clearly shows.\", \"id\": \"polusa_v1_4313485_-1_7_Dolan_5_10\"}\n{\"mention\": \"Bannon\", \"polarity\": 1, \"from\": 27, \"to\": 33, \"sentence\": \"But Dolan mischaracterized Bannon’s actual comments, as a look at the transcript of Bannon’s interview with CBS’s Charlie Rose on that topic clearly shows.\", \"id\": \"polusa_v1_4313485_-1_7_Steve Bannon_28_34\"}\n{\"mention\": \"her\", \"polarity\": -1, \"from\": 54, \"to\": 57, \"sentence\": \"Lois Lerner, the former IRS director accused of using her position to delay nonprofit applications to scores of conservative and tea party groups, has broken her wall of silence in a sit-down interview with Politico to say: “I didn’t do anything wrong.”\", \"id\": \"allsides_4127_1716_1_Lois Lerner_56_59\"}\n{\"mention\": \"President Trump\", \"polarity\": 1, \"from\": 4, \"to\": 19, \"sentence\": \"And President Trump has taken steps to increase opportunities for veterans after they return to civilian life, including through enhancing and expanding the post-9/11 GI Bill to a lifetime benefit.\", \"id\": \"polusa_v1_4589628_-1_28_President Trump_5_20\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 8, \"to\": 11, \"sentence\": \"We need his vote on stopping crime, illegal immigration, Border Wall, Military, Pro Life, V.A., Judges 2nd Amendment and more.\", \"id\": \"allsides_249_101_5_Republican Roy Moore_8_11\"}\n{\"mention\": \"Xi\", \"polarity\": -1, \"from\": 37, \"to\": 39, \"sentence\": \"Roman Pilipey / EPA\\nFrom the outset, Xi was compared to Mao because of the personality cult that was building around him.\", \"id\": \"polusa_v1_55261488_-1_25_Xi_37_39\"}\n{\"mention\": \"Paul\", \"polarity\": 0, \"from\": 50, \"to\": 54, \"sentence\": \"Another, more strategic challenge came from a man Paul had endorsed in his bid for a Senate seat in Texas: Ted Cruz.\", \"id\": \"allsides_2527_1029_60_Paul_50_54\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump appeared to relish the opportunity to speak in front of American workers, celebrating the increased job numbers, the rise in wages, and companies returning to the United States under his presidency.\", \"id\": \"polusa_v1_4301176_-1_4_Donald Trump_0_6\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 4, \"to\": 6, \"sentence\": \"But he was badly out-organized by Mr. Cruz, who relied on scores of church pastors and brought in hundreds of volunteers from as far as Idaho and Texas.\", \"id\": \"allsides_2534_1032_50_Mr. Trump_4_6\"}\n{\"mention\": \"him\", \"polarity\": 0, \"from\": 94, \"to\": 97, \"sentence\": \"U.S. officials speculate that they were for his children or wives, several of whom lived with him.\", \"id\": \"allsides_3221_1323_7_Osama bin Laden's_94_97\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 122, \"to\": 127, \"sentence\": \"So low was Kaine that he claimed Trump cared more about his tax returns than the troops — a slur so over-the-top that all Pence had to do was shake his head sadly.\", \"id\": \"allsides_1750_712_15_Mike Pence_122_127\"}\n{\"mention\": \"Kaine\", \"polarity\": -1, \"from\": 11, \"to\": 16, \"sentence\": \"So low was Kaine that he claimed Trump cared more about his tax returns than the troops — a slur so over-the-top that all Pence had to do was shake his head sadly.\", \"id\": \"allsides_1750_712_15_Kaine_11_16\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 33, \"to\": 38, \"sentence\": \"So low was Kaine that he claimed Trump cared more about his tax returns than the troops — a slur so over-the-top that all Pence had to do was shake his head sadly.\", \"id\": \"allsides_1750_712_15_Trump_33_38\"}\n{\"mention\": \"Najle\", \"polarity\": 0, \"from\": 18, \"to\": 23, \"sentence\": \"I ran Gervais and Najle’s conclusion by Greg Smith, who directs Pew’s polling efforts on religion.\", \"id\": \"allsides_1166_466_50_Najle_18_23\"}\n{\"mention\": \"Gervais\", \"polarity\": 0, \"from\": 6, \"to\": 13, \"sentence\": \"I ran Gervais and Najle’s conclusion by Greg Smith, who directs Pew’s polling efforts on religion.\", \"id\": \"allsides_1166_466_50_Gervais_6_13\"}\n{\"mention\": \"Smith\", \"polarity\": 0, \"from\": 45, \"to\": 50, \"sentence\": \"I ran Gervais and Najle’s conclusion by Greg Smith, who directs Pew’s polling efforts on religion.\", \"id\": \"allsides_1166_466_50_Smith_45_50\"}\n{\"mention\": \"Portman\", \"polarity\": 1, \"from\": 209, \"to\": 216, \"sentence\": \"“I think he’s happy and, you know, proud that we’ve come to this point, but he let it be my decision just as you 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\"polusa_v1_79065726_-1_61_Obama_42_56\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 0, \"from\": 14, \"to\": 26, \"sentence\": \"Interested in Donald Trump?\", \"id\": \"polusa_v1_115862502_-1_3_Donald Trump_16_28\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 14, \"to\": 16, \"sentence\": \"If confirmed, he would make the Supreme Court solidly conservative, joining Chief Justice John Roberts and Justices Clarence Thomas, Samuel Alito, and Neil Gorsuch — providing a five-vote majority.\", \"id\": \"polusa_v1_55364017_-1_12_federal appeals court Judge Brett Kavanaugh for Supreme Court_14_16\"}\n{\"mention\": \"Spicer\", \"polarity\": -1, \"from\": 129, \"to\": 135, \"sentence\": \"Meanwhile, lawmakers and Jewish organizations, including the Anne Frank Center, are calling for White House Press Secretary Sean Spicer’s resignation, after Spicer tried to drum up support for more U.S. military attacks against the Syrian regime by comparing Assad to Hitler and falsely claiming 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\"sentence\": \"After five days of silence, Mark Zuckerberg apologised for his company’s “mistakes”.\", \"id\": \"polusa_v1_39085040_-1_4_Mark Zuckerberg_28_43\"}\n{\"mention\": \"Bell\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Bell expressed sadness over the incident.\", \"id\": \"polusa_v1_55140384_-1_13_Sheriff Devon Bell_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 26, \"to\": 31, \"sentence\": \"This is a guy who accused Trump of treason on social media and was arrested for assaulting his girlfriend a decade ago.\\nNow would the media’s connect-the-dots mentality shift into higher gear if a Trump supporter who hated liberals started firing at a Democratic baseball practice?\", \"id\": \"polusa_v1_4512741_-1_21_Donald Trump_26_31\"}\n{\"mention\": \"Gilda Cobb-Hunter of Orangeburg\", \"polarity\": 0, \"from\": 0, \"to\": 31, \"sentence\": \"Gilda Cobb-Hunter of Orangeburg said on the House floor Wednesday she was told by the Orangeburg County 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was released on Sunday night where Harkin is shown saying that even if Ernst is “as good looking as Taylor Swift” she is not fit to represent the state of Iowa.\", \"id\": \"allsides_3962_1647_12_Taylor Swift_136_148\"}\n{\"mention\": \"Ridd\", \"polarity\": -1, \"from\": 43, \"to\": 47, \"sentence\": \"Among the allegations, the university says Ridd had “perpetuated a view that you were not allowed to talk to your wife about the disciplinary process, when in fact this was contrary to what you were told by verbally, and in writing … ”. He had denigrated a colleague, disclosed confidential information and “failed to take reasonable steps to avoid or manage a conflict of interest between your own interests and the interests of the Institute of Public Affairs (IPA) and the interests of the university”.\", \"id\": \"polusa_v1_38941265_-1_31_Ridd_44_48\"}\n{\"mention\": \"John McCain\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"John McCain's decision to oppose the latest Republican health care plan to repeal and replace the Affordable Care Act, the effort is still ongoing, GOP aides say -- at least for the moment.\", \"id\": \"polusa_v1_4868620_-1_2_John McCain_0_11\"}\n{\"mention\": \"Grant Hayes\", \"polarity\": -1, \"from\": 17, \"to\": 28, \"sentence\": \"Associated Press Grant Hayes after he was taken into custody by authorities.\", \"id\": \"polusa_v1_3955442_-1_28_Amanda Hayes_18_29\"}\n{\"mention\": \"Ann Romney\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Ann Romney ran for town 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0, \"from\": 128, \"to\": 138, \"sentence\": \"Days before the obituary was set to run in the print edition of The Courier-Journal, Williams’ son, Art Williams, and daughter, Carol Duff, were told it had been rejected, despite the fact that the family had paid $1,684 for it to appear.\", \"id\": \"polusa_v1_3912183_-1_7_Carol Duff_129_139\"}\n{\"mention\": \"Art Williams\", \"polarity\": 0, \"from\": 100, \"to\": 112, \"sentence\": \"Days before the obituary was set to run in the print edition of The Courier-Journal, Williams’ son, Art Williams, and daughter, Carol Duff, were told it had been rejected, despite the fact that the family had paid $1,684 for it to appear.\", \"id\": \"polusa_v1_3912183_-1_7_Art Williams_101_113\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 84, \"to\": 86, \"sentence\": \"\\\"God willing, this litany of stupidity will be the epitaph of the Haqqani Network,\\\" he said.\", \"id\": \"polusa_v1_55342650_-1_8_Boyle_85_87\"}\n{\"mention\": \"Donald 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  },
  {
    "path": "NewsSentiment/experiments/default/datasets/newsmtsc-rw-hf/test.jsonl",
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Circuit Attorney Kim Gardner interviews the woman who had an affair with Greitens.\", \"id\": \"polusa_v1_4198906_-1_14_Eric Greitens'_94_102\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 11, \"to\": 23, \"sentence\": \"On Sunday, Mrs. Clinton repeatedly said she was glad to be back in Iowa, but the state holds bitter memories for her.\", \"id\": \"allsides_4150_1727_17_Hillary Clinton_11_23\"}\n{\"mention\": \"President Boris Yeltsin\", \"polarity\": 1, \"from\": 165, \"to\": 188, \"sentence\": \"As soon as Bill Clinton assumed the White House in 1993, his experts discussed “formulating a policy of American tutelage”, including unabashed partisan support for President Boris Yeltsin.\", \"id\": \"polusa_v1_39052447_-1_20_President Boris Yeltsin_166_189\"}\n{\"mention\": \"Minhaj\", \"polarity\": 0, \"from\": 71, \"to\": 77, \"sentence\": \"“This event is about celebrating the first amendment and free speech,” Minhaj said.\\n.@HasanMinhaj: “This event is about celebrating the first amendment and free speech” #WHCD2017 pic.twitter.com/v3v6VDl8f0 — Hollywood Reporter (@THR) April 30, 2017\\n“Donald Trump doesn’t care about free speech,” he added.\", \"id\": \"polusa_v1_4300903_-1_8_Comedian Hasan Minhaj_72_78\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 38, \"to\": 40, \"sentence\": \"\\\"But maybe modern political history,\\\" he added.\", \"id\": \"allsides_611_243_3_Former White House chief strategist Steve Bannon_38_40\"}\n{\"mention\": \"President Obama\", \"polarity\": 1, \"from\": 57, \"to\": 72, \"sentence\": \"On Wednesday, in one of his strongest economic speeches, President Obama pushed past all the distractions of his opponents and addressed the core of those fears.\", \"id\": \"allsides_4791_2013_5_President Obama_57_72\"}\n{\"mention\": \"McCabe\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"McCabe kept personal memos regarding his interactions with Trump, the Associated Press revealed Saturday afternoon in a 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\"polusa_v1_3905186_-1_12_Aja Dang_0_5\"}\n{\"mention\": \"unlikely Mueller\", \"polarity\": 1, \"from\": 5, \"to\": 21, \"sentence\": \"It’s unlikely Mueller would have taken this step unless he felt there was a good reason to do so.\", \"id\": \"allsides_750_303_5_Special counsel Robert Mueller_5_21\"}\n{\"mention\": \"Pruitt\", \"polarity\": -1, \"from\": 70, \"to\": 76, \"sentence\": \"Chmielewski, who said he was pushed out of the agency for questioning Pruitt, said the EPA boss “just doesn’t understand what it’s like to be a public figure.”\", \"id\": \"polusa_v1_3977230_-1_16_Pruitt_70_76\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 58, \"to\": 63, \"sentence\": \"(At one point during a heated exchange about health care, Trump brought up Rubio’s much-maligned gaffe where he repeated himself “five times” during the New Hampshire debates.\", \"id\": \"allsides_2461_1000_12_Donald Trump_58_63\"}\n{\"mention\": \"Rubio\", \"polarity\": -1, \"from\": 75, \"to\": 80, \"sentence\": \"(At one point during a heated exchange about health care, Trump brought up Rubio’s much-maligned gaffe where he repeated himself “five times” during the New Hampshire debates.\", \"id\": \"allsides_2461_1000_12_Marco Rubio_75_80\"}\n{\"mention\": \"Duterte\", \"polarity\": -1, \"from\": 4, \"to\": 11, \"sentence\": \"And Duterte was initially dismissive of the case Sabio filed.\", \"id\": \"polusa_v1_52994289_-1_15_Duterte_5_12\"}\n{\"mention\": \"New Jersey governor Chris Christie\", \"polarity\": -1, \"from\": 27, \"to\": 61, \"sentence\": \"According to WatchDog.org, New Jersey governor Chris Christie spent nearly $83,000 on concessions at Jets and Giants games during the 2010 and 2011 seasons.\", \"id\": \"allsides_3258_1339_1_Chris Christie_29_63\"}\n{\"mention\": \"DeVos\", \"polarity\": -1, \"from\": 60, \"to\": 65, \"sentence\": \"Democrats took the Senate floor and spoke all night against DeVos, raising some damn good points: \\\"When presented with a nominee who says that public education is a 'dead end' for students in this country, people take it personally,\\\" [Sen. Chris Murphy] said, referring to a 2015 speech given by DeVos.\", \"id\": \"allsides_1375_552_4_Betsy DeVos_60_65\"}\n{\"mention\": \"New York Times reporter Julie Bosman, who covers the region\", \"polarity\": 0, \"from\": 0, \"to\": 59, \"sentence\": \"New York Times reporter Julie Bosman, who covers the region, said they apologized after realizing she “wasn’t police.”\", \"id\": \"allsides_4271_1782_2_New York Times reporter Julie Bosman, who covers the region_0_59\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He raised the gun and started firing.\", \"id\": \"allsides_5046_2128_13_Todd Brundidge_0_2\"}\n{\"mention\": \"Wilcox\", \"polarity\": 1, \"from\": 89, \"to\": 95, \"sentence\": \"“Not being viewed as an enemy, but being viewed as an asset is so refreshing,” said Alex Wilcox, Chief Executive Officer of JetSuite Inc., who, on Thursday, spoke to the Dallas Business Journal.\", \"id\": \"polusa_v1_4359253_-1_3_Wilcox_90_96\"}\n{\"mention\": \"JetSuite\", \"polarity\": 0, \"from\": 124, \"to\": 132, \"sentence\": \"“Not being viewed as an enemy, but being viewed as an asset is so refreshing,” said Alex Wilcox, Chief Executive Officer of JetSuite Inc., who, on Thursday, spoke to the Dallas Business Journal.\", \"id\": \"polusa_v1_4359253_-1_3_JetSuite_125_133\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 72, \"to\": 79, \"sentence\": \"Paul Manafort breached plea deal by repeatedly lying in Russia inquiry, Mueller says\", \"id\": \"polusa_v1_38988170_-1_0_Mueller_72_79\"}\n{\"mention\": \"Wasserman Schultz's\", \"polarity\": -1, \"from\": 5, \"to\": 24, \"sentence\": \"But, Wasserman Schultz's emphasis on her own political future — and the need to make sure she was front and center when it came to media attention and interviews — rubbed lots and lots of people the wrong way.\", \"id\": \"allsides_1967_800_26_Debbie Wasserman Schultz_5_24\"}\n{\"mention\": \"Zichal\", \"polarity\": 1, \"from\": 76, \"to\": 82, \"sentence\": \"Paul Bledsoe, who worked on climate issues in the Clinton White House, said Zichal renewed a pledge Obama made in in his first year in office, during global climate talks in Copenhagen, to cut U.S. carbon emissions by about 17 percent by 2020, compared to 2005 levels.\", \"id\": \"allsides_5282_2242_18_Heather Zichal_76_82\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 111, \"to\": 116, \"sentence\": \"Looking to push the idea Kelly will have authority within the West Wing, a senior administration official said Trump has given \\\"Gen. 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Leader Eric Cantor (R-Va_83_89\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She noted that \\\"going on the Sunday shows is not my favorite thing,\\\" a possible reference to claims that she declined to go on television Sept. 16.\", \"id\": \"allsides_5809_2488_38_Clinton_1_4\"}\n{\"mention\": \"Rob Goldman\", \"polarity\": 0, \"from\": 87, \"to\": 98, \"sentence\": \"After the US indicted 13 Russian nationals for election meddling, Facebook's VP of ads Rob Goldman took to Twitter on Friday, arguing that the main goal of the campaign wasn't to sway the election since much of the Kremlin-backed advertising spend on Facebook occurred after Nov. 8.\", \"id\": \"polusa_v1_4402721_-1_3_Rob Goldman_88_99\"}\n{\"mention\": \"“President Trump\", \"polarity\": -1, \"from\": 0, \"to\": 16, \"sentence\": \"“President Trump is legally required to honor our treaty rights and provide a fair and reasonable pipeline process,” said Standing Rock Sioux tribal chairman Dave Archambault, who called Trump’s action “politically motivated”.\", \"id\": \"polusa_v1_39086177_-1_3_“President Trump_1_17\"}\n{\"mention\": \"Sean Hannity\", \"polarity\": -1, \"from\": 68, \"to\": 80, \"sentence\": \"Yet, when arch-capitalists such as Bill O’Reilly, Katie Hopkins and Sean Hannity find themselves at the receiving end of corporate savagery, their reactions speak volumes.\", \"id\": \"polusa_v1_38974957_-1_13_Sean Hannity_69_81\"}\n{\"mention\": \"Browder\", \"polarity\": 0, \"from\": 52, \"to\": 59, \"sentence\": \"Keep up with this story and more by subscribing now Browder, who had been an American citizen but became a British subject, tells Newsweek he learned of his ban when he was denied a standard Electronic System for Travel Authorization waiver for a flight to the U.S.\", \"id\": \"allsides_433_172_7_Browder_52_59\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 10, \"to\": 19, \"sentence\": \"At times, Mr. Trump even mocked Iowans.\", \"id\": \"allsides_2534_1032_59_Mr. Trump_10_19\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 99, \"to\": 104, \"sentence\": \"CORNISH: Some people have raised the question of North Korea, looking to a template there from the Trump administration.\", \"id\": \"polusa_v1_52991436_-1_17_President Trump_100_105\"}\n{\"mention\": \"Krauthammer\", \"polarity\": 0, \"from\": 105, \"to\": 116, \"sentence\": \"Further, there is one obvious “contradiction” currently “gnawing away” at Obama’s case for Syria action, Krauthammer explained.\", \"id\": \"allsides_5060_2135_3_Charles Krauthammer_105_116\"}\n{\"mention\": \"Tapper\", \"polarity\": -1, \"from\": 22, \"to\": 28, \"sentence\": \"Here is a sampling of Tapper’s unrelenting cheap shots against Miller:\\n…”I’m sure [Trump’s] watching and he’s happy that you said that.”\", \"id\": \"polusa_v1_4328888_-1_23_Jake Tapper's_23_29\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 30, \"to\": 35, \"sentence\": \"Washington – President Donald Trump on Tuesday said Rep.\", \"id\": \"allsides_456_182_1_Mr. Trump_32_37\"}\n{\"mention\": \"Najib\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Najib said the facts would show he \\\"returned a large sum of money\\\" right after he lost the national election this past spring.\", \"id\": \"polusa_v1_52876943_-1_13_Najib_0_6\"}\n{\"mention\": \"Pelosi\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Pelosi was undisputedly correct about one thing: Republicans desperately want to sit around and talk about Benghazi -- it is absolute catnip for their political base and there is a real belief in some GOP circles that the full story is simply not being told.\", \"id\": \"allsides_4477_1871_25_House Minority Leader Nancy Pelosi_0_6\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump has traveled nearly every weekend to his luxury properties in Florida, Virginia and New Jersey as the agency protects an unprecedented 42 officials.\", \"id\": \"polusa_v1_4237513_-1_21_pro-Trump_0_5\"}\n{\"mention\": \"Priebus\", \"polarity\": -1, \"from\": 15, \"to\": 22, \"sentence\": \"By pushing out Priebus, Trump is ousting a Republican Party man and replacing him with a less political former general who has few ties to the GOP or even politics in general.\", \"id\": \"allsides_775_313_5_Reince Priebus_15_22\"}\n{\"mention\": \"an “Ambassador for Humanity” award from Steven Spielberg at a Holocaust memorial event sponsored by the University of Southern California’s Shoah Foundation, which was founded by the director\", \"polarity\": 1, \"from\": 21, \"to\": 212, \"sentence\": \"He will also receive an “Ambassador for Humanity” award from Steven Spielberg at a Holocaust memorial event sponsored by the University of Southern California’s Shoah Foundation, which was founded by the director.\", \"id\": \"allsides_4464_1866_17_Mr. Spielberg_21_212\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 85, \"to\": 90, \"sentence\": \"One prominent Cuban dissident, though, argued that, while he had initially supported Obama’s new policy, he has concluded that it is not working.\", \"id\": \"allsides_948_381_28_Obama_85_90\"}\n{\"mention\": \"Spletstoser\", \"polarity\": -1, \"from\": 245, \"to\": 256, \"sentence\": \"The Army colonel suggested her experience could have an impact on victims stepping forward, saying, \\\"It basically tells sexual assault survivors: ‘Don't bother reporting, you won't be taken seriously, and we'll give your attacker a promotion.'\\\"\\nSpletstoser was removed from her position at U.S. Strategic Command after an investigation in early 2018 determined she had engaged in a toxic leadership style with her subordinate staff.\", \"id\": \"polusa_v1_115885383_-1_37_Spletstoser_246_257\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump Organization officials did not immediately respond to ABC News requests for comment.\", \"id\": \"polusa_v1_115879353_-1_19_candidate Donald Trump_1_6\"}\n{\"mention\": \"Stephen Paddock\", \"polarity\": -1, \"from\": 191, \"to\": 206, \"sentence\": \"Ask yourself if all those lives lost and lives maimed at the hands of white, American gun owners ― people who could look like you, people who live quietly in your community, like 64-year-old Stephen Paddock who apparently liked to gamble and go to shows in Vegas ― are worth trading for the freedom to own assault weapons.\", \"id\": \"allsides_524_208_31_Stephen Paddock_191_206\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 18, \"to\": 25, \"sentence\": \"The victory gives Sanders a total of three victories over the weekend to Clinton’s one, in the Louisiana primary.\", \"id\": \"allsides_2432_987_43_Sanders_18_25\"}\n{\"mention\": \"Spicer\", \"polarity\": 0, \"from\": 17, \"to\": 23, \"sentence\": \"Trump picks Sean Spicer for press secretary\", \"id\": \"allsides_1513_610_0_Republican Party communications chief Sean Spicer_17_23\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 6, \"to\": 8, \"sentence\": \"“What he meant was we can stop Hillary Clinton from being elected,” he told CNN’s Wolf Blitzer.\", \"id\": \"allsides_1914_779_25_Duncan Hunter (R-Calif.)_6_8\"}\n{\"mention\": \"Wolf Blitzer\", \"polarity\": 0, \"from\": 82, \"to\": 94, \"sentence\": \"“What he meant was we can stop Hillary Clinton from being elected,” he told CNN’s Wolf Blitzer.\", \"id\": \"allsides_1914_779_25_Wolf Blitzer_82_94\"}\n{\"mention\": \"AM Mandy Jones\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"AM Mandy Jones suspended from UKIP after Hamilton remarks\", \"id\": \"polusa_v1_18202424_-1_0_AM Mandy Jones_0_14\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 19, \"to\": 24, \"sentence\": \"For instance, when Obama vowed to make paying back student loans easier, Democratic lawmakers introduced bills aimed at reducing debt for loan borrowers.\", \"id\": \"allsides_2600_1060_24_Obama_19_24\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 135, \"to\": 140, \"sentence\": \"And as recently as last week Collins was the lone Republican to oppose the nomination of Andrew Wheeler, who was narrowly confirmed as Trump’s pick to head the Environmental Protection Agency.\", \"id\": \"polusa_v1_4143643_-1_54_President Donald Trump_136_141\"}\n{\"mention\": \"Zhu\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"Zhu had deleted the tweets by then, but she seemed to defend them after her dismissal, tweeting that she was a victim of “prejudice views against people with ‘different opinions.’\", \"id\": \"polusa_v1_131734847_-1_8_Kathy Zhu_1_4\"}\n{\"mention\": \"17-year-old Nelson Martinez\", \"polarity\": 1, \"from\": 11, \"to\": 38, \"sentence\": \"Graduating 17-year-old Nelson Martinez said his activism supporting fellow DACA students helped him get a full scholarship to College of the Holy Cross in Massachusetts.\", \"id\": \"polusa_v1_115881202_-1_35_17-year-old Nelson Martinez_12_39\"}\n{\"mention\": \"Breitbart Texas\", \"polarity\": 0, \"from\": 53, \"to\": 68, \"sentence\": \"State Representative Dennis Bonnen (R-Angleton) told Breitbart Texas, “For years, Texas has stood in the gap where the federal government has failed.\", \"id\": \"polusa_v1_4308468_-1_5_Breitbart Texas_53_68\"}\n{\"mention\": \"Bellingcat\", \"polarity\": 1, \"from\": 45, \"to\": 55, \"sentence\": \"Seven years later, his investigative website Bellingcat has been responsible for revealing key aspects of some of the world’s biggest stories.\", \"id\": \"polusa_v1_39026885_-1_2_Bellingcat_45_55\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 19, \"to\": 22, \"sentence\": \"Seven years later, his investigative website Bellingcat has been responsible for revealing key aspects of some of the world’s biggest stories.\", \"id\": \"polusa_v1_39026885_-1_2_Eliot Higgins_19_22\"}\n{\"mention\": \"It\", \"polarity\": 0, \"from\": 0, 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his administration’s lapses and do the minimum to appear to be reacting to them without actually doing anything.\", \"id\": \"allsides_2684_1092_4_Obama_8_10\"}\n{\"mention\": \"Burns\", \"polarity\": 0, \"from\": 64, \"to\": 69, \"sentence\": \"On Saturday, members of the militia attended a demonstration in Burns that had gathered to protest the Hammonds' case.\", \"id\": \"allsides_2623_1069_36_Burns_64_69\"}\n{\"mention\": \"Mr. McCain\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Mr. McCain said Sunday that the investigation was necessary to determine Russia’s motives but that Russian involvement was not in question.\", \"id\": \"allsides_1550_624_41_Mr. McCain_0_10\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 95, \"to\": 101, \"sentence\": \"A separate CNN poll, also conducted before the grand jury announcement, found that most wanted Wilson charged with a crime: 32 percent of Americans thought Wilson should be charged with murder, 25 percent that he 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\"polarity\": -1, \"from\": 78, \"to\": 91, \"sentence\": \"The Washington Post was accurate, based on unnamed sources, in reporting that Michael Flynn not leveling with the vice president about his past contacts with the Russian ambassador.\", \"id\": \"allsides_1338_538_15_Michael Flynn_78_91\"}\n{\"mention\": \"Assange\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Assange, who has been credited by Trump fans with campaign-changing clout ever since his website published emails obtained in a hack of the Democratic National Committee, spoke after an hour of updates on WikiLeaks's content and legal fights, and dismissed a rumor that the news conference had been called to destroy Clinton.\", \"id\": \"allsides_1758_715_5_WikiLeaks founder Julian Assange_0_7\"}\n{\"mention\": \"Christie\", \"polarity\": -1, \"from\": 59, \"to\": 67, \"sentence\": \"Since cruising to an easy re-election victory in November, Christie has been hit with multiple investigations into traffic 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the successful economic record of his presidency to offer an illustration of the magnitude of the problems Mr. Obama inherited when he took office in 2009.\", \"id\": \"allsides_6275_2698_24_Clinton_0_11\"}\n{\"mention\": \"Saul Loeb\", \"polarity\": 0, \"from\": 8, \"to\": 17, \"sentence\": \"(Photo: Saul Loeb, AFP/Getty Images)\\nAlthough his words are blunter, President Trump’s recent attacks on Germany’s trade policies have been made frequently by the global political and economic establishment — and by his predecessor Barack Obama.\", \"id\": \"polusa_v1_4248159_-1_4_Saul Loeb_8_17\"}\n{\"mention\": \"McConnell\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"McConnell has earned a reputation as a talented legislative tactician and dealmaker who has held his caucus together more effectively than Speaker Paul Ryan or his predecessor John Boehner have in the House.\", \"id\": \"allsides_1110_443_23_Capito_0_9\"}\n{\"mention\": \"Biden\", \"polarity\": 0, \"from\": 18, 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the 2020 campaign trail today\\nJoe Biden, in New York, speaks at the Biden Courage Awards… Bill Weld, meanwhile, meets with New Hampshire Gov.\", \"id\": \"polusa_v1_55262155_-1_56_Bill Weld_94_103\"}\n{\"mention\": \"Biden\", \"polarity\": 1, \"from\": 37, \"to\": 42, \"sentence\": \"On the 2020 campaign trail today\\nJoe Biden, in New York, speaks at the Biden Courage Awards… Bill Weld, meanwhile, meets with New Hampshire Gov.\", \"id\": \"polusa_v1_55262155_-1_56_Biden_38_43\"}\n{\"mention\": \"McCain\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"McCain's office had previously said he would be recovering from the blood clot procedure for at least the next week.\", \"id\": \"polusa_v1_55207756_-1_33_McCain_1_7\"}\n{\"mention\": \"Fontaine\", \"polarity\": -1, \"from\": 73, \"to\": 81, \"sentence\": \"(Zbigniew Bzdak/Chicago Tribune)\\nThough she kept her $90,000-a-year job, Fontaine has not returned to street duties.\", \"id\": 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witness the start of a new era in their country's history\\nImage copyright Reuters Image caption Mr Mnangagwa's swearing-in follows the dramatic departure of Robert Mugabe after 37 years of authoritarian rule\\nImage copyright Reuters Image caption Mr Mnangagwa was the former vice-president, who was dismissed earlier this month, leading the army to intervene and force Mr Mugabe to resign\\nImage copyright Reuters Image caption Mr Mnangagwa, who had fled the country, returned from exile on Wednesday 21 November\\nImage copyright Reuters Image caption The new president (centre, left) arrived with his wife Auxilia (centre, right).\", \"id\": \"polusa_v1_17864917_-1_4_Zimbabwe's new President Emmerson Mnangagwa_200_212\"}\n{\"mention\": \"Jenkinson\", \"polarity\": 1, \"from\": 85, \"to\": 94, \"sentence\": \"From striking miners to Palestinian refugees, this powerful retrospective highlights Jenkinson’s talent for capturing the humanity at the heart of the action\", \"id\": 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and, in particular, to stop government raids on private business that threaten to frighten away potential investors and stymy the country’s economic recovery.\", \"id\": \"polusa_v1_4463280_-1_17_Poroshenko_5_15\"}\n{\"mention\": \"Corker\", \"polarity\": 0, \"from\": 262, \"to\": 268, \"sentence\": \"“The president has not yet been able to demonstrate the stability, nor some of the competence, that he needs to demonstrate in order for him to be successful — and our nation and our world needs for him to be successful, whether you are Republican or Democrat,” Corker added.\", \"id\": \"allsides_673_271_7_Bob Corker_262_268\"}\n{\"mention\": \"\\\" Booker\", \"polarity\": 1, \"from\": 155, \"to\": 163, \"sentence\": \"\\\"My plan to reduce firearm suicide is simple: prevent guns from getting in the hands of those who have shown signs of wanting to hurt themselves or others,\\\" Booker added in the statement.\", \"id\": \"polusa_v1_113832826_-1_16_Booker_156_164\"}\n{\"mention\": 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denunciation, in the days after the interview, as backtracking.\", \"id\": \"allsides_1867_760_64_Bernie Sanders’_19_22\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She falsely paints his repeated denunciation, in the days after the interview, as backtracking.\", \"id\": \"allsides_1867_760_64_Clinton_0_3\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 4, \"to\": 9, \"sentence\": \"The Obama administration is appealing the 5th Circuit Court of Appeals’ November decision to keep in place a district court’s ruling blocking the amnesty programs from moving forward.\", \"id\": \"allsides_2574_1049_3_Obama_4_9\"}\n{\"mention\": \"District Judge Lee Yeakel\", \"polarity\": 0, \"from\": 0, \"to\": 25, \"sentence\": \"District Judge Lee Yeakel has blocked the state from enforcing a requirement that abortion-providing doctors obtain admitting privileges at local hospitals — a restriction that would have ended abortion services at one-third of the health centers currently providing them.\", \"id\": \"allsides_4912_2067_2_District Judge Lee Yeakel_0_25\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 58, \"to\": 61, \"sentence\": \"Critics of Lopez Obrador have long attempted to associate him with Venezuelan-style socialism, despite little evidence he favors such policies.\", \"id\": \"polusa_v1_4480946_-1_6_Venezuela's socialist President Nicolas Maduro_59_62\"}\n{\"mention\": \"Carroll\", \"polarity\": 1, \"from\": 63, \"to\": 70, \"sentence\": \"City Councilwoman Esther Rocha-Baldazo and businessman William Carroll deftly answered questions posed by Julie Bradford of the Lake Station-New Chicago Public Library.\", \"id\": \"polusa_v1_59533704_-1_2_Carroll_64_71\"}\n{\"mention\": \"Rocha-Baldazo\", \"polarity\": 1, \"from\": 25, \"to\": 38, \"sentence\": \"City Councilwoman Esther Rocha-Baldazo and businessman William Carroll deftly answered questions posed by Julie Bradford of the Lake Station-New Chicago Public Library.\", \"id\": \"polusa_v1_59533704_-1_2_Rocha-Baldazo_26_39\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 68, \"to\": 71, \"sentence\": \"The presumptive Democratic presidential nominee also is reaffirming her support for a public-option insurance plan and for expanding Medicare by letting people age 55 year and older opt in.\", \"id\": \"allsides_2008_818_4_Hillary Clinton_68_71\"}\n{\"mention\": \"Aaron Rich\", \"polarity\": -1, \"from\": 79, \"to\": 89, \"sentence\": \"When previously asked about the lawsuit, Butowsky told CNN he had no idea what Aaron Rich was \\\"talking about\\\" and asked, \\\"I have nothing else to say, other than how many more family members do the Riches have that want to sue me?\\\"\", \"id\": \"polusa_v1_116922446_-1_20_Aaron Rich_80_90\"}\n{\"mention\": \"Butowsky\", \"polarity\": 0, \"from\": 41, \"to\": 49, \"sentence\": \"When previously asked about the lawsuit, Butowsky told CNN he had no idea what Aaron Rich was \\\"talking about\\\" and asked, \\\"I have nothing else to say, other than how many more family members do the Riches have that want to sue me?\\\"\", \"id\": \"polusa_v1_116922446_-1_20_Butowsky_42_50\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 4, \"to\": 7, \"sentence\": \"But she was also dogged by questions about her record at Hewlett-Packard, where she was hired as CEO in 1999.\", \"id\": \"allsides_2501_1019_42_Fiorina_4_7\"}\n{\"mention\": \"Holder\", \"polarity\": 0, \"from\": 20, \"to\": 26, \"sentence\": \"The department said Holder plans to engage with news media organizations, including print media, wire services, radio, television, online media and news and trade associations.\", \"id\": \"allsides_5347_2272_23_Attorney General Eric Holder_20_26\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 109, \"to\": 118, \"sentence\": \"One stressed that the move had been in the works for many weeks, particularly since it had become clear that Mr. Trump would be the Republican nominee.\", \"id\": \"allsides_2070_842_32_Mr. Trump_109_118\"}\n{\"mention\": \"Merkel\", \"polarity\": 1, \"from\": 92, \"to\": 98, \"sentence\": \"So when Martin Schulz returned home to Germany with the goal of unseating Chancellor Angela Merkel, perhaps the world’s most powerful woman, it was understandably viewed as a suicide mission.\", \"id\": \"polusa_v1_55114716_-1_2_Merkel_93_99\"}\n{\"mention\": \"Wilson\", \"polarity\": 1, \"from\": 41, \"to\": 47, \"sentence\": \"More than 100 friends and family greeted Wilson as he arrived Wednesday afternoon at Shreveport Regional Airport.\", \"id\": \"polusa_v1_4565068_-1_6_Zachary Wilson_41_47\"}\n{\"mention\": \"Hillary Clintons\", \"polarity\": -1, \"from\": 12, \"to\": 28, \"sentence\": \"Why is that Hillary Clintons family and Dems dealings with Russia are not looked at, but my non-dealings are?— Donald J. Trump (@realDonaldTrump) June 15, 2017 Crooked H destroyed phones w/ hammer, 'bleached' emails, & had husband meet w/AG days before she was cleared- & they talk about obstruction?— Donald J. Trump (@realDonaldTrump) June 15, 2017 The president's tweets come after it was reported Wednesday that Robert Mueller, special counsel for the investigation into Russian meddling in the 2016 election, is now investigating Trump for obstruction of justice.\", \"id\": \"allsides_953_383_6_Hillary Clintons_12_28\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 152, \"to\": 157, \"sentence\": \"I DON'T BELIEVE YOU\\n#TrumpsKidnappingChildren #TrumpConcentrationCamps — erotesis (@erotesis) June 18, 2018\\nSome speculated what was really going on in Trump’s mind.\", \"id\": \"polusa_v1_3931081_-1_17_Donald Trump_152_157\"}\n{\"mention\": \"Ashraf Ghani\", \"polarity\": 0, \"from\": 4, \"to\": 16, \"sentence\": \"Has Ashraf Ghani talked about this?\", \"id\": \"polusa_v1_4494836_-1_19_Ashraf Ghani_4_16\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 62, \"to\": 67, \"sentence\": \"As to whether President Trump made the right decision to fire Flynn in February, after it came to light he had discussed U.S. sanctions on Russia when he told Vice President Mike Pence he hadn’t, Spicer said it was the right call.\", \"id\": \"polusa_v1_4332225_-1_30_former National Security Adviser Michael Flynn_63_68\"}\n{\"mention\": \"Spicer\", \"polarity\": 0, \"from\": 196, \"to\": 202, \"sentence\": \"As to whether President Trump made the right decision to fire Flynn in February, after it came to light he had discussed U.S. sanctions on Russia when he told Vice President Mike Pence he hadn’t, Spicer said it was the right call.\", \"id\": \"polusa_v1_4332225_-1_30_Sean Spicer_197_203\"}\n{\"mention\": \"Murphy\", \"polarity\": -1, \"from\": 47, \"to\": 53, \"sentence\": \"Read more here\\n—“NJ political analysts dissect Murphy’s fumble of the Katie Brennan case, tax incentives, and Trump’s immigration policy” Read more here\\n—“Faith-based leaders push for Murphy’s millionaire’s tax” Read more here\\n—“Attention tobacco companies.\", \"id\": \"polusa_v1_79066149_-1_84_Murphy_47_53\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He had no experience of departmental office, and behaved like Donald Trump in khaki.\", \"id\": \"polusa_v1_39035126_-1_29_Williamson_0_2\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": 1, \"from\": 60, \"to\": 69, \"sentence\": \"In the version of the poll that Ipsos released on Saturday, Mr. Obama led by one percentage point, 44-43, among likely voters.\", \"id\": \"allsides_6293_2706_8_Mr. Obama_60_69\"}\n{\"mention\": \"Mr. Kasich\", \"polarity\": 1, \"from\": 136, \"to\": 146, \"sentence\": \"Leading the Kasich effort in New Hampshire is John E. Sununu, the former senator, who warmed up the crowd on Tuesday by reminding it of Mr. Kasich’s work in Washington.\", \"id\": \"allsides_3025_1237_40_classic Kasich_136_146\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 1, \"to\": 4, \"sentence\": \"“She said the inspector had decided it was not ‘cost effective’ to investigate it in terms of the cost and manpower hours.\", \"id\": \"polusa_v1_4330003_-1_6_Victoria Woods_2_5\"}\n{\"mention\": \"Ivanka Trump\", \"polarity\": 0, \"from\": 120, \"to\": 132, \"sentence\": \"House Judiciary Committee Chairman Jerry Nadler, D-N.Y., declined to say Thursday why his panel didn't send a letter to Ivanka Trump in its first round of document requests, but didn't rule out doing so later.\", \"id\": \"polusa_v1_115910038_-1_37_Ivanka Trump_121_133\"}\n{\"mention\": \"Hillary Clinton's\", \"polarity\": -1, \"from\": 54, \"to\": 71, \"sentence\": \"Donald Trump's campaign Friday slammed the release of Hillary Clinton's taxes as merely \\\"an attempt at distraction and misdirection\\\" from the Democratic nominee's email scandal.\", \"id\": \"allsides_1904_775_1_Hillary Clinton's_56_73\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 44, \"to\": 49, \"sentence\": \"As part of that practice, neither President Obama nor any White House official ever ordered surveillance on any U.S. citizen.\", \"id\": \"allsides_1297_519_40_Mr. Obama_44_49\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 136, \"to\": 151, \"sentence\": \"In an atmosphere where some delegates remain anti-Trump and party leaders like Paul Ryan are barely mentioning Trump in their speeches, Hillary Clinton is a unifying force.\", \"id\": \"allsides_1985_807_31_Hillary Clinton_136_151\"}\n{\"mention\": \"Manning\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Manning is more than six years into a 35-year sentence at the military prison at Fort Leavenworth, Kansas for leaking classified government and military documents to the anti-secrecy website WikiLeaks.\", \"id\": \"allsides_1442_581_13_Manning_0_7\"}\n{\"mention\": \"Sotomayor\", \"polarity\": 0, \"from\": 8, \"to\": 17, \"sentence\": \"Justice Sotomayor acted after the United States Court of Appeals for the 10th Circuit, in Denver, declined to issue an injunction.\", \"id\": \"allsides_4700_1973_17_Justice Sonia Sotomayor_8_17\"}\n{\"mention\": \"Spicer\", \"polarity\": -1, \"from\": 144, \"to\": 150, \"sentence\": \"That was positively Soviet. https://t.co/jcj8cMeKxq > — Joy Reid (@JoyAnnReid) January 21, 2017 Left-wing Think Progress’s Judd Legum suggested Spicer had “torched his credibility” for confronting the media’s misreporting with the truth: > Spicer torching his credibility on DAY ONE > — Judd Legum (@JuddLegum) January 21, 2017 Naturally, other media figures from the New York Times, Washington Post, Huffington Post, and Salon also complained: > In that rendition of history Spicer gave, with no q's taken and false info given, the reality of what's happening w rallies doesn't exist.\", \"id\": \"allsides_1428_575_21_White House Press Secretary Sean Spicer_144_150\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 14, \"to\": 17, \"sentence\": \"“Importantly, she also lacks the mental and physical stamina to take on ISIS and all the many adversaries we face — not only in terrorism, but in trade and every other challenge we must confront to turn this country around.”\", \"id\": \"allsides_1895_772_22_Clinton_14_17\"}\n{\"mention\": \"Darrell Issa\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Darrell Issa to apologize after the California congressman bashed the current administration spokesman as a “paid liar.”\", \"id\": \"allsides_5334_2266_2_Issa_0_12\"}\n{\"mention\": \"DeVos\", \"polarity\": 1, \"from\": 8, \"to\": 13, \"sentence\": \"SIEGEL: DeVos has strong Republican support, but she fielded some tough questions from the committee's Democrats.\", \"id\": \"polusa_v1_52913186_-1_9_Betsy DeVos_9_14\"}\n{\"mention\": \"Steyer\", \"polarity\": -1, \"from\": 25, \"to\": 31, \"sentence\": \"With the amount of money Steyer spent, a whopping $74.3 million, and the results he received in return, he got trounced.\", \"id\": \"allsides_3757_1553_7_Steyer_26_32\"}\n{\"mention\": \"Castaneda\", \"polarity\": -1, \"from\": 47, \"to\": 56, \"sentence\": \"Police said shortly after 6 p.m. on Wednesday, Castaneda drove up to a Chevron gas station, where he attacked a man pumping gas “for no reason.”\", \"id\": \"polusa_v1_4562489_-1_34_Castaneda_48_57\"}\n{\"mention\": \"Franken\", \"polarity\": -1, \"from\": 89, \"to\": 96, \"sentence\": \"As our Theodore Kupfer writes below, KABC radio host Leeann Tweeden says that Senator Al Franken groped and forcibly kissed her on a USO tour in 2006.\", \"id\": \"allsides_312_126_3_Franken_89_96\"}\n{\"mention\": \"Francis\", \"polarity\": 1, \"from\": 202, \"to\": 209, \"sentence\": \"Image copyright AFP/Getty Images Image caption The Vatican said it had not planned to publish the letter in full\\nThough Pope Benedict is often characterised as a more hardline, doctrinaire pontiff than Francis, he has spoken warmly of his successor and his \\\"goodness\\\".\", \"id\": \"polusa_v1_17958842_-1_21_Pope Francis_203_210\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 24, \"to\": 31, \"sentence\": \"Three of the four chose Clinton over Donald Trump in their presidential vote.\", \"id\": \"polusa_v1_55243640_-1_8_Hillary Clinton_25_32\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": 0, \"from\": 234, \"to\": 243, \"sentence\": \"“They say that their biggest priority is making sure that we deal with the deficit in a serious way, but the way they’re behaving is that their only priority is making sure that tax breaks for the wealthiest Americans are protected,” Mr. Obama said on NBC’s “Meet the Press” program.\", \"id\": \"allsides_5881_2522_16_Mr. Obama_234_243\"}\n{\"mention\": \"Mr. Epstein\", \"polarity\": -1, \"from\": 326, \"to\": 337, \"sentence\": \"EPSTEIN'S FINANCIAL TRAIL TRACES BACK TO DEUTSCHE BANK — NYT's David Enrich and Jo Becker: \\\"As Deutsche Bank officials this year scrambled to extricate themselves from a yearslong relationship with Jeffrey Epstein, the wealthy financier charged this month with sex trafficking, they uncovered suspicious transactions in which Mr. Epstein had moved money out of the United States.\", \"id\": \"polusa_v1_79062260_-1_56_Mr. Epstein_327_338\"}\n{\"mention\": \"Chrissy Houlahan\", \"polarity\": 0, \"from\": 47, \"to\": 63, \"sentence\": \"(Photo: Michael K. Dakota, Lebanon Daily News)\\nChrissy Houlahan is one of those candidates.\", \"id\": \"polusa_v1_4173591_-1_52_Democratic candidate Chrissy Houlahan_47_63\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 78, \"to\": 85, \"sentence\": \"But even accounting for the favorable demographics, this is a good result for Clinton.\", \"id\": \"allsides_2455_998_5_Clinton_78_85\"}\n{\"mention\": \"al-Bashir's\", \"polarity\": -1, \"from\": 25, \"to\": 36, \"sentence\": \"Facing genocide charges, al-Bashir's rule has been rocked by civil wars and increasing street demonstrations.\", \"id\": \"polusa_v1_4577470_-1_4_Al-Bashir — who seized power in a 1989 coup—_26_37\"}\n{\"mention\": \"Sessions\", \"polarity\": 0, \"from\": 146, \"to\": 154, \"sentence\": \"FULL COVERAGE: Live updates from the hearing\\nIn his own testimony before the same committee last week, Comey said he deliberately avoided telling Sessions about what he felt was pressure from Trump to drop an investigation into Michael T. Flynn, Trump’s former national security advisor.\", \"id\": \"polusa_v1_55200525_-1_14_Gen. Jeff Sessions_147_155\"}\n{\"mention\": \"Mr. Farage\", \"polarity\": 0, \"from\": 120, \"to\": 130, \"sentence\": \"And I think a lot of Trump voters will be scratching their heads hard and asking, ‘where does this go from here?’” said Mr. Farage Friday morning, speaking on the LBC radio network.\", \"id\": \"polusa_v1_4303807_-1_4_Former UKIP leader Nigel Farage_120_130\"}\n{\"mention\": \"Wilson\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Wilson told WPLG, \\\"Now I didn’t hear the entire conversation, but when I tried to find out what the entire conversation was, she said I just can’t remember everything that he said.\", \"id\": \"polusa_v1_115964269_-1_33_Wilson_1_7\"}\n{\"mention\": \"Powell\", \"polarity\": 0, \"from\": 93, \"to\": 99, \"sentence\": \"I said nothing about servers, basements, domains, Clinton foundation, government employees,” Powell wrote, reiterating that this information was not new, and was detailed in his latest book.\", \"id\": \"allsides_1813_738_8_Colin Powell_93_99\"}\n{\"mention\": \"Jack Lopresti\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"Jack Lopresti MP (Conservative)\\nChairman, APPG on the Kurdistan Region in Iraq\\n• Join the debate – email guardian.letters@theguardian.com\\n• Read more Guardian letters – click here to visit gu.com/letters\", \"id\": \"polusa_v1_39006804_-1_6_Jack Lopresti_1_14\"}\n{\"mention\": \"Margaret\", \"polarity\": -1, \"from\": 18, \"to\": 26, \"sentence\": \"Little by little, Margaret became frail and isolated.\", \"id\": \"polusa_v1_4247544_-1_8_Margaret Lundebjerg_19_27\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 112, \"to\": 115, \"sentence\": \"Her family agreed to help her to file the complaint, which prompted police to arrest the principal, infuriating him and his supporters.\", \"id\": \"polusa_v1_55174544_-1_4_Rafi_112_115\"}\n{\"mention\": \"Sisi\", \"polarity\": -1, \"from\": 34, \"to\": 38, \"sentence\": \"Unlike Trump, Obama never invited Sisi to the White House.\", \"id\": \"polusa_v1_4348444_-1_11_Egyptian President Abdel Fattah al-Sisi_35_39\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 7, \"to\": 12, \"sentence\": \"Unlike Trump, Obama never invited Sisi to the White House.\", \"id\": \"polusa_v1_4348444_-1_11_President Trump_8_13\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 111, \"to\": 114, \"sentence\": \"The opposition has demanded the families minister, Pru Goward, be stood down pending an investigation into why she failed to release the report for more than 18 months after it was delivered.\", \"id\": \"polusa_v1_38959349_-1_14_Kim Jong-un_111_114\"}\n{\"mention\": \"Lewandowski\", \"polarity\": -1, \"from\": 116, \"to\": 127, \"sentence\": \"People close to Trump, including adult children Ivanka, Eric and Donald Jr., also had long-simmering concerns about Lewandowski, who had limited national experience before becoming Trump's campaign chief.\", \"id\": \"allsides_2069_842_18_Corey Lewandowski_116_127\"}\n{\"mention\": \"Mr. Nunes\", \"polarity\": -1, \"from\": 152, \"to\": 161, \"sentence\": \"Representatives Adam B. Schiff of California, the committee’s top Democrat, and Nancy Pelosi of California, the House Democratic leader, suggested that Mr. Nunes, who served on the Trump transition team, was simply too close to the White House to run an independent, thorough inquiry.\", \"id\": \"allsides_1229_491_5_Mr. Nunes_152_161\"}\n{\"mention\": \"McCain\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"McCain reached for her microphone, his head shaking in disagreement.\", \"id\": \"polusa_v1_39072149_-1_29_The Republican senator John McCain_0_6\"}\n{\"mention\": \"Mueller\", \"polarity\": 1, \"from\": 89, \"to\": 96, \"sentence\": \"The source told Fox News that the president's legal team \\\"has tremendous respect for Bob Mueller\\\" and claimed that the two sides \\\"have been working well together.\\\"\", \"id\": \"allsides_809_325_11_special counsel Robert Mueller_89_96\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Obama’s moralizing about avoiding “suspicion and hate” implied, once again, that Americans are bigoted — another attempt to shift blame.\", \"id\": \"allsides_2684_1092_11_Obama_0_5\"}\n{\"mention\": \"Mr. Romney\", \"polarity\": 0, \"from\": 71, \"to\": 81, \"sentence\": \"A moment later, he stopped again, saying, “What do you want me to tell Mr. Romney?”\", \"id\": \"allsides_6298_2708_37_Mitt Romney himself_71_81\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 16, \"to\": 18, \"sentence\": \"A moment later, he stopped again, saying, “What do you want me to tell Mr. Romney?”\", \"id\": \"allsides_6298_2708_37_Mr. Eastwood_16_18\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 80, \"to\": 85, \"sentence\": \"“We are cautiously confident that he will make the right choice,” Brune said of Obama.\", \"id\": \"allsides_4606_1928_12_Obama_80_85\"}\n{\"mention\": \"Governor Romney\", \"polarity\": -1, \"from\": 142, \"to\": 157, \"sentence\": \"“We are shocked that, at a time when the United States of America is confronting the tragic death of one of our diplomatic officers in Libya, Governor Romney would choose to launch a political attack,” said Ben LaBolt, a campaign spokesman, early Wednesday morning.\", \"id\": \"allsides_6243_2686_21_Mr. Romney_142_157\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 123, \"to\": 126, \"sentence\": \"Clinton, whose book What Happened is to be released September 12, told CBS News in an interview the many reasons for which she thinks she lost the election — focusing primarily on the letter from FBI Director James Comey announcing in October the reopening of the investigation into her use of a private email server as secretary of state.\", \"id\": \"allsides_604_241_2_Hillary Clinton_123_126\"}\n{\"mention\": \"Christie's\", \"polarity\": -1, \"from\": 7, \"to\": 17, \"sentence\": \"Before Christie's press conference, the Democratic National Committee called on Christie to give the public more than \\\"his customary bluster and deflection.\\\"\", \"id\": \"allsides_4683_1963_24_Christie_7_17\"}\n{\"mention\": \"Khodorkovsky\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Khodorkovsky spent 10 years in prison on charges seen as punishment for his political ambitions.\", \"id\": \"polusa_v1_4450056_-1_8_Khodorkovsky_1_13\"}\n{\"mention\": \"\\\"Paul\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"\\\"Paul had a fantastic sense of humour, and his family has many memories that will make us smile when we think of him.\", \"id\": \"polusa_v1_17986727_-1_10_\\\"Paul_1_6\"}\n{\"mention\": \"Vladimir Putin\", \"polarity\": 0, \"from\": 38, \"to\": 52, \"sentence\": \"Hide Caption 8 of 14\\nPhotos: The 2017 Vladimir Putin calendar August -- \\\"Without bread it is impossible to live.\", \"id\": \"polusa_v1_4803134_-1_15_Putin_38_52\"}\n{\"mention\": \"Pope Francis\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Pope Francis’ recent comments favoring evolution and the Big Bang Theory led to rampant media coverage claiming that the pontiff is embracing a newfound and “progressive” mentality.\", \"id\": \"allsides_3969_1649_1_Pope Benedict XVI_2_14\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 13, \"to\": 18, \"sentence\": \"In addition, Obama suggested that the poor and middle class shouldn't shoulder the burden of such changes.\", \"id\": \"allsides_5728_2455_22_Obama_13_18\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 92, \"to\": 97, \"sentence\": \"The editorial argues that the only way to hold Bannon in check is through “President Donald Trump’s out-of-control vanity,” which “could become a welcome force for peace” if he feels upstaged by Bannon and reduces his influence.\", \"id\": \"polusa_v1_4291799_-1_12_President Trump_92_97\"}\n{\"mention\": \"Patrick Moore\", \"polarity\": -1, \"from\": 16, \"to\": 29, \"sentence\": \"Mr Trump quoted Patrick Moore, who he claimed was a founder of Greenpeace, as saying: \\\"The whole climate crisis is not only Fake News, it's Fake Science.\\\"\", \"id\": \"polusa_v1_18413587_-1_3_Mr Moore_17_30\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton, as Dunn sees it, couldn't ask for a better opponent than the one she's getting: a braggadocios businessman with a lengthy history of misogynistic comments.\", \"id\": \"allsides_2112_859_31_Hillary Clinton_0_7\"}\n{\"mention\": \"Rachel Martin\", \"polarity\": 0, \"from\": 6, \"to\": 19, \"sentence\": \"NPR's Rachel Martin speaks with Rep.\", \"id\": \"polusa_v1_52900265_-1_2_Rachel Martin_8_21\"}\n{\"mention\": \"Mr. Sheffer\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Mr. Sheffer said his company’s situation was different from that of Carrier, which has profitable operations in Indiana but could make more money in Mexico.\", \"id\": \"allsides_1584_640_47_Mr. Sheffer_0_11\"}\n{\"mention\": \"Daniel\", \"polarity\": 1, \"from\": 111, \"to\": 117, \"sentence\": \"“He’ll be bringing his deep Rolodex and knowledge of Washington’s power players to a beat that is both vintage Daniel -- harnessing his unique knack for finding out who in D.C. is doing what, and why – and vintage POLITICO.\", \"id\": \"polusa_v1_79078710_-1_71_Daniel_112_118\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 0, \"from\": 217, \"to\": 232, \"sentence\": \"WASHINGTON — After all the ways that this year’s presidential election has made history, Donald J. Trump found a new line to cross on Wednesday, when he said at a news conference that Russia should hack his opponent, Hillary Clinton.\", \"id\": \"allsides_1954_793_1_Hillary Clinton_219_234\"}\n{\"mention\": \"Williams\", \"polarity\": 0, \"from\": 53, \"to\": 61, \"sentence\": \"Last week, \\\"NBC Nightly News\\\" ran a segment in which Williams took veteran Tim Terpak to a New York Rangers game, at which an announcer hailed Terpak as \\\"responsible for the safety of Brian Williams and his NBC News team after their Chinook helicopter was hit and crippled by enemy fire” during the 2003 invasion.\", \"id\": \"allsides_3626_1495_2_NBC News anchor Brian Williams_53_61\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton toured factories to promote her proposals to revitalize American manufacturing.\", \"id\": \"allsides_2234_909_24_front-runner Hillary Clinton_0_7\"}\n{\"mention\": \"the company\", \"polarity\": 0, \"from\": 40, \"to\": 51, \"sentence\": \"Police initially said Kroll was 35, but the company confirmed he was 34 years old.\", \"id\": \"polusa_v1_113869382_-1_20_Twitter_41_52\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 32, \"to\": 37, \"sentence\": \"That launch came shortly before Trump's first meeting with Chinese leader Xi Jinping.\", \"id\": \"allsides_1164_465_14_President Trump_32_37\"}\n{\"mention\": \"Dzhokhar Tsarnaev\", \"polarity\": -1, \"from\": 0, \"to\": 17, \"sentence\": \"Dzhokhar Tsarnaev, Boston Marathon Bombing Suspect, Reportedly Awake And Responding To Questions In Writing\", \"id\": \"allsides_5488_2342_0_Dzhokhar Tsarnaev_0_17\"}\n{\"mention\": \"MARTIN\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"MARTIN: Has any of that changed in recent years, as there's been more focus on it?\", \"id\": \"polusa_v1_52915276_-1_56_MARTIN_0_7\"}\n{\"mention\": \"Spencer\", \"polarity\": 0, \"from\": 51, \"to\": 58, \"sentence\": \"The city's health commissioner, Mary Bassett, said Spencer's fiancee and two friends had been quarantined but showed no symptoms.\", \"id\": \"allsides_4010_1665_20_Spencer_51_58\"}\n{\"mention\": \"Fairfax\", \"polarity\": 0, \"from\": 36, \"to\": 43, \"sentence\": \"As a part-time lieutenant governor, Fairfax keeps a small team of aides working on his behalf in Richmond.\", \"id\": \"polusa_v1_113848229_-1_6_Justin Fairfax_36_43\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She said she would seek Garcia’s endorsement and said she wouldn't ask for Emanuel’s support.\", \"id\": \"polusa_v1_59512551_-1_12_Gutierrez_1_4\"}\n{\"mention\": \"\\\" Rove\", \"polarity\": 0, \"from\": 77, \"to\": 83, \"sentence\": \"\\\"Please don't lecture us about [how Trump] hasn't done anything in two years,\\\" Rove added.\", \"id\": \"polusa_v1_4475554_-1_4_Fox News political contributor Karl Rove_78_84\"}\n{\"mention\": \"Brockway\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Brockway, who is charged with felony assault on a minor, is a registered violent offender after being convicted of a 2010 charge of assault with a weapon.\", \"id\": \"polusa_v1_4177419_-1_23_Brockway_0_9\"}\n{\"mention\": \"Ryan\", \"polarity\": 0, \"from\": 67, \"to\": 71, \"sentence\": \"The agreement, which Trump reportedly sprang on House Speaker Paul Ryan (R-Wis.) and Senate Majority Leader Mitch McConnell (R-Ky.), extended government spending and the debt limit for a far shorter period than Republican leaders wanted.\", \"id\": \"polusa_v1_3908487_-1_3_Ryan_68_72\"}\n{\"mention\": \"Almodovar\", \"polarity\": 0, \"from\": 24, \"to\": 33, \"sentence\": \"I’m just shocked,” said Almodovar.\", \"id\": \"polusa_v1_4495306_-1_8_Manuel Almodovar_24_33\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said Chairman of the Joint Chiefs of Staff Gen Joseph Dunford would continue negotiations with his Turkish counterparts this week to seek protection for 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to Mr Corbyn's apparently supportive message to the creator of an allegedly anti-Semitic mural in 2012. and his attendance at \\\"pro-Hezbollah rallies\\\".\", \"id\": \"polusa_v1_18490916_-1_8_Jeremy Corbyn_28_39\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 89, \"to\": 101, \"sentence\": \"Asked for a comment, it would only note that in a Quinnipiac University poll last month, Mrs. Clinton led her closest opponent, Mr. Sanders, by 46 points among voters who consider themselves “very liberal.”\", \"id\": \"allsides_3234_1328_48_Mrs. Clinton_89_101\"}\n{\"mention\": \"Escamilla\", \"polarity\": -1, \"from\": 41, \"to\": 50, \"sentence\": \"When asked about Ferguson’s finding that Escamilla’s explanations had been disingenuous and implausible, Johnson replied that “nobody deserves special treatment.”\", \"id\": \"polusa_v1_59556386_-1_33_Anthony Escamilla_41_50\"}\n{\"mention\": \"Ferguson\", \"polarity\": 0, \"from\": 17, \"to\": 25, \"sentence\": \"When asked about Ferguson’s finding that Escamilla’s explanations had been disingenuous and implausible, Johnson replied that “nobody deserves special treatment.”\", \"id\": \"polusa_v1_59556386_-1_33_Ferguson_17_25\"}\n{\"mention\": \"Mrs May\", \"polarity\": -1, \"from\": 45, \"to\": 52, \"sentence\": \"For Conservatives who want to soften Brexit, Mrs May’s game plan has been to suck out the oxygen of parliamentary debate.\", \"id\": \"polusa_v1_38894676_-1_22_Mrs May_46_53\"}\n{\"mention\": \"Castile\", \"polarity\": -1, \"from\": 92, \"to\": 99, \"sentence\": \"The fatal encounter\\nDuring their brief encounter in Falcon Heights, Minnesota, Yanez warned Castile not to reach for the firearm.\", \"id\": \"polusa_v1_4900445_-1_31_Philando Castile's_93_100\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 73, \"to\": 80, \"sentence\": \"Sanders and O'Malley declined to make the same promise, and Sanders said Clinton was abandoning the Democratic Party's social legacy, \\\"disagreeing with FDR on Social Security, disagreeing with LBJ on Medicare\\\" and how to fund large social programs.\", \"id\": \"allsides_2666_1085_68_Hillary Clinton's_73_80\"}\n{\"mention\": \"O'Malley\", \"polarity\": -1, \"from\": 12, \"to\": 20, \"sentence\": \"Sanders and O'Malley declined to make the same promise, and Sanders said Clinton was abandoning the Democratic Party's social legacy, \\\"disagreeing with FDR on Social Security, disagreeing with LBJ on Medicare\\\" and how to fund large social programs.\", \"id\": \"allsides_2666_1085_68_O'Malley_12_20\"}\n{\"mention\": \"Bamberger's\", \"polarity\": 0, \"from\": 153, \"to\": 164, \"sentence\": \"\\\"At the Louisville political rally at issue in this lawsuit, Trump and/or the Trump Campaign urged people attending the rally to remove the protesters,\\\" Bamberger's lawyers wrote.\", \"id\": \"polusa_v1_59599129_-1_25_Bamberger_154_165\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 66, \"to\": 71, \"sentence\": \"When asked if he believes marijuana is less harmful than alcohol, Obama said it is less damaging \\\"in terms of its impact on the individual consumer.\\\"\", \"id\": \"allsides_4648_1948_5_President Barack Obama_66_71\"}\n{\"mention\": \"Cuccinelli\", \"polarity\": -1, \"from\": 224, \"to\": 234, \"sentence\": \"( VIDEO: Coverage & POLITICO analysis on Election Day 2013) When President Barack Obama crossed the Potomac for McAuliffe on Sunday, he glaringly avoided even mentioning his signature accomplishment — trying instead to link Cuccinelli with the federal government shutdown.\", \"id\": \"allsides_4880_2053_9_Cuccinelli_224_234\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 22, \"to\": 27, \"sentence\": \"Republicans criticize Obama over call for repeal of 2001 use of force law\", \"id\": \"allsides_5367_2282_0_Obama_22_27\"}\n{\"mention\": \"Papadopoulos\", \"polarity\": 0, \"from\": 52, \"to\": 64, \"sentence\": \"“I know of no questions that have been asked about” Papadopoulos, he 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city's trains and buses — key tools to fight climate change.\", \"id\": \"polusa_v1_52864520_-1_35_London Mayor Sadiq Khan_5_7\"}\n{\"mention\": \"Ms. Hicks\", \"polarity\": 1, \"from\": 13, \"to\": 22, \"sentence\": \"In her role, Ms. Hicks will oversee corporate communications for Fox and work closely with both Co-Chairman and Chief Executive Lachlan Murdoch and Viet Dinh, chief legal and policy officer, to whom she will report.\", \"id\": \"polusa_v1_55487961_-1_8_Former White House Communications Director Hope Hicks_14_23\"}\n{\"mention\": \"Rubio\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Rubio was acceptable to all wings of the Republican Party even if he was the first choice of few.\", \"id\": \"allsides_2402_974_15_Marco Rubio_0_5\"}\n{\"mention\": \"Mr. Sabato\", \"polarity\": 0, \"from\": 30, \"to\": 40, \"sentence\": \"It’s all about Mark Sanford,” Mr. Sabato said.\", \"id\": \"allsides_5430_2313_31_Mr. Sabato_30_40\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 61, \"to\": 66, \"sentence\": \"Surveys since July have shown everything from an eight-point Obama lead to a five-point advantage for Romney.\", \"id\": \"allsides_6216_2670_42_Obama_61_66\"}\n{\"mention\": \"They\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"They had only a handful of brief exchanges before the 2012 election, and their campaign interactions were largely confined to the three presidential debates.\", \"id\": \"allsides_5982_2565_8_Obama and Romney's meeting_0_4\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 115, \"to\": 118, \"sentence\": \"The report also includes statements from Givens and another woman who was there that night, Yolonda Whitaker, said she saw Slager stun Givens \\\"for no reason.\\\"\", \"id\": \"allsides_3373_1391_67_Brown_115_118\"}\n{\"mention\": \"Givens\", \"polarity\": 0, \"from\": 41, \"to\": 47, \"sentence\": \"The report also includes statements from Givens and another woman who was there that night, Yolonda Whitaker, said she saw Slager stun Givens \\\"for no reason.\\\"\", \"id\": \"allsides_3373_1391_67_Mario Givens_41_47\"}\n{\"mention\": \"Gavin Newsom\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Gavin Newsom visited some of the victims and their families.\", \"id\": \"polusa_v1_4479448_-1_22_Gavin Newsom_0_12\"}\n{\"mention\": \"Dana Perino\", \"polarity\": 0, \"from\": 35, \"to\": 46, \"sentence\": \"Click here for more information on Dana Perino.\", \"id\": \"allsides_2729_1110_19_Dana Perino_35_46\"}\n{\"mention\": \"Mueller\", \"polarity\": -1, \"from\": 80, \"to\": 87, \"sentence\": \"Sean Hannity: New York Times 'trying to distract' with report on Trump ordering Mueller's ouster\", \"id\": \"allsides_39_14_0_Mueller_80_87\"}\n{\"mention\": \"Mueller\", \"polarity\": 1, \"from\": 17, \"to\": 24, \"sentence\": \"The selection of Mueller, a former FBI director himself with a reputation for integrity and strong bipartisan credentials, to lead the investigation received applause on Capitol Hill.\", \"id\": \"allsides_405_162_32_Donald J. 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Roosevelt\", \"polarity\": 1, \"from\": 65, \"to\": 86, \"sentence\": \"Standing on a platform set in the middle of a grassy memorial to Franklin D. Roosevelt on the East River island named after him, Mrs. Clinton invoked his legacy.\", \"id\": \"allsides_3126_1283_10_Franklin D. Roosevelt_65_86\"}\n{\"mention\": \"Zinke\", \"polarity\": 0, \"from\": 31, \"to\": 36, \"sentence\": \"Secretary of the Interior Ryan Zinke visits Bunkerville, Nev. to discuss the future of Gold Butte and other local land issues Sunday, July 30, 2017.\", \"id\": \"polusa_v1_4217954_-1_2_Interior Secretary Ryan Zinke\\nZinke’s trip to Nevada_33_38\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 44, \"to\": 46, \"sentence\": \"Sweat was sentenced to life in prison after he and another man killed Kevin Tarsia, a Broome County, New York Sheriff's Deputy, firing 15 rounds into him after Sweat broke into a Pennsylvania house and stole rifles and handguns.\", \"id\": \"allsides_3134_1286_48_Matt_44_46\"}\n{\"mention\": \"Epps\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Epps was recently tapped to play the lead role in the forthcoming Lee Daniels-directed bio drama, Richard Pryor: Is It Something I Said?\", \"id\": \"polusa_v1_4338380_-1_21_Comedian Mike Epps_0_5\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Romney arguably needed a much more dismal reading in order to crank up the heat on his closing argument that Obama has failed miserably on the economy and must be replaced.\", \"id\": \"allsides_6073_2607_15_Obama_0_6\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 18, \"to\": 21, \"sentence\": \"Supporters credit him with providing Ecuador political and economic stability after a tumultuous period in the nation's history.\", \"id\": \"polusa_v1_4564911_-1_12_Balda_18_21\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 20, \"to\": 22, \"sentence\": \"“I feel jacked up,” he said.\", \"id\": \"allsides_694_279_3_Bannon_20_22\"}\n{\"mention\": \"Lightfoot\", \"polarity\": 1, \"from\": 100, \"to\": 109, \"sentence\": \"As we explained in our March 15 endorsement for the runoff election, former federal prosecutor Lori Lightfoot is best positioned to carry out that mandate — for a safer city, a cleaner City Council, a stronger school system and a more accountable government.\", \"id\": \"polusa_v1_59560876_-1_3_Lightfoot_101_110\"}\n{\"mention\": \"Hagel\", \"polarity\": -1, \"from\": 58, \"to\": 63, \"sentence\": \"But they also raised serious and recurring concerns about Hagel's record of past statements and votes on everything from Israel to Iran to nuclear weapons.\", \"id\": \"allsides_5688_2434_6_Hagel_58_63\"}\n{\"mention\": \"Ginsburg\", \"polarity\": -1, \"from\": 24, \"to\": 32, \"sentence\": \"Some critics argue that Ginsburg’s words are insufficient given her refusal to retire from the bench under Barack Obama.\", \"id\": \"polusa_v1_39116943_-1_37_Ginsburg_25_33\"}\n{\"mention\": \"Coons\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Coons added that he has shared with Grassley \\\"a few sections of his amendment about which I have some concerns\\\" and that \\\"I'm optimistic that we can resolve this by Thursday\\\" to help the bill get through a committee markup.\", \"id\": \"polusa_v1_79081727_-1_12_\\\" Coons_0_6\"}\n{\"mention\": \"Ryan\", \"polarity\": -1, \"from\": 8, \"to\": 12, \"sentence\": \"Speaker Ryan’s globalist agenda stands in clear opposition to the will of the Republican electorate, who want safe communities, immigration control, smart trade deals, and leaders who put the needs of the American people first,” he said.\", \"id\": \"allsides_1928_784_23_Ryan_8_12\"}\n{\"mention\": \"Biden\", \"polarity\": 1, \"from\": 113, \"to\": 118, \"sentence\": \"(Yuri Gripas/Pool Photo via AP) A crowd of 1,000 gathered at St. Anthony of Padua Roman Catholic Church to mourn Biden, who served as Delaware's attorney general from 2007 to 2015.\", \"id\": \"allsides_3158_1295_20_\\\" Hunter Biden_113_118\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": -1, \"from\": 222, \"to\": 231, \"sentence\": \"A decision to maintain the DACA program would be a reversal from Mr. Trump’s anti-immigrant language during the campaign and would disappoint some of the president’s most ardent supporters, who view the program started by Mr. Obama as an illegal grant of amnesty.\", \"id\": \"allsides_949_382_16_President Barack Obama’s_222_231\"}\n{\"mention\": \"David Frum, staff writer at The Atlantic and former speech writer for George W. Bush\", \"polarity\": 0, \"from\": 23, \"to\": 107, \"sentence\": \"Rachel Martin talks to David Frum, staff writer at The Atlantic and former speech writer for George W. Bush, about his essay proposing new limits on immigration.\", \"id\": \"polusa_v1_52875102_-1_1_David Frum, staff writer at The Atlantic and former speech writer for George W. Bush_25_109\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 4, \"to\": 6, \"sentence\": \"But he warned that the investigation was still ongoing and the terrorist threat level remains at \\\"critical,\\\" meaning another attack is highly likely.\", \"id\": \"allsides_590_235_4_\\\" Deputy Assistant Police Commissioner Neil Basu_4_6\"}\n{\"mention\": \"Donohue\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Donohue’s letter, dated August 1, makes reference to a recent interview of Hulse conducted by New York Times columnist Maureen Dowd concerning Hulse’s book Confirmation Bias: Inside Washington’s War Over the Supreme Court, From Scalia’s Death to Justice Kavanaugh.\", \"id\": \"polusa_v1_4344995_-1_4_Catholic League president William Donohue_1_8\"}\n{\"mention\": \"DeSantis\", \"polarity\": 0, \"from\": 88, \"to\": 96, \"sentence\": \"The new Broward County Supervisor of Elections could be appointed by Governor-elect Ron DeSantis – depending on when exactly Brenda Snipes’ resignation goes into effect.\", \"id\": \"polusa_v1_4442797_-1_2_DeSantis_90_98\"}\n{\"mention\": \"Lee\", \"polarity\": 0, \"from\": 64, \"to\": 67, \"sentence\": \"And if they choose to take those statues down, fine,\\\" Robert E. Lee V told CNN.\", \"id\": \"allsides_699_282_4_Robert E. Lee's_64_67\"}\n{\"mention\": \"Walker\", \"polarity\": 1, \"from\": 6, \"to\": 12, \"sentence\": \"Scott Walker, a conservative Republican, put forward a surprisingly liberal budget Wednesday that includes a huge boost in funding for schools, sizable tuition cuts for college students and increased tax breaks for the working poor.\", \"id\": \"polusa_v1_59531959_-1_2_Walker_6_12\"}\n{\"mention\": \"Reid\", \"polarity\": 0, \"from\": 109, \"to\": 113, \"sentence\": \"Many in the Senate privately expected that this go-round would be yet another example of saber rattling, but Reid said pressure was increasing within his own party to change the rules.\", \"id\": \"allsides_4827_2030_19_Reid_109_113\"}\n{\"mention\": \"Feinstein\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Feinstein has not said if she will seek a fifth term in 2018.\", \"id\": \"polusa_v1_79079669_-1_13_Dianne Feinstein in the Senate_1_10\"}\n{\"mention\": \"Ishler\", \"polarity\": 0, \"from\": 9, \"to\": 15, \"sentence\": \"In fact, Ishler said, officials later determined Comcast did not fully understand exactly where their cables in the area were located.\", \"id\": \"polusa_v1_59587480_-1_9_City Administrator Troy Ishler_9_15\"}\n{\"mention\": \"Mueller\", \"polarity\": -1, \"from\": 5, \"to\": 12, \"sentence\": \"\\\"And Mueller has been using the FBI as a political weapon.\", \"id\": \"polusa_v1_116918257_-1_30_special counsel Robert Mueller_5_12\"}\n{\"mention\": \"McConnell\", \"polarity\": -1, \"from\": 61, \"to\": 70, \"sentence\": \"Senate Minority Leader Chuck Schumer, D-N.Y., said, \\\"Senator McConnell would have the world believe that his hands are tied.\", \"id\": \"allsides_1206_481_12_McConnell_61_70\"}\n{\"mention\": \"Prime Minister Abe\", \"polarity\": 1, \"from\": 21, \"to\": 39, \"sentence\": \"\\\"President Trump and Prime Minister Abe will explore ways to expand fair and reciprocal trade and investment ties between the United States and Japan, two of the world's wealthiest and most innovative economies,\\\" the White House said.\", \"id\": \"polusa_v1_4861086_-1_5_Shinzo Abe_22_40\"}\n{\"mention\": \"President-elect Donald Trump\", \"polarity\": 0, \"from\": 0, \"to\": 28, \"sentence\": \"President-elect Donald Trump has asked freshman Montana Rep.\", \"id\": \"allsides_1546_622_2_President-elect Donald Trump_0_30\"}\n{\"mention\": \"Salman\", \"polarity\": -1, \"from\": 50, \"to\": 56, \"sentence\": \"Her indictment alleges, without elaborating, that Salman \\\"did knowingly aid and abet\\\" her husband from at least April onward and that after the shooting, she \\\"did knowingly mislead\\\" investigators.\", \"id\": \"polusa_v1_4702976_-1_19_Noor Salman_51_57\"}\n{\"mention\": \"Clarke\", \"polarity\": 0, \"from\": 9, \"to\": 15, \"sentence\": \"\\\"Sheriff Clarke has yet to respond to the substance of our story,\\\" he wrote.\", \"id\": \"polusa_v1_115988427_-1_21_Clarke_10_16\"}\n{\"mention\": \"Cohen\", \"polarity\": -1, \"from\": 32, \"to\": 37, \"sentence\": \"Daniels is also suing Trump and Cohen for defamation.\", \"id\": \"polusa_v1_115996851_-1_14_Cohen_33_38\"}\n{\"mention\": \"Mr. Faqey\", \"polarity\": -1, \"from\": 68, \"to\": 77, \"sentence\": \"The court heard extracts from alleged online chat logs, which claim Mr. Faqey wanted to obtain automatic weapons and commit a terrorist attack on Jewish people in north London.\", \"id\": \"polusa_v1_4327831_-1_10_Aweys Faqey_69_78\"}\n{\"mention\": \"Arpaio\", \"polarity\": -1, \"from\": 11, \"to\": 17, \"sentence\": \"Otherwise, Arpaio doesn’t demonstrate much interest in policy—trade or the deficit or health care—aside from the broad strokes of the Trump agenda.\", \"id\": \"polusa_v1_79065322_-1_84_Arpaio_12_18\"}\n{\"mention\": \"Monahan\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Monahan was wearing her uniform, and Needham was wearing an ivory dress and jacket and matching hat.\", \"id\": \"allsides_5952_2552_17_Monahan_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 30, \"to\": 37, \"sentence\": \"Entering Tuesday's primaries, Clinton had won more contests than Sanders, 28-23.\", \"id\": \"allsides_2110_858_41_Clinton_30_37\"}\n{\"mention\": \"Only Governors Johnson and Weld\", \"polarity\": 1, \"from\": 0, \"to\": 31, \"sentence\": \"Only Governors Johnson and Weld have consistently represented the middle ground.\", \"id\": \"allsides_2143_872_21_Only Governors Johnson and Weld_0_31\"}\n{\"mention\": \"Liberman\", \"polarity\": 0, \"from\": 12, \"to\": 20, \"sentence\": \"In Chicago, Liberman and McIntosh, who talked frequently by phone with Calabresi at Yale, started a similar student group.\", \"id\": \"polusa_v1_79066836_-1_87_Lee Liberman_13_21\"}\n{\"mention\": \"McIntosh\", \"polarity\": 0, \"from\": 25, \"to\": 33, \"sentence\": \"In Chicago, Liberman and McIntosh, who talked frequently by phone with Calabresi at Yale, started a similar student group.\", \"id\": \"polusa_v1_79066836_-1_87_McIntosh_26_34\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 36, \"to\": 41, \"sentence\": \"The KCNA had previously referred to Obama as a “wicked black monkey” and a “crossbreed,” the Washington Post noted at the time.\", \"id\": \"polusa_v1_4360651_-1_54_President Barack Obama_36_41\"}\n{\"mention\": \"Liston\", \"polarity\": 0, \"from\": 18, \"to\": 24, \"sentence\": \"After six rounds, Liston was completely spent.\", \"id\": \"allsides_2118_862_12_Liston_18_24\"}\n{\"mention\": \"Brahmadev Yadav\", \"polarity\": 0, \"from\": 48, \"to\": 63, \"sentence\": \"Image copyright Samiratmaj Mishra Image caption Brahmadev Yadav lost both his newborn children at the Baba Raghav Das Medical College\\nThe first deaths from the hospital were reported on 7 August, but the news made it to national headlines only four days later when the death toll began to rapidly mount.\", \"id\": \"polusa_v1_18153883_-1_15_Mr Yadav_49_64\"}\n{\"mention\": \"Kelley\", \"polarity\": -1, \"from\": 36, \"to\": 42, \"sentence\": \"“Initial information indicates that Kelley’s domestic violence offense was not entered into the National Criminal Information Center database by the Hollomon Air Force Base Office of Special Investigations,” the USAF said in a statement.\", \"id\": \"allsides_361_145_11_Devin Patrick Kelley_36_42\"}\n{\"mention\": \"Jacob Zuma's\", \"polarity\": -1, \"from\": 47, \"to\": 59, \"sentence\": \"South Africa's parliament has merely postponed Jacob Zuma's day of reckoning Read more\\nThe ballot counting was accompanied by scenes of singing and dancing on both sides of the assembly, as rival parties sought to project confidence.\", \"id\": \"polusa_v1_39068430_-1_4_Jacob Zuma_48_60\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 111, \"to\": 118, \"sentence\": \"During a New York Times interview in July, Trump responded to a question by reporter Michael Schmidt asking if Mueller’s focus on the Trump family finances would be 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Changes His Stance On Roy Moore [VIDEO]) Moore has now been accused of sexually assaulting nine women, many of whom were minors at the time.\", \"id\": \"allsides_248_101_20_Roy Moore_42_51\"}\n{\"mention\": \"Mr. Sanders\", \"polarity\": 1, \"from\": 19, \"to\": 30, \"sentence\": \"At the university, Mr. Sanders highlighted items from his far-left agenda that resonate with students and young voters, including free tuition at public colleges and universities, raising the federal minimum wage to $15 per hour and criminal justice reforms to keep drug offenders out of jail and stop police brutality in black communities.\", \"id\": \"allsides_2459_999_9_Bernie Sanders_19_30\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He admitted, “Sometimes my Irish comes out and in my tweets” but said that as the son of an immigrant, he could not stand to watch Trump “trashing the reputation of his country worldwide” without being criticized.\", \"id\": \"polusa_v1_4339843_-1_11_Former CIA Director John Brennan_1_3\"}\n{\"mention\": \"Boehner\", \"polarity\": 0, \"from\": 3, \"to\": 10, \"sentence\": \"So Boehner and the other leaders changed that CR date, and thought they could move forward.\", \"id\": \"allsides_4949_2085_28_Boehner_3_10\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 57, \"to\": 62, \"sentence\": \"The same internal conflict and incoherence which allowed Trump to capture the nomination has prevented congressional Republicans from passing any legislation which made sense — or any legislation at all.\", \"id\": \"polusa_v1_3966823_-1_27_President Trump_58_63\"}\n{\"mention\": \"Mr. Slavitt\", \"polarity\": 0, \"from\": 57, \"to\": 68, \"sentence\": \"These were overwhelmed by people trying to use the site, Mr. Slavitt said.\", \"id\": \"allsides_4923_2073_13_Mr. Slavitt_57_68\"}\n{\"mention\": \"the Clinton\", \"polarity\": -1, \"from\": 73, \"to\": 84, \"sentence\": \"“The Trump Justice Department needs to 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Trump (@realDonaldTrump) August 31, 2016 Pena Nieto’s office says in its own tweet that the two men will meet in private Wednesday.\", \"id\": \"allsides_1852_754_6_President Enrique Pena Nieto_53_63\"}\n{\"mention\": \"Schatz\", \"polarity\": 1, \"from\": 51, \"to\": 57, \"sentence\": \"Hanabusa was a stalwart for Hillary Clinton, while Schatz was an early booster for Obama.\", \"id\": \"allsides_4699_1973_77_Brian Schatz_51_57\"}\n{\"mention\": \"Assange\", \"polarity\": 0, \"from\": 1, \"to\": 8, \"sentence\": \"#Assange: Regarding upcoming publications...\", \"id\": \"allsides_1757_715_8_Assange_1_8\"}\n{\"mention\": \"Environment Secretary Michael Gove\", \"polarity\": 1, \"from\": 0, \"to\": 34, \"sentence\": \"Environment Secretary Michael Gove gave the assurance during a visit to the Antrim Show.\", \"id\": \"polusa_v1_18099022_-1_1_Environment Secretary Michael Gove_0_36\"}\n{\"mention\": \"The federal Labor MP Emma Husar\", \"polarity\": 1, \"from\": 108, \"to\": 139, \"sentence\": \"BuzzFeed barrister unsuccessfully argues article by journalist Alice Workman did not contain the imputation\\nThe federal Labor MP Emma Husar has had an early victory in her defamation case against BuzzFeed, with a judge ruling an article published by the news website in July was capable of conveying that she was a “slut”.\", \"id\": \"polusa_v1_39005145_-1_2_The federal Labor MP Emma Husar_110_141\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 61, \"to\": 67, \"sentence\": \"Other speakers, but not Michelle Obama, took direct shots at Romney on Tuesday, casting him as an out-of-touch wealthy politician.\", \"id\": \"allsides_6279_2699_29_Romney_61_67\"}\n{\"mention\": \"Ahn\", \"polarity\": 1, \"from\": 67, \"to\": 70, \"sentence\": \"Of the 1,989 ballots counted since Friday, more than 1,800 went to Ahn.\", \"id\": \"polusa_v1_55187810_-1_3_Robert Lee Ahn_68_71\"}\n{\"mention\": \"author Ronald Kessler\", \"polarity\": 0, \"from\": 86, \"to\": 107, \"sentence\": \"Story Continued Below\\nIn an interview Sunday morning with CNN’s “State of the Union,” author Ronald Kessler said Conway is the top source of leaks inside the Trump administration, recalling an on the record interview with her in which she “said the most mean, cutting and obviously untrue things about Reince” Priebus, the former White House chief of staff who was fired last summer.\", \"id\": \"polusa_v1_79088402_-1_7_author Ronald Kessler_87_108\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 158, \"to\": 163, \"sentence\": \"Story Continued Below\\nIn an interview Sunday morning with CNN’s “State of the Union,” author Ronald Kessler said Conway is the top source of leaks inside the Trump administration, recalling an on the record interview with her in which she “said the most mean, cutting and obviously untrue things about Reince” Priebus, the former White House chief of staff who was fired last summer.\", \"id\": \"polusa_v1_79088402_-1_7_Ivanka Trump_159_164\"}\n{\"mention\": \"Bill de Blasio\", \"polarity\": -1, \"from\": 10, \"to\": 24, \"sentence\": \"NYC Mayor Bill de Blasio So 'Frustrated' with Panhandlers He Wants to Make It Illegal\", \"id\": \"polusa_v1_4294957_-1_0_New York City Mayor Bill de Blasio_10_24\"}\n{\"mention\": \"Donald Trump's\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"Donald Trump's front-runner status could be in jeopardy, with the latest polls showing Sen.\", \"id\": \"allsides_2337_949_4_Donald Trump's_0_14\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 4, \"to\": 9, \"sentence\": \"The Trump campaign has already tweaked its operations ahead of the New York primary.\", \"id\": \"allsides_2297_934_37_Donald Trump_4_9\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton campaign officials have described the plan as an effort to encourage long-term economic growth through a sliding tax rate scale – taxing short-term investments at higher rates and longer-term investments as lower rates.\", \"id\": \"allsides_3017_1234_12_Clinton_0_7\"}\n{\"mention\": \"Mr. Orr\", \"polarity\": -1, \"from\": 93, \"to\": 100, \"sentence\": \"The decision to go to court signaled a breakdown after weeks of tense negotiations, in which Mr. Orr had been trying to persuade creditors to accept pennies on the dollar and unions to accept cuts in benefits.\", \"id\": \"allsides_5217_2209_22_Mr. Orr_93_100\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 83, \"to\": 90, \"sentence\": \"| POLITICO Illustration/Getty Images Nerdcast Nerdcast: Connecting the dots of the Mueller investigation\\nIt’s time for a new episode of Nerdcast, POLITICO’s podcast on the White House and politics.\", \"id\": \"polusa_v1_79070283_-1_3_Special counsel Robert Mueller_83_90\"}\n{\"mention\": \"Portnoy\", \"polarity\": 0, \"from\": 132, \"to\": 139, \"sentence\": \"\\\"Those are two issues where, working in concert, the president and the Democrats in 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\"polarity\": 1, \"from\": 31, \"to\": 38, \"sentence\": \"\\\\- Twice as many voters expect Clinton to win as think Trump will (64-26 percent).\", \"id\": \"allsides_1691_689_48_Clinton_31_38\"}\n{\"mention\": \"Mr Sharif\", \"polarity\": -1, \"from\": 42, \"to\": 51, \"sentence\": \"But allegations of corruption have dogged Mr Sharif since the 1980s.\", \"id\": \"polusa_v1_18511712_-1_15_ousted Sharif_43_52\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 19, \"to\": 21, \"sentence\": \"It is just funny,” he said.\", \"id\": \"polusa_v1_4347724_-1_15_Florian Philippot_19_21\"}\n{\"mention\": \"Boehner\", \"polarity\": 0, \"from\": 35, \"to\": 42, \"sentence\": \"Jones said he hasn't yet spoken to Boehner.\", \"id\": \"allsides_5969_2559_27_Boehner_35_42\"}\n{\"mention\": \"Jones\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Jones said he hasn't yet spoken to Boehner.\", \"id\": \"allsides_5969_2559_27_Jones_0_5\"}\n{\"mention\": \"LaPierre\", \"polarity\": 0, 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\"polarity\": -1, \"from\": 53, \"to\": 58, \"sentence\": \"There remain very good reasons to be concerned about Trump’s respect for liberties he so often scorned on the campaign trail.\", \"id\": \"allsides_1396_561_37_Donald Trump_53_58\"}\n{\"mention\": \"her\", \"polarity\": -1, \"from\": 50, \"to\": 53, \"sentence\": \"However, the hormonal coil \\\"didn't sit well\\\" with her, and she now wants to have it removed.\", \"id\": \"polusa_v1_18339963_-1_38_Ms Halil_50_53\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 23, \"to\": 30, \"sentence\": \"By Obama’s assessment, Clinton performed “wonderfully under really tough circumstances.”\", \"id\": \"allsides_1502_606_19_Clinton_23_30\"}\n{\"mention\": \"McCain\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"McCain, a former Navy pilot, was held as a prisoner of war in Vietnam for more than five years.\", \"id\": \"polusa_v1_59514229_-1_6_John McCain_1_7\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 0, 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But momentum in recent days shifted to Mr. Sanford when he got a boost from several high-profile Republican endorsements, including Mr. Scott, Sen.\", \"id\": \"allsides_5430_2313_18_Mr. Sanford_217_228\"}\n{\"mention\": \"Biden\", \"polarity\": -1, \"from\": 28, \"to\": 33, \"sentence\": \"During a Sunday fundraiser, Biden said the mass shootings a day earlier took place in “Houston” and “Michigan,” instead of the actual locations in El Paso, Texas, and Dayton, Ohio.\", \"id\": \"polusa_v1_4309810_-1_17_Joe Biden_29_34\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 79, \"to\": 84, \"sentence\": \"The second hour of MSNBC’s “Morning Joe” started with a lengthy interview with Trump.\", \"id\": \"allsides_3032_1240_3_Donald Trump_79_84\"}\n{\"mention\": \"Senate Majority Leader Mitch McConnell\", \"polarity\": 0, \"from\": 0, \"to\": 38, \"sentence\": \"Senate Majority Leader Mitch McConnell said Monday that he doesn't believe that most news is \\\"fake news,\\\" a view that 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Estes’ campaign could not be reached for comment.\", \"id\": \"polusa_v1_116013018_-1_14_Ron Estes_117_126\"}\n{\"mention\": \"Brannon\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Brannon campaigned with Sen.\", \"id\": \"allsides_4457_1863_25_Tea party-aligned obstetrician Greg Brannon_0_7\"}\n{\"mention\": \"Poe\", \"polarity\": 0, \"from\": 91, \"to\": 94, \"sentence\": \"To have her now say she doesn't support our right to marry is offensive to say the least,\\\" Poe wrote.\", \"id\": \"allsides_4841_2036_10_Poe_91_94\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 98, \"to\": 103, \"sentence\": \"But some observers suggested it was tone-deaf for Sanders to insinuate that he could improve upon Obama's efforts to address racism and racial inequality at all.\", \"id\": \"allsides_2495_1015_21_Obama_98_103\"}\n{\"mention\": \"Cox\", \"polarity\": 0, \"from\": 95, \"to\": 98, \"sentence\": \"“It is my opinion that you are a key conspirator in this scheme to defraud the United States,” Cox told Schmidt in court.\", \"id\": \"polusa_v1_39150634_-1_5_Sean Cox_95_98\"}\n{\"mention\": \"Schmidt\", \"polarity\": -1, \"from\": 104, \"to\": 111, \"sentence\": \"“It is my opinion that you are a key conspirator in this scheme to defraud the United States,” Cox told Schmidt in court.\", \"id\": \"polusa_v1_39150634_-1_5_Schmidt_104_111\"}\n{\"mention\": \"Fryer\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Fryer looked at four national databases of crime statistics representing police-civilian confrontations from diverse states like Florida, Texas, and California.\", \"id\": \"allsides_553_220_12_Harvard Professor Roland Fryer – an African-American academic who focuses on economics –_0_5\"}\n"
  },
  {
    "path": "NewsSentiment/experiments/default/datasets/newsmtsc-rw-hf/train.jsonl",
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\"(RELATED: The 44 Most Damning Stories From WikiLeaks) During the same event, Clinton also attacked Facebook, Twitter bots, The New York Times, Steve Bannon, and the media in general.\", \"id\": \"allsides_1018_408_8_Hillary Clinton_77_84\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 8, \"to\": 15, \"sentence\": \"Hillary Clinton takes \\\"responsibility\\\" for loss, but says others contributed\", \"id\": \"allsides_1019_408_0_former Secretary of State Hillary Clinton_8_15\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton also looked to social media, saying sites like Facebook and Twitter have been \\\"victimized by deliberate efforts to shape the conversation and push it towards conspiracies, lies, false information.\\\"\", \"id\": \"allsides_1019_408_9_former Secretary of State Hillary Clinton_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump's unhinged Twitter attacks, 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\"Trump\", \"polarity\": 1, \"from\": 94, \"to\": 99, \"sentence\": \"“The reasons for my departure are personal, but it has been my great honor to serve President Trump and this administration,” Dubke, 47, wrote in an email to friends, according to Politico.\", \"id\": \"allsides_1031_412_7_Donald Trump's_94_99\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 22, \"sentence\": \"President Donald Trump hurled more jabs at the \\\"fake news media\\\" Sunday morning, describing White House \\\"leaks\\\" as \\\"fabricated lies\\\" and saying stories with \\\"sources say\\\" make it \\\"very possible\\\" those \\\"sources don't exist\\\" and are made up by \\\"fake news writers.\\\"\", \"id\": \"allsides_1037_415_1_President Donald Trump_0_24\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 30, \"to\": 39, \"sentence\": \"It was a familiar morning for Mr. Trump on his favored medium — and for a nation that had, for a little more than a week, gone without the president’s stream-of-consciousness missives.\", \"id\": \"allsides_1039_415_17_Trump_30_39\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 30, \"to\": 39, \"sentence\": \"It was a familiar morning for Mr. Trump on his favored medium — and for a nation that had, for a little more than a week, gone without the president’s stream-of-consciousness missives.\", \"id\": \"allsides_1039_415_17_Mr. Corker_30_39\"}\n{\"mention\": \"Sunday\", \"polarity\": 0, \"from\": 17, \"to\": 23, \"sentence\": \"But he seemed on Sunday to be as aggrieved as ever by what he considers unfair news coverage.\", \"id\": \"allsides_1039_415_28_Sunday_17_23\"}\n{\"mention\": \"[Mr. Trump]\", \"polarity\": 0, \"from\": 59, \"to\": 70, \"sentence\": \"“The leaders did want to know what his time frame was, and [Mr. Trump] said, look, ‘This is something where I want to get to the right decision.\", \"id\": \"allsides_1042_416_12_Mr. Trump_59_70\"}\n{\"mention\": \"(Reuters/Mike Segar) 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Jared Kushner and Ivanka Trump, the president's daughter, married in 2009.\", \"id\": \"allsides_1043_417_8_Ivanka Trump_23_28\"}\n{\"mention\": \"Harleen Kahlon\", \"polarity\": 1, \"from\": 0, \"to\": 14, \"sentence\": \"Harleen Kahlon was an experienced digital media maven when she was hired by Kushner in 2010 to boost the paper’s digital outreach.\", \"id\": \"allsides_1044_417_38_Harleen Kahlon_0_14\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 1, \"to\": 3, \"sentence\": \"“He would compensate his lack of knowledge by saying stuff like, ‘Let’s just blow up the whole concept of digital.’\", \"id\": \"allsides_1044_417_40_Spiers_1_3\"}\n{\"mention\": \"Mr. Gianforte\", \"polarity\": 0, \"from\": 21, \"to\": 34, \"sentence\": \"During the campaign, Mr. Gianforte embraced Mr. Trump, who won the state by more than 20 percentage points in the November election.\", \"id\": \"allsides_1045_418_15_Mr. Gianforte_21_34\"}\n{\"mention\": \"His\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"His campaign tried to characterize Jacobs as the aggressor, and labeled him a “liberal journalist.”\", \"id\": \"allsides_1050_420_10_CQ Roll Call reporter John M. 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for Christians, the humanity of Holy Week makes our faith overlap with the world around us, just as after years of instructing his followers to stay quiet (at least in Mark) Jesus made his triumphant entrance into Jerusalem.\", \"id\": \"allsides_1167_466_34_Christ_178_183\"}\n{\"mention\": \"Jesus\", \"polarity\": 1, \"from\": 178, \"to\": 183, \"sentence\": \"Yet for Christians, the humanity of Holy Week makes our faith overlap with the world around us, just as after years of instructing his followers to stay quiet (at least in Mark) Jesus made his triumphant entrance into Jerusalem.\", \"id\": \"allsides_1167_466_34_Tony Blair_178_183\"}\n{\"mention\": \"Spicer\", \"polarity\": -1, \"from\": 5, \"to\": 11, \"sentence\": \"Sean Spicer Under Fire After Falsely Claims Nazis Never Used Poison Gas\", \"id\": \"allsides_1176_470_0_Spicer_5_11\"}\n{\"mention\": \"Spicer\", \"polarity\": -1, \"from\": 13, \"to\": 19, \"sentence\": \"Hours later, Spicer apologized, although he made a number 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You know, you had a—you know, someone as despicable as Hitler, who didn’t even sink to the—to using chemical weapons.\", \"id\": \"allsides_1176_470_7_Hitler_143_149\"}\n{\"mention\": \"the president\", \"polarity\": 0, \"from\": 63, \"to\": 76, \"sentence\": \"White House Press Secretary Sean Spicer said Wednesday he “let the president down” comparing Adolf Hitler to Syrian leader Bashar Assad and Mr. Assad’s actions against his people.\", \"id\": \"allsides_1178_470_1_the president_65_78\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 134, \"to\": 139, \"sentence\": \"Mr. Spicer also downplayed reports of a growing feud between Steve Bannon, the president’s chief strategist, and other members of the Trump administration.\", \"id\": \"allsides_1178_470_8_President Trump_134_139\"}\n{\"mention\": \"Russia\", \"polarity\": 1, \"from\": 54, \"to\": 60, \"sentence\": \"“In that regard, we are hopeful that we can work with Russia and use their influence to achieve areas of stabilization throughout Syria and create the conditions for a political process through Geneva in which we can engage all of the parties on the way forward, and it is through that political process that we believe the Syrian people will lawfully be able to decide the fate of Bashar al-Assad,” he added.\", \"id\": \"allsides_1183_473_14_Russia_54_60\"}\n{\"mention\": \"Assad\", \"polarity\": -1, \"from\": 76, \"to\": 81, \"sentence\": \"“This idea that we’re going to get rid of ISIS and then we’ll hopefully use Assad and others to come up with a solution, it’s not going to work,” Rubio said.\", \"id\": \"allsides_1183_473_18_Assad_76_81\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He is a graduate of Columbia, Harvard and Oxford, served as a Supreme Court law clerk and worked as a lawyer at a prestigious Washington law firm and at the Justice Department.\", \"id\": \"allsides_1192_476_13_— Judge Neil M. 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49, \"sentence\": \"Trump said in a statement on Friday that Sessions was a “world-class legal mind and considered a truly great Attorney General and U.S. Attorney in the state of Alabama.”\", \"id\": \"allsides_1635_660_11_Sessions_41_49\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Flynn has also worried some national security experts with his warmth toward Russia.\", \"id\": \"allsides_1636_660_28_Flynn_0_5\"}\n{\"mention\": \"Yellen\", \"polarity\": 0, \"from\": 16, \"to\": 22, \"sentence\": \"In her remarks, Yellen said the Fed, “continues to expect that the evolution of the economy will warrant only gradual increases in the federal funds rate over time” in order to reach full employment and not overshoot on inflation.\", \"id\": \"allsides_1637_661_22_Fed Chair Janet L. 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.@MegynKelly made a total fool out of herself tonight- attacking @realDonaldTrump.\", \"id\": \"allsides_1696_690_23_Kelly_65_72\"}\n{\"mention\": \"Nancy Pelosi\", \"polarity\": -1, \"from\": 11, \"to\": 23, \"sentence\": \"Somewhere, Nancy Pelosi is chewing the inside of her cheek as she glares icily at a life-size Donald Trump 'FatHead' decal she's plastered onto the ceiling over her bed.\", \"id\": \"allsides_16_6_1_Nancy Pelosi_13_25\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 114, \"to\": 119, \"sentence\": \"By ELENA SCHNEIDER No presidential candidate since the advent of modern polling has overcome the sort of deficits Trump faces nationally — where he trails Clinton by an average of 5.9 points — and in swing states with two weeks to go in an election.\", \"id\": \"allsides_1701_692_11_little Trump_114_119\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 168, \"to\": 175, \"sentence\": \"With debate season over and the clock running out for significant swings in public opinion to materialize, the baton now goes to the get-out-the-vote operations, where Clinton enjoys an overwhelming advantage.\", \"id\": \"allsides_1701_692_13_Clinton_168_175\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 8, \"to\": 15, \"sentence\": \"Hillary Clinton enters the final 15 days of the race safely ahead in states worth more than 270 electoral votes.\", \"id\": \"allsides_1701_692_2_Clinton_8_15\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 121, \"to\": 128, \"sentence\": \"Larry Sabato’s Crystal Ball: “With less than three weeks to go, and all of the debates blessedly in the rearview mirror, Clinton is in a commanding position in the contest to become the 45th president… “A striking development in recent days has been the smattering of polling showing Trump with weak leads in some reliably Republican states.\", \"id\": \"allsides_1702_692_22_Hillary Clinton_121_128\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 3, \"to\": 10, \"sentence\": \"Is Clinton now the favorite to reach 270 electoral votes, or, according to some forecasts, much more?\", \"id\": \"allsides_1702_692_6_Clinton_3_10\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 15, \"to\": 18, \"sentence\": \"In the case of his Saturday speech, headlines were dominated by his lawsuit threat, not his detailed policy prescriptions.\", \"id\": \"allsides_1703_693_11_Mr. Trump_15_18\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 12, \"to\": 21, \"sentence\": \"But much of Mr. Trump’s pitch was lost as headlines instead focused on his vow to sue the 11 women that have come forward in recent weeks to accuse him of sexual assault.\", \"id\": \"allsides_1703_693_4_he_12_21\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 12, \"to\": 21, \"sentence\": \"But much of Mr. Trump’s pitch was lost as headlines instead focused on his vow to sue the 11 women that have come forward in recent weeks to accuse him of sexual assault.\", \"id\": \"allsides_1703_693_4_Mr. Trump_12_21\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump has a long history of threatening and occasionally following through on litigation, and in raising the possibility of suing his female accusers, he may have simply been trying to stop more from coming forward.\", \"id\": \"allsides_1704_693_22_Mr. Trump_0_9\"}\n{\"mention\": \"Saturday\", \"polarity\": 0, \"from\": 13, \"to\": 21, \"sentence\": \"At her rally Saturday in Pennsylvania, Mrs. Clinton devoted much of her remarks to the state’s contentious Senate race, giving an extended plug to the Democratic candidate, Katie McGinty, and attacking the Republican incumbent, Senator Patrick J. 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a series of undercover videos revealing corruption within Hillary Clinton's campaign.\", \"id\": \"allsides_1715_698_1_Hillary Clinton_288_305\"}\n{\"mention\": \"Kennedy\", \"polarity\": 0, \"from\": 4, \"to\": 11, \"sentence\": \"Mr. Kennedy was part of a long-running battle between the State Department and the intelligence agencies over Mrs. Clinton’s emails.\", \"id\": \"allsides_1716_699_12_not Mr. Kennedy_4_11\"}\n{\"mention\": \"the State Department\", \"polarity\": 0, \"from\": 300, \"to\": 320, \"sentence\": \"In one of the newly disclosed documents, an unidentified F.B.I. employee told investigators that Mr. Kennedy, through another F.B.I. official, had sought in one case “assistance in altering the email’s classification in exchange for a ‘quid pro quo.’” The F.B.I. had deemed the email classified, but the State Department disagreed.\", \"id\": \"allsides_1716_699_15_the State Department_300_320\"}\n{\"mention\": \"Kennedy\", \"polarity\": -1, \"from\": 43, \"to\": 50, 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about an hour later, which was followed by a third tweet stating: \\\"It is so nice that the shackles have been taken off me and I can now fight for America the way I want to.\\\"\", \"id\": \"allsides_1731_705_3_Paul Ryan_61_70\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 104, \"to\": 107, \"sentence\": \"Story Continued Below \\\"Our very weak and ineffective leader, Paul Ryan, had a bad conference call where his members went wild at his disloyalty,\\\" Trump wrote in a subsequent post about an hour later, which was followed by a third tweet stating: \\\"It is so nice that the shackles have been taken off me and I can now fight for America the way I want to.\\\"\", \"id\": \"allsides_1731_705_3_Ryan (R-Wis.)_104_107\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 81, \"to\": 88, \"sentence\": \"Still, he battled his way to a strong performance in the rest of the debate, and Clinton spent much time on the defensive as the focus shifted to her record.\", \"id\": 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Donald Trump_44_49\"}\n{\"mention\": \"Kaine\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Kaine was admittedly overexcited and his constant interrupting of Pence in the first 20 minutes rubbed everyone, on the left and right, the wrong way.\", \"id\": \"allsides_1749_712_4_Tim Kaine of Virginia_0_5\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 11, \"to\": 16, \"sentence\": \"Meanwhile, Pence exuded the preternatural calm of a sociopath, increasingly frustrating Kaine with his ability to endlessly lie — about easily checked facts — with a disturbingly practiced assurance.\", \"id\": \"allsides_1749_712_5_Pence_11_16\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 6, \"to\": 11, \"sentence\": \"While Pence was the living embodiment of an unflappable liar — definitely the guy to go to if you need someone to bury the bodies — Kaine's relentlessness on this front clearly got to him enough that, for a brief, shining moment, he got flustered and angry.\", \"id\": \"allsides_1749_712_9_Pence_6_11\"}\n{\"mention\": \"House Speaker Paul Ryan (R-Wis.)\", \"polarity\": -1, \"from\": 0, \"to\": 32, \"sentence\": \"House Speaker Paul Ryan (R-Wis.) appeared on NBC’s “Today” show on Wednesday to discuss the Republican tax bill and the impact it will have on workers, leading host Savannah Guthrie to ask him if he was “living in a fantasy world.”\", \"id\": \"allsides_174_71_1_Paul Ryan_0_34\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 64, \"to\": 67, \"sentence\": \"It was a wise choice by Pence, who commanded the debate through his calm re-directing of it back to serious issues.\", \"id\": \"allsides_1750_712_11_Slays Kaine_64_67\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 24, \"to\": 29, \"sentence\": \"It was a wise choice by Pence, who commanded the debate through his calm re-directing of it back to serious issues.\", \"id\": \"allsides_1750_712_11_Mike Pence_24_29\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 145, \"to\": 152, \"sentence\": \"That Reaganesque rejoinder from Mike Pence — one of many — effectively put Tim Kaine in his place during a debate that exposed the depths of the Hillary campaign’s demagogic cheapness.\", \"id\": \"allsides_1750_712_2_Hillary_145_152\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 71, \"to\": 76, \"sentence\": \"Kaine’s labored lines and sweaty lunges contrasted embarrassingly with Pence’s smooth and substantive debate performance.\", \"id\": \"allsides_1750_712_4_Mike Pence_71_76\"}\n{\"mention\": \"Kaine\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Kaine’s labored lines and sweaty lunges contrasted embarrassingly with Pence’s smooth and substantive debate performance.\", \"id\": \"allsides_1750_712_4_Kaine_0_5\"}\n{\"mention\": \"Kaine\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Kaine puts it even more starkly than Clinton.\", \"id\": \"allsides_1754_714_106_Kaine_0_5\"}\n{\"mention\": \"Kaine\", 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Giuliani defended Mr. Trump’s tax moves by boasting that the billionaire businessman was an “absolute genius.”\", \"id\": \"allsides_1761_717_4_Mr. Trump_51_60\"}\n{\"mention\": \"the billionaire businessman was an “absolute genius\", \"polarity\": 1, \"from\": 90, \"to\": 141, \"sentence\": \"Former New York Mayor Rudolph W. Giuliani defended Mr. Trump’s tax moves by boasting that the billionaire businessman was an “absolute genius.”\", \"id\": \"allsides_1761_717_4_the billionaire businessman was an “absolute genius_90_141\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 25, \"to\": 34, \"sentence\": \"However, he has endorsed Mr. Trump’s proposals to cut taxes and reduce federal regulations, and he has criticized Mrs. Clinton’s tax plan for increasing a variety of taxes.\", \"id\": \"allsides_1761_717_69_Mr. Trump_25_34\"}\n{\"mention\": \"Hillary\", \"polarity\": -1, \"from\": 117, \"to\": 124, \"sentence\": \"The wolf was replaced Monday night by a kinder, gentler Trump, a lovable lamb — now that the target in the debate is Hillary.\", \"id\": \"allsides_1763_718_40_Hillary Clinton_117_124\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 191, \"to\": 206, \"sentence\": \"On January 27, 1998, she told NBC News that there was a “vast right-wing conspiracy” out to get her husband — one that included this august publication, The American Spectator It was classic Hillary Clinton.\", \"id\": \"allsides_1763_718_60_Hillary Clinton_191_206\"}\n{\"mention\": \"It\", \"polarity\": -1, \"from\": 176, \"to\": 178, \"sentence\": \"On January 27, 1998, she told NBC News that there was a “vast right-wing conspiracy” out to get her husband — one that included this august publication, The American Spectator It was classic Hillary Clinton.\", \"id\": \"allsides_1763_718_60_It_176_178\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 49, \"to\": 51, \"sentence\": \"Rather than excoriating his debate opponent — as he did freely, wantonly, brutally, to the likes of Ted Cruz and Marco Rubio — Trump this time chose not to jump into the gutter.\", \"id\": \"allsides_1763_718_6_Donald Trump_49_51\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 52, \"to\": 61, \"sentence\": \"But when asked if he had ever cheated on his wives, Mr. Trump said: “No — I never discuss it.\", \"id\": \"allsides_1764_718_20_Donald Trump_52_61\"}\n{\"mention\": \"it\", \"polarity\": -1, \"from\": 90, \"to\": 92, \"sentence\": \"But when asked if he had ever cheated on his wives, Mr. Trump said: “No — I never discuss it.\", \"id\": \"allsides_1764_718_20_it_90_92\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump’s sharply negative attacks on the Clintons, and on Ms. Machado, pose a significant political risk to his own appeal: Two-thirds of voters already see him unfavorably, according to polls, and he is struggling to win over female voters — including white women, a majority of whom have historically supported the Republican candidate in presidential elections.\", \"id\": \"allsides_1764_718_30_Donald Trump_0_9\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 56, \"to\": 65, \"sentence\": \"The Clinton campaign is running a new attack ad against Mr. Trump featuring his insults of women over the years and has aggressively defended Ms. Machado; Mrs. Clinton called her on Friday to offer thanks “for all she had done and the courage she has shown, particularly as this became elevated through a war of some pretty unpleasant words,” according to Nick Merrill, a campaign spokesman.\", \"id\": \"allsides_1764_718_31_Trump_56_65\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 155, \"to\": 167, \"sentence\": \"The Clinton campaign is running a new attack ad against Mr. Trump featuring his insults of women over the years and has aggressively defended Ms. Machado; Mrs. Clinton called her on Friday to offer thanks “for all she had done and the courage she has shown, particularly as this became elevated through a war of some pretty unpleasant words,” according to Nick Merrill, a campaign spokesman.\", \"id\": \"allsides_1764_718_31_Hillary Clinton_155_167\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 56, \"to\": 65, \"sentence\": \"The Clinton campaign is running a new attack ad against Mr. Trump featuring his insults of women over the years and has aggressively defended Ms. Machado; Mrs. Clinton called her on Friday to offer thanks “for all she had done and the courage she has shown, particularly as this became elevated through a war of some pretty unpleasant words,” according to Nick Merrill, a campaign spokesman.\", \"id\": \"allsides_1764_718_31_Donald Trump_56_65\"}\n{\"mention\": \"Ms. Machado\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"Ms. Machado was being paid to look perfect, and when she couldn’t -- or wouldn’t -- live up to the standard she had asked to be measured by, she caught criticism.\", \"id\": \"allsides_1765_719_40_Alicia Machado_0_11\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton's campaign jumped on Trump's Machado tweets later Friday morning, eager for yet another chance to highlight his tendency to fling derogatory remarks at women.\", \"id\": \"allsides_1766_719_23_Alicia Machado_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 143, \"to\": 148, \"sentence\": \"\\\"There's been a lot of talk about sex tapes today and in a strange turn of events only one adult film has emerged today and its star is Donald Trump,\\\" Clinton spokesman Nick Merrill told her traveling press.\", \"id\": \"allsides_1766_719_37_Trump_143_148\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 130, \"to\": 135, \"sentence\": \"The former pageant winner told Cosmopolitan Magazine this week that she became a citizen last August specifically to vote against Trump, well after Clinton's 2013 departure from the State Department.\", \"id\": \"allsides_1766_719_61_Trump_130_135\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 45, \"to\": 50, \"sentence\": \"One of the main talking points has been that Trump was a “gentleman” for not bringing up Bill Clinton’s infidelities and hasn’t gotten the credit he deserved.\", \"id\": \"allsides_1766_719_72_Trump_45_50\"}\n{\"mention\": \"Bill Clinton’s\", \"polarity\": -1, \"from\": 89, \"to\": 103, \"sentence\": \"One of the main talking points has been that Trump was a “gentleman” for not bringing up Bill Clinton’s infidelities and hasn’t gotten the credit he deserved.\", \"id\": \"allsides_1766_719_72_Bill Clinton’s_89_103\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 53, \"to\": 60, \"sentence\": \"Trump struggled to defend himself against attacks by Clinton over his denigration of women, insensitivity on race relations and an assertion that he avoided paying federal taxes for years.\", \"id\": \"allsides_1771_722_13_Hillary Clinton_53_60\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump struggled to defend himself against attacks by Clinton over his denigration of women, insensitivity on race relations and an assertion that he avoided paying federal taxes for years.\", \"id\": \"allsides_1771_722_13_Trump_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 256, \"to\": 261, \"sentence\": \"On the monitor tracking the voters’ reactions to the candidates, which was visible to the handful of reporters observing the group, even those leaning toward the Republican nominee disapproved of his windy response when Clinton ticked off possible reasons Trump may not want to disclose his tax returns.\", \"id\": \"allsides_1771_722_16_Trump_256_261\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 8, \"to\": 13, \"sentence\": \"“Donald Trump just got nuked,” he said.\", \"id\": \"allsides_1771_722_18_Trump_8_13\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 31, \"to\": 33, \"sentence\": \"“Donald Trump just got nuked,” he said.\", \"id\": \"allsides_1771_722_18_The freewheeling Republican nominee_31_33\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 97, \"to\": 109, \"sentence\": \"Members of Philadelphia focus group cite Clinton’s ‘informed’ and ‘strong’ showing over ‘sloppy’ Donald Trump but remain unenthusiastic about choices Lauren Gambino in Philadelphia Tue 27 Sep 2016 12.32 BST Last modified on Fri 14 Jul 2017 19.39 BST In a clash between the two most unpopular presidential nominees in modern history, a group of undecided voters in the battleground state of Pennsylvania declared Hillary Clinton the clear winner; but remained deeply pessimistic about their choices in November.\", \"id\": \"allsides_1771_722_1_Trump_99_111\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 3, \"to\": 6, \"sentence\": \"As she spoke, many of the voters in the room agreed with her, especially among those already leaning towards her.\", \"id\": \"allsides_1771_722_24_Hillary Clinton_3_6\"}\n{\"mention\": \"—Clinton Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 16, \"sentence\": \"—Clinton Clinton exaggerates here.\", \"id\": \"allsides_1774_723_21_Hillary Clinton_0_16\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton is subtly adjusting her words here when confronted with a question about her consistency on policy positions.\", \"id\": \"allsides_1774_723_70_Hillary Clinton_0_7\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He asks no similar questions about Clinton’s record, leaving Trump himself to bring up such Clinton hits as “superpredator.”\", \"id\": \"allsides_1775_723_16_Lester Holt_0_2\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 52, \"to\": 59, \"sentence\": \"Trump counters, again, with examples of racism from Clinton’s 2008 campaign.\", \"id\": \"allsides_1775_723_20_Democratic presidential nominee Hillary Clinton_52_59\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 22, \"to\": 29, \"sentence\": \"PolitiFact notes that Clinton did, indeed, flip-flop on the deal: > LIVE FACT-CHECK: Trump is right, Clinton flip-flopped on TPP https://t.co/howNkUisAE pic.twitter.com/V70SDG3MAY > — PolitiFact Live (@politifactlive) September 27, 2016 Was that necessary, though?\", \"id\": \"allsides_1775_723_49_Democratic presidential nominee Hillary Clinton_22_29\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 22, \"to\": 29, \"sentence\": \"The whopper came from Clinton, who suggested that the U.S. does not yet have “equal pay for equal work,” something that has been a matter of law for decades.\", \"id\": \"allsides_1775_723_64_Clinton_22_29\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 34, \"to\": 41, \"sentence\": \"For months, evidence mounted that Clinton had lied.\", \"id\": \"allsides_1775_723_78_Clinton_35_42\"}\n{\"mention\": \"Mook\", \"polarity\": 0, \"from\": 68, \"to\": 72, \"sentence\": \"\\\"So we're saying this is a special circumstance, a special debate,\\\" Mook added.\", \"id\": \"allsides_1776_724_18_Clinton campaign manager Robby Mook_68_72\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 68, \"to\": 73, \"sentence\": \"\\\"It's unfair to ask for Hillary both to play traffic cop while with Trump, make sure that his lies are corrected, and also to present her vision for what she wants to do for the American people,\\\" Mook said.\", \"id\": \"allsides_1776_724_5_Trump_68_73\"}\n{\"mention\": \"Hillary\", \"polarity\": 1, \"from\": 24, \"to\": 31, \"sentence\": \"\\\"It's unfair to ask for Hillary both to play traffic cop while with Trump, make sure that his lies are corrected, and also to present her vision for what she wants to do for the American people,\\\" Mook said.\", \"id\": \"allsides_1776_724_5_Hillary Clinton's_24_31\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 36, \"to\": 43, \"sentence\": \"—Instant polls 60-70% likely to say Clinton wins.\", \"id\": \"allsides_1778_724_28_Clinton_36_43\"}\n{\"mention\": \"(Obligatory parenthetical: Yes, Clinton lies too\", \"polarity\": -1, \"from\": 0, \"to\": 48, \"sentence\": \"(Obligatory parenthetical: Yes, Clinton lies too.\", \"id\": \"allsides_1778_724_55_(Obligatory parenthetical: Yes, Clinton lies too_0_48\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 32, \"to\": 39, \"sentence\": \"(Obligatory parenthetical: Yes, Clinton lies too.\", \"id\": \"allsides_1778_724_55_Clinton_32_39\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 4, \"to\": 9, \"sentence\": \"Mr. Trump can get bored with both debate preparations and debates themselves.\", \"id\": \"allsides_1780_725_32_Mr. Trump_4_9\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 49, \"to\": 54, \"sentence\": \"Her aim is to look steady and attentive when Mr. Trump is speaking, and to avoid visibly or audibly reacting to him too much.\", \"id\": \"allsides_1780_725_40_Mr. Trump_49_54\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 41, \"to\": 50, \"sentence\": \"Mrs. Clinton has concluded that catching Mr. Trump in a lie during the debate is not enough to beat him: She needs the huge television audience to see him as temperamentally unfit for the presidency, and that she has the power to unhinge him.\", \"id\": \"allsides_1780_725_7_Donald J. Trump’s_41_50\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 277, \"to\": 289, \"sentence\": \"Given what must be the top two issues up for discussion: crime (and the subsidiary conversation about law enforcement) and terrorism, both of which should be among Trump’s few strong suits, the debate represents an unlikely opportunity for The Donald to go on offense, to show Mrs. Clinton for what she is: an elitist who is wildly out of touch with the concerns of ordinary Americans.\", \"id\": \"allsides_1781_725_20_Hillary Clinton_277_289\"}\n{\"mention\": \"Police Chief Kerr Putney\", \"polarity\": -1, \"from\": 0, \"to\": 24, \"sentence\": \"Police Chief Kerr Putney added to that anger at a news conference on Thursday when he said that the video did not give him “absolute, definitive, visual evidence that would confirm that a person is pointing a gun,” though he insisted that there was evidence to suggest that the police account of the event was correct.\", \"id\": 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\"sentence\": \"Donald Trump is surging in new battleground and national polls at a time when Hillary Clinton faces tough questions not only about her health but her sweeping criticism of her Republican opponent’s supporters.\", \"id\": \"allsides_1806_735_1_Trump_9_14\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 78, \"to\": 93, \"sentence\": \"Donald Trump is surging in new battleground and national polls at a time when Hillary Clinton faces tough questions not only about her health but her sweeping criticism of her Republican opponent’s supporters.\", \"id\": \"allsides_1806_735_1_Hillary Clinton_80_95\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He takes us for idiots,\\\" Powell, who is black, said in the email.\", \"id\": \"allsides_1808_737_14_Donald Trump_1_3\"}\n{\"mention\": \"Powell\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Powell also derided former Fox News CEO Roger Ailes, who advises Trump, 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several national public opinion polls that compared the views of Clinton and Trump voters.\", \"id\": \"allsides_1816_739_17_Hillary Clinton_103_110\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 52, \"to\": 59, \"sentence\": \"Former President Obama adviser David Axelrod rapped Clinton Monday on her \\\"penchant for privacy.\\\"\", \"id\": \"allsides_1817_740_19_Hillary Clinton_52_59\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton wore a high-collared shirt and a dark pant suit and donned sunglasses for the morning event.\", \"id\": \"allsides_1819_740_26_Clinton_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 54, \"to\": 61, \"sentence\": \"Trump spokesman Jason Miller said in a statement that Clinton had \\\"revealed her true contempt for everyday Americans\\\" and called the remarks an \\\"inexcusable mistake.\\\"\", \"id\": \"allsides_1823_742_17_Clinton_54_61\"}\n{\"mention\": \"Trump\", \"polarity\": 0, 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\"id\": \"allsides_1830_745_32_Hillary Clinton_116_123\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 22, \"to\": 29, \"sentence\": \"At that time, Hillary Clinton’s lead over Trump in national polls rose to around 8 to 9 points on average, and now appears to be something more like 3 to 5 points.\", \"id\": \"allsides_1830_745_3_Hillary Clinton_22_29\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 104, \"to\": 109, \"sentence\": \"Katie ran through the basics this morning, underscoring the astonishing reversal of fortunes for Donald Trump and Hillary Clinton.\", \"id\": \"allsides_1831_745_13_Trump_104_109\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 58, \"to\": 63, \"sentence\": \"One of the key findings of the poll is that although both Trump and Clinton are dominating among their own parties' respective bases, Trump voters are more enthusiastic to turn out than hers are: Story of CNN poll showing Trump taking the lead: His voters are more enthusiastic.\", \"id\": \"allsides_1831_745_17_Trump_60_65\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton scandals taking a toll. pic.twitter.com/FA3lRy1uQt Ben Shapiro writes that unlike other \\\"good\\\" polls for Trump, in which his support remained static as Hillary's dropped, the new CNN survey actually shows him gaining.\", \"id\": \"allsides_1831_745_18_Hillary Clinton_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 113, \"to\": 118, \"sentence\": \"Clinton scandals taking a toll. pic.twitter.com/FA3lRy1uQt Ben Shapiro writes that unlike other \\\"good\\\" polls for Trump, in which his support remained static as Hillary's dropped, the new CNN survey actually shows him gaining.\", \"id\": \"allsides_1831_745_18_Trump_113_118\"}\n{\"mention\": \"Hillary Clinton's\", \"polarity\": -1, \"from\": 39, \"to\": 56, \"sentence\": \"And the relentless drip, drip, drip of Hillary Clinton's corrupt lying getting systematically 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\"allsides_1842_750_23_Clinton_0_3\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 174, \"to\": 179, \"sentence\": \"And as the procession of mothers and fathers came up to the podium to state the name of their child -- who was murdered by illegal immigrants -- and then say “I’m voting for Trump” or “Trump is our last chance to save America” I found myself tearing up.\", \"id\": \"allsides_1849_753_16_President Donald J. 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\"polarity\": -1, \"from\": 18, \"to\": 21, \"sentence\": \"But consider what she is saying: if you speak honestly about problems in the black community, you are racist.\", \"id\": \"allsides_1867_760_27_Clinton_18_21\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 5, \"to\": 12, \"sentence\": \"What Clinton leaves out, of course, is that Trump had already denounced Duke and the KKK several times — including the day before that CNN interview.\", \"id\": \"allsides_1867_760_63_Clinton_6_13\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 44, \"to\": 49, \"sentence\": \"What Clinton leaves out, of course, is that Trump had already denounced Duke and the KKK several times — including the day before that CNN interview.\", \"id\": \"allsides_1867_760_63_Trump_45_50\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 116, \"to\": 121, \"sentence\": \"On Wednesday, the campaigns of his former rivals were quick to point this out. .@JebBush spox @kristymcampbell says 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York Times writes, “[W]hile the move could avoid the awkwardness of Mr. Clinton jetting around the world asking for money while his wife is president, it did not resolve a more pressing question: how her administration would handle longtime donors seeking help from the United States, or whose interests might conflict with the country’s own.”\", \"id\": \"allsides_1875_764_39_the New York Times_11_29\"}\n{\"mention\": \"Toomey\", \"polarity\": 1, \"from\": 18, \"to\": 24, \"sentence\": \"Bloomberg praised Toomey’s support of expanding background checks as his chief reason for helping him.\", \"id\": \"allsides_1878_765_21_Pat Toomey_18_24\"}\n{\"mention\": \"New York hedge fund billionaire George Soros\", \"polarity\": 1, \"from\": 15, \"to\": 59, \"sentence\": \"In July alone, New York hedge fund billionaire George Soros gave $1.5 million to Planned Parenthood’s super PAC and $35,000 to Priorities USA, both working to elect Clinton, as well as $500,000 to the Senate Majority PAC.\", \"id\": \"allsides_1878_765_9_New York hedge fund billionaire George Soros_15_59\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 48, \"to\": 50, \"sentence\": \"But this time, I actually believe that’s true,” he said, adding: “I am a Hillary Clinton fan, and I have been for quite some time.\", \"id\": \"allsides_1879_765_26_Sussman_48_50\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 81, \"to\": 88, \"sentence\": \"But this time, I actually believe that’s true,” he said, adding: “I am a Hillary Clinton fan, and I have been for quite some time.\", \"id\": \"allsides_1879_765_26_anti-Clinton_81_88\"}\n{\"mention\": \"Loewentritt\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Loewentritt also told BuzzFeed that the GSA suggested that Mueller's team issue a warrant or subpoena for the transition team materials, but the special prosecutor's office decided a letter requesting the materials would suffice.\", \"id\": \"allsides_187_77_19_GSA Deputy Counsel Lenny Loewentritt_0_11\"}\n{\"mention\": \"Lochte\", \"polarity\": -1, \"from\": 18, \"to\": 24, \"sentence\": \"Rio police indict Lochte, teammate for falsely reporting robbery\", \"id\": \"allsides_1891_770_0_Lochte_18_24\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He stopped me quickly and strongly denied that,\\\" Lauer said.\", \"id\": \"allsides_1891_770_39_Lochte_1_3\"}\n{\"mention\": \"Mr. Ailes\", \"polarity\": -1, \"from\": 104, \"to\": 113, \"sentence\": \"Before Mr. Ailes’s ouster, some of the network’s journalists and contributors privately complained that Mr. Ailes was pushing them to be more supportive of Mr. Trump.\", \"id\": \"allsides_1892_771_48_Mr. Ailes_104_113\"}\n{\"mention\": \"Mr. Bannon\", \"polarity\": -1, \"from\": 185, \"to\": 195, \"sentence\": \"The website emerged as a singular defender of Mr. Ailes, with a piece about a planned walkout by network stars loyal to him should he be forced out — it never came to pass — and one by Mr. Bannon ridiculing the “minor Murdochs” (the 21st Century Fox chief Rupert Murdoch’s sons and co-executives, James and Lachlan), who were seen as leading the push for Mr. Ailes to resign.\", \"id\": \"allsides_1892_771_51_his_185_195\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton, though, has been plastering the airwaves with ads, while taking a significant post-convention lead in a number of battleground and national polls.\", \"id\": \"allsides_1893_771_7_Clinton_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 140, \"to\": 147, \"sentence\": \"In a shift, he delivered a scripted speech to a rally audience Tuesday night in Wisconsin, appealing to minority voters in part by accusing Clinton of \\\"bigotry\\\" and saying she sees African-Americans as no more than votes to be won.\", \"id\": \"allsides_1893_771_9_Clinton_140_147\"}\n{\"mention\": \"Tuesday\", \"polarity\": 0, \"from\": 63, \"to\": 70, \"sentence\": \"In a shift, he delivered a scripted speech to a rally audience Tuesday night in Wisconsin, appealing to minority voters in part by accusing Clinton of \\\"bigotry\\\" and saying she sees African-Americans as no more than votes to be won.\", \"id\": \"allsides_1893_771_9_Tuesday_63_70\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 49, \"to\": 64, \"sentence\": \"“Incident after incident proves again and again: Hillary Clinton lacks the judgment, the temperament and the moral character to lead this nation,” he said.\", \"id\": \"allsides_1895_772_21_Clinton_49_64\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 38, \"to\": 43, \"sentence\": \"“As in several other areas of policy, Trump’s approach to foreign policy and national security seems a bit nebulous, focused on slogans rather concrete policies.”\", \"id\": \"allsides_1895_772_31_Donald Trump_38_43\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 13, \"to\": 25, \"sentence\": \"“Simply put, Donald Trump is unfit to be our commander in chief.\", \"id\": \"allsides_1895_772_33_Donald Trump_13_25\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 62, \"to\": 67, \"sentence\": \"“It all began in 2009 with what has become known as President Obama’s global ‘Apology Tour.’” Trump resurrects an old — and discredited — Republican talking point.\", \"id\": \"allsides_1896_772_26_Obama_62_67\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 55, \"to\": 60, \"sentence\": \"As we demonstrated more than five years ago, Rove took Obama’s quotes out of context and twisted their meaning in order to build a tendentious case.\", \"id\": \"allsides_1896_772_28_Obama_55_60\"}\n{\"mention\": \"Rove\", \"polarity\": -1, \"from\": 45, \"to\": 49, \"sentence\": \"As we demonstrated more than five years ago, Rove took Obama’s quotes out of context and twisted their meaning in order to build a tendentious case.\", \"id\": \"allsides_1896_772_28_Karl Rove_45_49\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 42, \"to\": 47, \"sentence\": \"In the quote cited by the Trump campaign, Obama said that intervening was “the right thing to do.”\", \"id\": \"allsides_1896_772_37_Obama_42_47\"}\n{\"mention\": \"his worst mistake\", \"polarity\": -1, \"from\": 21, \"to\": 38, \"sentence\": \"What he regretted as his worst mistake was failing to plan for “the day after.”\", \"id\": \"allsides_1896_772_38_his worst mistake_21_38\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He laid the blame for the rise of Islamic extremism on President Obama and Mrs. Clinton.\", \"id\": \"allsides_1897_773_12_Mr. Trump_0_2\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 10, \"to\": 12, \"sentence\": \"Over all, he appeared to be arguing for the kind of terrorism-centric foreign policy that President George W. 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portray Mrs. Clinton as being chummy with Wall Street.\", \"id\": \"allsides_1905_775_27_Mrs. Clinton_96_108\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 8, \"to\": 15, \"sentence\": \"Hillary Clinton vowed Thursday to kill the Pacific trade deal that she helped push just a few years ago as President Obama’s top diplomat, hoping to win over wavering liberals and steal some of the anti-trade thunder from Republican presidential nominee Donald Trump.\", \"id\": \"allsides_1906_776_1_Clinton_10_17\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 12, \"to\": 24, \"sentence\": \"Fact Check: Mrs. Clinton was making the point that, for many people, post-high school options that she promised to promote with government help — like job-training programs and community college degrees — would be sufficient to find jobs.\", \"id\": \"allsides_1908_776_31_Hillary Clinton_12_24\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Mrs. Clinton is also correct that most Americans, including wealthy ones, are not affected now by estate taxes.\", \"id\": \"allsides_1908_776_49_Mrs. Clinton_0_12\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Mrs. Clinton is also correct that most Americans, including wealthy ones, are not affected now by estate taxes.\", \"id\": \"allsides_1908_776_49_Hillary Clinton_0_12\"}\n{\"mention\": \"most Americans, including wealthy ones, are not affected now by estate taxes\", \"polarity\": 0, \"from\": 34, \"to\": 110, \"sentence\": \"Mrs. Clinton is also correct that most Americans, including wealthy ones, are not affected now by estate taxes.\", \"id\": \"allsides_1908_776_49_most Americans, including wealthy ones, are not affected now by estate taxes_34_110\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 118, \"to\": 125, \"sentence\": \"The emails are separate from a larger batch of several thousand work-related emails that FBI officials recovered from Clinton’s private server.\", \"id\": \"allsides_1913_778_9_Hillary Clinton_118_125\"}\n{\"mention\": \"FBI\", \"polarity\": 0, \"from\": 89, \"to\": 92, \"sentence\": \"The emails are separate from a larger batch of several thousand work-related emails that FBI officials recovered from Clinton’s private server.\", \"id\": \"allsides_1913_778_9_FBI_89_92\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton lies more than Trump is outspoken.\", \"id\": \"allsides_1914_779_27_Clinton_0_7\"}\n{\"mention\": \"Ms. Smith and Mr. Woods\", \"polarity\": 0, \"from\": 5, \"to\": 28, \"sentence\": \"Both Ms. Smith and Mr. Woods have spoken out publicly against Mrs. Clinton during the election campaign.\", \"id\": \"allsides_1917_780_4_Patricia Smith and Charles Woods_5_28\"}\n{\"mention\": \"Smith\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Smith has been a very vocal critic of Clinton, who she says is a 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Clinton_41_56\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 63, \"to\": 66, \"sentence\": \"Stein also served as the party’s standard-bearer in 2012, when she received .9 percent of the national popular vote.\", \"id\": \"allsides_1922_781_3_human rights activist Ajamu Baraka_64_67\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 11, \"to\": 18, \"sentence\": \"Trump said Clinton is a \\\"dangerous liar\\\" and accused her of failing to achieve anything during her long career in public service — except, he said, avoiding criminal charges for using a private email server during her tenure as secretary of state.\", \"id\": \"allsides_1926_783_12_Clinton_11_18\"}\n{\"mention\": \"Crooked Hillary\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"Crooked Hillary said loudly, and for the world to see, that she \\\"SHORT CIRCUITED\\\" when answering a question on her e-mails.\", \"id\": \"allsides_1927_783_6_Crooked Hillary_0_15\"}\n{\"mention\": \"The Washington 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\"allsides_1937_787_6_Trump_110_115\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 12, \"to\": 17, \"sentence\": \"On Tuesday, Trump praised Nehlen for running “a very good campaign”.\", \"id\": \"allsides_1940_788_37_Donald Trump_12_17\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump Strikes Blow to GOP ‘Unity’ by Withholding Endorsement From House Speaker Ryan\", \"id\": \"allsides_1941_788_0_Republican presidential nominee Donald Trump_0_5\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 15, \"to\": 22, \"sentence\": \"The poll shows Clinton’s favorable rating ticking up to 43 percent, from 41 percent the week prior.\", \"id\": \"allsides_1943_789_38_Hillary Clinton's_15_22\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 26, \"to\": 33, \"sentence\": \"Patricia Smith criticized Clinton at the Republican convention, noting that she has received much different treatment than the Khan family.\", \"id\": \"allsides_1944_789_11_Clinton_26_33\"}\n{\"mention\": \"Khizr Khan\", \"polarity\": 1, \"from\": 0, \"to\": 10, \"sentence\": \"Khizr Khan blasted Trump on stage last week at the Democratic National Convention, noting that unlike his fallen son, who was killed in 2004 while guarding his base in Iraq, Trump has \\\"sacrificed nothing and no one.\\\"\", \"id\": \"allsides_1945_790_2_Khizr Khan_0_10\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 19, \"to\": 24, \"sentence\": \"Khizr Khan blasted Trump on stage last week at the Democratic National Convention, noting that unlike his fallen son, who was killed in 2004 while guarding his base in Iraq, Trump has \\\"sacrificed nothing and no one.\\\"\", \"id\": \"allsides_1945_790_2_Trump_19_24\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 9, \"to\": 11, \"sentence\": \"However, he tweeted about Khizr Khan on Monday morning.\", \"id\": \"allsides_1946_790_26_Gold Star Families Attack Trump Over Comments About Ghazala 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speech, and the audience’s reaction (“lock her up!”), “really disturbing.”\", \"id\": \"allsides_1950_791_13_when bereaved Benghazi mother Patricia Smith_14_19\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 5, \"to\": 12, \"sentence\": \"Bill Clinton notoriously avoided the Vietnam draft — a subject that came up in his 1992 presidential campaign, as Stephanopoulos surely remembers.\", \"id\": \"allsides_1950_791_23_Hillary Clinton_5_12\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton’s actions have been reckless and have directly led to the loss of American lives.\", \"id\": \"allsides_1950_791_34_Hillary Clinton_0_7\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 46, \"to\": 61, \"sentence\": \"As Bernie Sanders said on numerous occasions, Hillary Clinton suffers from “bad judgement.”\", \"id\": \"allsides_1950_791_36_Hillary Clinton_46_61\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 158, \"to\": 164, \"sentence\": \"What’s striking about the coverage is that it barely acknowledges that this could be an open question: The New York Times headline: “Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts”: “There is simply no precedent for this: A presidential candidate publicly appealing to a foreign adversary to intervene in the election on his behalf.”\", \"id\": \"allsides_1953_793_19_Russia_158_164\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 140, \"to\": 145, \"sentence\": \"What’s striking about the coverage is that it barely acknowledges that this could be an open question: The New York Times headline: “Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts”: “There is simply no precedent for this: A presidential candidate publicly appealing to a foreign adversary to intervene in the election on his behalf.”\", \"id\": \"allsides_1953_793_19_Republican nominee Donald Trump_140_145\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 23, \"to\": 28, \"sentence\": \"The uproar over Donald Trump’s latest comments is a classic case of media-generated outrage.\", \"id\": \"allsides_1953_793_1_Republican nominee Donald Trump_25_30\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 41, \"to\": 47, \"sentence\": \"Politico’s lead: \\\"Donald Trump's call on Russia to hack Hillary Clinton's emails has shocked, flabbergasted and appalled lawmakers and national security experts across the political spectrum, with one saying it was ‘tantamount to treason.’” “Is it possible that Trump was being sarcastic?\", \"id\": \"allsides_1953_793_21_Russia_41_47\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 25, \"to\": 31, \"sentence\": \"Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts\", \"id\": \"allsides_1954_793_0_Russia_25_31\"}\n{\"mention\": \"Donald Trump’s\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"Donald Trump’s Appeal to Russia Shocks Foreign Policy Experts\", \"id\": \"allsides_1954_793_0_Donald Trump’s_0_14\"}\n{\"mention\": \"President Jimmy Carter\", \"polarity\": -1, \"from\": 5, \"to\": 27, \"sentence\": \"When President Jimmy Carter ran for re-election in 1980, he lost in part because he had failed to secure the freedom of 52 American hostages held in Iran.\", \"id\": \"allsides_1954_793_16_President Jimmy Carter_5_27\"}\n{\"mention\": \"the department\", \"polarity\": 0, \"from\": 87, \"to\": 101, \"sentence\": \"But she deleted a similar number of emails that she said were unrelated to her work at the department.\", \"id\": \"allsides_1954_793_8_the State Department_87_101\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 4, \"to\": 7, \"sentence\": \"But she deleted a similar number of emails that she said were unrelated to her work at the department.\", \"id\": \"allsides_1954_793_8_Hillary Clinton_4_7\"}\n{\"mention\": \"it\", \"polarity\": 0, \"from\": 172, \"to\": 174, \"sentence\": \"She quipped that “he's taken the Republican 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\"allsides_1957_794_29_Hillary_50_57\"}\n{\"mention\": \"Bill Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Bill Clinton really did help Obama win.\", \"id\": \"allsides_1960_797_10_Bill Clinton_0_12\"}\n{\"mention\": \"Bill Clinton\", \"polarity\": 1, \"from\": 65, \"to\": 77, \"sentence\": \"The best jokes have at least a kernel of truth to them: Tonight, Bill Clinton strode into the spotlight once again, this time to work his magic on behalf of his wife.\", \"id\": \"allsides_1960_797_13_Clinton_65_77\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 147, \"to\": 154, \"sentence\": \"“Because this is a movement fuelled by love it can never be stopped or defeated,” said Hawaii congresswoman Tulsi Gabbard as she formally proposed Sanders for the nomination.\", \"id\": \"allsides_1962_797_33_Bernie Sanders_147_154\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 1, \"to\": 16, \"sentence\": \"“Hillary Clinton will make an outstanding 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\"allsides_1964_799_8_Sanders_70_72\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 105, \"to\": 112, \"sentence\": \"“Hillary Clinton will make an outstanding president, and I am proud to stand with her here tonight,” Mr. Sanders said as his supporters waved his blue campaign signs.\", \"id\": \"allsides_1966_799_15_Senator Bernie Sanders_105_112\"}\n{\"mention\": \"his supporters\", \"polarity\": 1, \"from\": 121, \"to\": 135, \"sentence\": \"“Hillary Clinton will make an outstanding president, and I am proud to stand with her here tonight,” Mr. Sanders said as his supporters waved his blue campaign signs.\", \"id\": \"allsides_1966_799_15_his supporters_121_135\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 83, \"to\": 95, \"sentence\": \"“We trusted you!” they yelled, suggesting that she had betrayed them by supporting Mrs. Clinton.\", \"id\": \"allsides_1966_799_20_Some targeted Mrs. Clinton with a taunting chant from last week_83_95\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 83, \"to\": 95, \"sentence\": \"“We trusted you!” they yelled, suggesting that she had betrayed them by supporting Mrs. Clinton.\", \"id\": \"allsides_1966_799_20_Hillary Clinton_83_95\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": 1, \"from\": 127, \"to\": 139, \"sentence\": \"Some Democratic officials said the fury was an illustration of the work that still needed to be done to unify the party behind Mrs. Clinton, as well as a sign of the dedication Mr. Sanders engendered over the last year.\", \"id\": \"allsides_1966_799_39_Some targeted Mrs. Clinton with a taunting chant from last week_127_139\"}\n{\"mention\": \"Wasserman Schultz's\", \"polarity\": -1, \"from\": 13, \"to\": 32, \"sentence\": \"Even some of Wasserman Schultz's harshest critics acknowledge that part of that problem was structural: She was in elected office while also serving as the party chair.\", \"id\": \"allsides_1967_800_20_Debbie Wasserman Schultz_13_32\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She faces a primary from a Sanders-backed candidate but most political observers say she will win it.\", \"id\": \"allsides_1967_800_43_Wasserman Schultz_0_3\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 27, \"to\": 34, \"sentence\": \"She faces a primary from a Sanders-backed candidate but most political observers say she will win it.\", \"id\": \"allsides_1967_800_43_Bernie Sanders_27_34\"}\n{\"mention\": \"the DNC news\", \"polarity\": -1, \"from\": 20, \"to\": 32, \"sentence\": \"Trump tweeted after the DNC news broke: Today proves what I have always known, that @Reince Priebus is the tough one and the smart one, not Debbie Wasserman Shultz (@DWStweets.) Sanders himself blasted the DNC and Wasserman Schultz in interviews earlier Sunday, demanding her resignation as party chairwoman.\", \"id\": \"allsides_1969_800_15_Fox News_20_32\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": 1, \"from\": 60, \"to\": 77, \"sentence\": \"President Obama and Clinton both issued statements thanking Wasserman Schultz for her service.\", \"id\": \"allsides_1969_800_20_Wasserman Schultz_60_77\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": -1, \"from\": 12, \"to\": 29, \"sentence\": \"Others from Wasserman Schultz herself contained very strong language, raising questions about her status as an ostensibly neutral party official.\", \"id\": \"allsides_1969_800_27_Wasserman Schultz_12_29\"}\n{\"mention\": \"Sanders\", \"polarity\": -1, \"from\": 14, \"to\": 21, \"sentence\": \"Responding to Sanders’ complaints the party hasn’t been fair to him, she wrote to a staffer in an April email: “Spoken like someone who has never been a member of the Democratic Party and has no understanding of what we do.”\", \"id\": \"allsides_1969_800_28_Sanders'_14_21\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 143, \"to\": 146, \"sentence\": \"The announcement came just hours after reports first surfaced that Wasserman Schultz may be denied a speaking role at the convention, and that she would not be presiding -- a decision apparently made under pressure from the Clinton campaign and the White House.\", \"id\": \"allsides_1969_800_7_Vice Chairwoman Donna Brazile_143_146\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": -1, \"from\": 21, \"to\": 38, \"sentence\": \"In a statement after Wasserman Schultz’s resignation, Sanders said the DNC needs new leadership.\", \"id\": \"allsides_1972_801_27_Debbie Wasserman Schultz (Fla.) to resign_21_38\"}\n{\"mention\": \"Tim Kaine\", \"polarity\": 1, \"from\": 24, \"to\": 33, \"sentence\": \"Hillary Clinton Selects Tim Kaine, a Popular Senator From a Swing State, as Running Mate\", \"id\": \"allsides_1973_802_0_Mr. Kaine_24_33\"}\n{\"mention\": \"Tampa\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"At a rally in Tampa on Friday evening, Mrs. Clinton blasted the bleak vision of America presented by her Republican rival.\", \"id\": \"allsides_1973_802_20_Tampa_14_19\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 40, \"to\": 47, \"sentence\": \"The Trump campaign quickly labeled Mrs. Clinton’s new running mate “Corrupt Kaine,” pointing to lavish gifts he had received during his years as governor and lieutenant governor of Virginia.\", \"id\": \"allsides_1973_802_35_Clinton_40_47\"}\n{\"mention\": \"Tim Kaine\", \"polarity\": -1, \"from\": 61, \"to\": 70, \"sentence\": \"The Bernie Sanders supporters are furious with the choice of Tim Kaine, who represents the opposite of what Bernie stands for.\", \"id\": \"allsides_1974_802_1_Dem VP Pick Kaine_63_72\"}\n{\"mention\": \"Bernie\", \"polarity\": 1, \"from\": 108, \"to\": 114, \"sentence\": \"The Bernie Sanders supporters are furious with the choice of Tim Kaine, who represents the opposite of what Bernie stands for.\", \"id\": \"allsides_1974_802_1_Bernie_110_116\"}\n{\"mention\": \"Tim Kaine\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Tim Kaine is, and always has been, owned by the banks.\", \"id\": \"allsides_1974_802_3_Dem VP Pick Kaine_0_9\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"She asked, if Trump were president, “Will a woman make the same as a man and will I get to choose what I do with my body?”\", \"id\": \"allsides_1975_803_18_Ivanka Trump_14_19\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 22, \"to\": 27, \"sentence\": \"She specifically said Trump will fight to change laws in order to address these problems for working women.\", \"id\": \"allsides_1975_803_35_Ivanka Trump_22_27\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 167, \"to\": 170, \"sentence\": \"That stance is earning high praise from liberals who have been arguing for years the federal government should get involved to regulate the cost of childcare. i mean, she basically outlined Hillary Clinton's pro-working family's policy agenda... https://t.co/STm1bAK2Kg Great speech from Ivanka.\", \"id\": \"allsides_1976_803_3_Ivanka Trump's_167_170\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 35, \"to\": 38, \"sentence\": \"But then, perhaps there’s truth to his absurd promises: When the crisis is invented, the solution is simpler.\", \"id\": \"allsides_1978_804_61_Donald Trump_35_38\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 91, \"to\": 98, \"sentence\": \"“With Donald Trump and Mike Pence, America’s ready for a comeback after almost a decade of Clinton-Obama failures.”\", \"id\": \"allsides_1979_804_31_Clinton_91_98\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 1, \"from\": 6, \"to\": 18, \"sentence\": \"“With Donald Trump and Mike Pence, America’s ready for a comeback after almost a decade of Clinton-Obama failures.”\", \"id\": \"allsides_1979_804_31_Trump_6_18\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 88, \"to\": 95, \"sentence\": \"Chris Christie spoke on the second night of the convention, he ticked off criticisms of Clinton, asking the crowd of she was “guilty or not guilty.”\", \"id\": \"allsides_1986_807_3_Anti-Clinton_88_95\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 110, \"to\": 125, \"sentence\": \"The other striking thing from last night: While Patricia Smith, whose son was killed in Benghazi, was blaming Hillary Clinton on stage, Trump called in to Bill O’Reilly—essentially preempting his own convention for those few minutes.\", \"id\": \"allsides_1987_808_26_Hillary Clinton_110_125\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 44, \"to\": 49, \"sentence\": \"In March 2012, at a meeting in South Korea, Obama declared about Erdogan “that we find ourselves in frequent agreement upon a wide range of issues… [and] because he has two daughters that are a little older than mine — they’ve turned out very well, so I’m always interested in his perspective on raising girls.”\", \"id\": \"allsides_1991_811_10_Obama_44_49\"}\n{\"mention\": \"Erdogan\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Erdogan has pushed step-by-step create an Islamic state.\", \"id\": \"allsides_1991_811_11_Erdogan_0_7\"}\n{\"mention\": \"Erdogan\", \"polarity\": -1, \"from\": 154, \"to\": 161, \"sentence\": \"Obama entered power in 2009 hoping to use Turkey’s Islamist president to help remake politics in the Middle East — but the wished-for alliance crashed as Erdogan’s Islamist government became more radical year by year.\", \"id\": \"allsides_1991_811_6_Erdogan_154_161\"}\n{\"mention\": \"Erdogan\", \"polarity\": 0, \"from\": 71, \"to\": 78, \"sentence\": \"So, too, have street demonstrators and leading politicians — including Erdogan opponents.\", \"id\": \"allsides_1992_811_18_Erdogan_71_78\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 3, \"to\": 5, \"sentence\": \"If he is perceived as the defender of Turkish civilian government, his popularity could well soar.\", \"id\": \"allsides_1992_811_22_Erdogan_3_5\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 0, \"from\": 16, \"to\": 28, \"sentence\": \"Just into @CNN: Donald Trump has called Indiana Gov.\", \"id\": \"allsides_1998_814_12_Donald Trump_16_28\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 23, \"to\": 26, \"sentence\": \"Mike Pence and offered him the vice-presidential slot on his ticket.\", \"id\": \"allsides_1998_814_13_Donald Trump_23_26\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 113, \"to\": 118, \"sentence\": \"Patricia Murphy wrote, “In addition to testing the men's chemistry together, Trump was reportedly impressed with Pence's calm demeanor, his experience on Capitol Hill and as a governor, and Pence's potential to assist Trump in governing, should the ticket win in November.”\", \"id\": \"allsides_1998_814_20_Mike Pence_113_118\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 69, \"to\": 72, \"sentence\": \"Director James Comey's damning report on Clinton's email usage while she was secretary of state also didn't do her any favors.\", \"id\": \"allsides_1998_814_39_Hillary_69_72\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Pence, who twice considered running for president, is well regarded by conservatives and evangelicals around the country, earning plaudits recently from the likes of Sen.\", \"id\": \"allsides_1999_814_10_Mike Pence_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 7, \"to\": 12, \"sentence\": \"Before Trump even made his pick, he had at least one detractor in prominent conservative radio host and former Red State editor Erick Erickson, who chided Pence on Twitter.\", \"id\": \"allsides_1999_814_32_Donald Trump_7_12\"}\n{\"mention\": \"Pence\", \"polarity\": -1, \"from\": 155, \"to\": 160, \"sentence\": \"Before Trump even made his pick, he had at least one detractor in prominent conservative radio host and former Red State editor Erick Erickson, who chided Pence on Twitter.\", \"id\": \"allsides_1999_814_32_Mike Pence_155_160\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 1, \"to\": 4, \"sentence\": \"“She may have got out over her skis a little bit and more forthright and political than she should have been.\", \"id\": \"allsides_2002_816_27_Chris Murphy, D-Conn_1_4\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump’s hands, of course, are far from clean on the matter of judicial independence.\", \"id\": \"allsides_2003_816_18_Donald Trump_0_9\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 122, \"to\": 134, \"sentence\": \"In an interview with The Times published Sunday, Justice Ginsburg said, “I can’t imagine what the country would be — with Donald Trump as our president,” joking that if her husband were alive, he might have said, “It’s time for us to move to New Zealand.”\", \"id\": \"allsides_2003_816_3_Donald Trump_122_134\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 11, \"to\": 18, \"sentence\": \"He praised Clinton’s proposal in strong, unambiguous terms ― describing it as “an extremely important initiative” and predicting that “it will save lives, it will ease suffering, it will improve health care in America, and it will cut health care costs.”\", \"id\": \"allsides_2007_818_12_Clinton_11_18\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He praised Clinton’s proposal in strong, unambiguous terms ― describing it as “an extremely important initiative” and predicting that “it will save lives, it will ease suffering, it will improve health care in America, and it will cut health care costs.”\", \"id\": \"allsides_2007_818_12_Sanders_0_2\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Sanders told reporters that the two campaigns “are coming closer and closer together in trying to address the major issues facing this country.”\", \"id\": \"allsides_2008_818_19_Sanders_0_7\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 55, \"to\": 70, \"sentence\": \"(AP) — In another nod to primary rival Bernie Sanders, Hillary Clinton is proposing to increase federal money for community health centers and outlining steps to expand access to health care across the nation.\", \"id\": \"allsides_2008_818_2_Hillary Clinton_55_70\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 118, \"to\": 133, \"sentence\": \"He repeated the statements during a Wednesday morning press conference saying, “I think the DNI, Clapper, should deny Hillary Clinton access to classified information during this campaign, given how she so recklessly handled classified information.\", \"id\": \"allsides_2015_821_3_Hillary_118_133\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 17, \"to\": 24, \"sentence\": \"Comey criticized Clinton and her staff for being “extremely careless” in handling classified information, noting that 110 of Clinton’s emails contained classified information at the time they were sent and received.\", \"id\": \"allsides_2017_821_3_presumptive Democratic nominee Hillary Clinton_17_24\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 27, \"to\": 42, \"sentence\": \"Read more: Why the FBI Let Hillary Clinton Off the Hook Ryan also sent a letter to Comey, requesting that he release all of the findings from the bureau’s investigation into Clinton’s emails, saying “there are simply too many unanswered questions.”\", \"id\": \"allsides_2017_821_8_Hillary Clinton_27_42\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 13, \"to\": 20, \"sentence\": \"FBI’s Comey: Clinton 'extremely careless' about emails, but bureau will not advise criminal charges\", \"id\": \"allsides_2020_823_0_Clinton_13_20\"}\n{\"mention\": \"Comey\", \"polarity\": 0, \"from\": 288, \"to\": 293, \"sentence\": \"“There is evidence to support a conclusion that any reasonable person in Secretary Clinton’s position, or in the position of those government employees with whom she was corresponding about these matters, should have known that an unclassified system was no place for that conversation,” Comey said.\", \"id\": \"allsides_2020_823_23_FBI Director James Comey_288_293\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 139, \"to\": 142, \"sentence\": \"In the wake of that report, Trump, the presumptive Republican presidential nominee, stepped up his criticism of her email actions and said she belongs in “jail.”\", \"id\": \"allsides_2020_823_27_Clinton_139_142\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 56, \"to\": 63, \"sentence\": \"\\\"Although we did not find clear evidence that Secretary Clinton or her colleagues intended to violate laws governing the handling of classified information, there is information that they were extremely careless in their handling of very sensitive, highly classified information,\\\" Comey told reporters in Washington, D.C., noting that the probe has found that the former secretary of state used several different email servers and numerous devices during her time in office.\", \"id\": \"allsides_2021_823_2_Clinton_56_63\"}\n{\"mention\": \"Comey\", \"polarity\": 0, \"from\": 31, \"to\": 36, \"sentence\": \"Story Continued Below Even so, Comey added later, “Although there is evidence of potential violations of the statutes regarding the handling of classified information, our judgment is that no reasonable prosecutor would bring such a case.\", \"id\": \"allsides_2021_823_3_Bernie Sanders’_31_36\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 146, \"to\": 153, \"sentence\": \"Longtime Obama aide and strategist David Axelrod on Tuesday morning tweeted that Comey’s statement in which he recommended no charges but rebuked Clinton for carelessness “is about [the] best result she could get.”\", \"id\": \"allsides_2021_823_74_Clinton_146_153\"}\n{\"mention\": \"Ernst\", \"polarity\": 0, \"from\": 73, \"to\": 78, \"sentence\": \"Trump spent time with Pence and his family on Sunday and was due to meet Ernst in New Jersey on Monday.\", \"id\": \"allsides_2024_824_3_Ernst_73_78\"}\n{\"mention\": \"Pence\", \"polarity\": 0, \"from\": 140, \"to\": 145, \"sentence\": \"Cotton, 39 and thought by some a likely post-Trump presidential candidate in 2020, has not been as often named among potential Trump VPs as Pence and Ernst.\", \"id\": \"allsides_2024_824_6_Pence_140_145\"}\n{\"mention\": \"Lincoln\", \"polarity\": 1, \"from\": 44, \"to\": 51, \"sentence\": \"It is remarkable that there was a time when Lincoln’s idea, now so central to our American mindset, was not dominant.\", \"id\": \"allsides_2025_825_21_Abraham Lincoln_44_51\"}\n{\"mention\": \"the Founders\", \"polarity\": 1, \"from\": 16, \"to\": 28, \"sentence\": \"We must do what the Founders did, and what Lincoln did in his own time, and fight against the insidious notion that those words mean other than what they say.\", \"id\": \"allsides_2025_825_32_the Founders_16_28\"}\n{\"mention\": \"Lincoln\", \"polarity\": 1, \"from\": 43, \"to\": 50, \"sentence\": \"We must do what the Founders did, and what Lincoln did in his own time, and fight against the insidious notion that those words mean other than what they say.\", \"id\": \"allsides_2025_825_32_Abraham Lincoln_43_50\"}\n{\"mention\": \"Lincoln\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Lincoln meant this literally.\", \"id\": \"allsides_2025_825_4_Abraham Lincoln_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 27, \"to\": 32, \"sentence\": \"\\\"What is distasteful about Trump is not that he offends old-fashioned American values,\\\" wrote Mother Jones’s Tim Murphy in one typical reaction.\", \"id\": \"allsides_2026_825_3_Donald Trump_27_32\"}\n{\"mention\": \"\\\"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"\\\"Trump is distasteful because he taps into certain old-fashioned American values — nativism, brash tough talk, slow-burning authoritarianism; family dynasties — that have played a not-inconsequential role throughout our history.\\\"\", \"id\": \"allsides_2026_825_4_Donald Trump_0_6\"}\n{\"mention\": \"\\\" Becker\", \"polarity\": 0, \"from\": 193, \"to\": 201, \"sentence\": \"\\\"It taught that beneath all local and temporary diversity, beneath the superficial traits and talents that distinguish men and nations, all men are equal in the possession of a common humanity,\\\" Becker says.\", \"id\": \"allsides_2026_825_55_Carl Becker_193_201\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 24, \"to\": 27, \"sentence\": \"\\\"It was unfortunate and she has admitted that the optics were not good in retrospect,\\\" said Carl Tobias, a law professor at the University of Richmond, adding that she had mitigated some of the fallout by deferring the decision on filing charges to Comey and career prosecutors.\", \"id\": \"allsides_2032_828_36_former attorney general Janet Reno_24_27\"}\n{\"mention\": \"Lynch\", \"polarity\": -1, \"from\": 58, \"to\": 63, \"sentence\": \"After Widespread Criticism for Meeting With Bill Clinton, Lynch to Step Back in Email Probe\", \"id\": \"allsides_2034_828_0_Lynch_58_63\"}\n{\"mention\": \"Bill Clinton\", \"polarity\": -1, \"from\": 44, \"to\": 56, \"sentence\": \"After Widespread Criticism for Meeting With Bill Clinton, Lynch to Step Back in Email Probe\", \"id\": \"allsides_2034_828_0_Bill Clinton_44_56\"}\n{\"mention\": \"Johnson\", \"polarity\": 0, \"from\": 105, \"to\": 112, \"sentence\": \"She added that influential right-wing media barons Rupert Murdoch and Paul Dacre \\\"instinctively dislike\\\" Johnson.\", \"id\": \"allsides_2036_829_16_Boris Johnson_105_112\"}\n{\"mention\": \"Boris\", \"polarity\": -1, \"from\": 150, \"to\": 155, \"sentence\": \"Main public face of Brexit makes shock announcement hours after his key ally Michael Gove launched his own campaign Live coverage of the fallout from Boris Johnson’s announcement Heather Stewart and  Jessica Elgot Thu 30 Jun 2016 13.20 BST First published on Thu 30 Jun 2016 12.02 BST Boris Johnson has unexpectedly ruled himself out as a candidate for Britain’s next prime minister, after the justice secretary, Michael Gove, sent shockwaves through Westminster with a last-minute bid for the Conservative leadership.\", \"id\": \"allsides_2037_829_1_Boris_152_157\"}\n{\"mention\": \"Farage\", \"polarity\": -1, \"from\": 54, \"to\": 60, \"sentence\": \"Speaking to the host of ITV's \\\"Good Morning Britain,\\\" Farage called one of the \\\"leave\\\" campaign's biggest promises a \\\"mistake,\\\" though he distanced himself from the decision to make the promise in the first place.\", \"id\": \"allsides_2043_832_8_Nigel Farage_54_60\"}\n{\"mention\": \"Britain\", \"polarity\": 0, \"from\": 44, \"to\": 51, \"sentence\": \"Speaking to the host of ITV's \\\"Good Morning Britain,\\\" Farage called one of the \\\"leave\\\" campaign's biggest promises a \\\"mistake,\\\" though he distanced himself from the decision to make the promise in the first place.\", \"id\": \"allsides_2043_832_8_Britain_44_51\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 31, \"to\": 36, \"sentence\": \"Clinton Opens 12-Point Lead on Trump as Two-Thirds See Him as Biased (POLL)\", \"id\": \"allsides_2045_833_0_Trump_31_36\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton, further, is now leading among young adults, a group in which Trump was surprisingly competitive last month.\", \"id\": \"allsides_2045_833_59_Clinton_0_7\"}\n{\"mention\": \"presumptive Democratic presidential nominee Hillary Clinton\", \"polarity\": 1, \"from\": 17, \"to\": 76, \"sentence\": \"A new poll finds presumptive Democratic presidential nominee Hillary Clinton with a towering lead over her likely Republican counterpart, Donald Trump.\", \"id\": \"allsides_2047_833_1_presumptive Democratic presidential nominee Hillary Clinton_19_78\"}\n{\"mention\": \"the Supreme Court\", \"polarity\": 0, \"from\": 196, \"to\": 213, \"sentence\": \"Mr. Obama said the court’s immigration ruling was a stark reminder of the consequences of Republicans’ refusal to consider Judge Merrick B. 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chamber gallery — and apologized to him for missing pizza night, while telling him: “I hope that you’ll understand someday why we’re doing this.”\", \"id\": \"allsides_2082_847_53_Murphy_30_36\"}\n{\"mention\": \"his young son Owen\", \"polarity\": 1, \"from\": 54, \"to\": 72, \"sentence\": \"At one point Wednesday night, Murphy looked up toward his young son Owen — seated in the chamber gallery — and apologized to him for missing pizza night, while telling him: “I hope that you’ll understand someday why we’re doing this.”\", \"id\": \"allsides_2082_847_53_his young son Owen_54_72\"}\n{\"mention\": \"Murphy\", \"polarity\": 1, \"from\": 72, \"to\": 78, \"sentence\": \"When asked by another senator how he was feeling just before 7:30 p.m., Murphy said rehabilitation from a back injury in his 20s had helped him build up endurance.\", \"id\": \"allsides_2083_847_20_Murphy_72_78\"}\n{\"mention\": \"his\", \"polarity\": 0, \"from\": 94, \"to\": 97, \"sentence\": \"But they have not found 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after the Civil War, that abolished slavery and gave broader rights to African-Americans.\", \"id\": \"allsides_208_85_35_African-Americans_222_239\"}\n{\"mention\": \"“crooked Hillary\", \"polarity\": -1, \"from\": 45, \"to\": 61, \"sentence\": \"Trump, meanwhile, continued calling Clinton, “crooked Hillary” and referred to her ongoing email scandal.\", \"id\": \"allsides_2096_852_20_“crooked Hillary_45_61\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump, meanwhile, continued calling Clinton, “crooked Hillary” and referred to her ongoing email scandal.\", \"id\": \"allsides_2096_852_20_Trump_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 154, \"to\": 159, \"sentence\": \"\\\"I am ready to get in this fight and work my heart out for Hillary Clinton to become the next president of the United States and to make sure that Donald Trump never gets anyplace close to the White House,\\\" the Massachusetts senator said on MSNBC's 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Sanders_6_13\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 37, \"to\": 44, \"sentence\": \"\\\"Help us organize in all 50 states,\\\" Clinton concluded.\", \"id\": \"allsides_2111_859_10_Clinton_37_44\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 81, \"to\": 84, \"sentence\": \"\\\"We all owe so much to those who came before and tonight belongs to all of you,\\\" she continued.\", \"id\": \"allsides_2111_859_4_Clinton_81_84\"}\n{\"mention\": \"\\\"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"\\\"Trump has proven himself very thin-skinned, so poking him and focusing on his intemperance and intolerance can draw new eruptions and produce unexpected rewards,\\\" said David Axelrod, Obama's longtime advisor.\", \"id\": \"allsides_2112_859_39_Donald Trump_0_6\"}\n{\"mention\": \"\\\"Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 13, \"sentence\": \"\\\"Donald Trump is temperamentally unfit to be president and commander in chief.\", \"id\": \"allsides_2112_859_41_Donald Trump_0_13\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 80, \"to\": 87, \"sentence\": \"\\\"If we stand together, we will rise together because we are stronger together,\\\" Clinton said.\", \"id\": \"allsides_2112_859_52_Hillary Clinton_80_87\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 159, \"to\": 166, \"sentence\": \"At a fundraising concert in Los Angeles on Monday where celebrity supporters included Stevie Wonder, Ricky Martin, Cher, Magic Johnson and Christina Aguilera, Clinton told the crowd: “We’re going to come out of the primary even stronger to take on Donald Trump.\", \"id\": \"allsides_2113_860_20_Clinton_159_166\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 214, \"to\": 221, \"sentence\": \"Hillary Clinton has earned enough delegates to clinch the Democratic presidential nomination, according to an Associated Press count released Monday night – an assessment swiftly challenged by primary rival Bernie Sanders and his campaign.\", \"id\": \"allsides_2114_860_1_Sanders_216_223\"}\n{\"mention\": \"Elliott\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Elliott said his grandmother was once a nanny to Ali's family.\", \"id\": \"allsides_2117_862_26_Elliott_0_7\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 41, \"to\": 43, \"sentence\": \"But it is hard to think of a moment when he was ever less than brave.\", \"id\": \"allsides_2118_862_7_Muhammad Ali: a life of bravery_41_43\"}\n{\"mention\": \"U.S.\", \"polarity\": 0, \"from\": 120, \"to\": 124, \"sentence\": \"In an interview on CBS’ “Face the Nation,” Mr. Trump said his proposal to temporarily ban all Muslims from entering the U.S. could theoretically lead Muslim judges to single him out and treat him unfairly.\", \"id\": \"allsides_2119_863_2_U.S._120_124\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 43, \"to\": 52, \"sentence\": \"In an interview on CBS’ “Face the Nation,” Mr. Trump said his proposal to temporarily ban all Muslims from entering the U.S. could theoretically lead Muslim judges to single him out and treat him unfairly.\", \"id\": \"allsides_2119_863_2_Donald Trump_43_52\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump has come under intense fire — including from some fellow Republicans — for saying U.S. District Judge Gonzalo Curiel, who is of Mexican heritage, is biased against him.\", \"id\": \"allsides_2119_863_5_Donald Trump_0_9\"}\n{\"mention\": \"Tapper\", \"polarity\": 0, \"from\": 43, \"to\": 49, \"sentence\": \"This moment right here — with this look on Tapper's face — perfectly encapsulates the exchange.\", \"id\": \"allsides_2120_863_12_Jake Tapper_43_49\"}\n{\"mention\": \"TAPPER\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"TAPPER: If you are saying he cannot do his job because of his race, is that not the definition of racism?\", \"id\": \"allsides_2120_863_15_Jake Tapper_0_6\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 41, \"to\": 46, \"sentence\": \"Soon after, she offered this: \\\"Of course Trump doesn’t have answers to those questions.\", \"id\": \"allsides_2121_864_13_\\\"Donald Trump_41_46\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 105, \"to\": 110, \"sentence\": \"It certainly appeared to have calmed preternaturally skittish Democrats, who have looked on in horror as Trump has made a show of it in recent polls.\", \"id\": \"allsides_2121_864_22_\\\"Donald Trump_105_110\"}\n{\"mention\": \"It\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"It certainly appeared to have calmed preternaturally skittish Democrats, who have looked on in horror as Trump has made a show of it in recent polls.\", \"id\": \"allsides_2121_864_22_Thursday's speech_0_2\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump, he noted, had a unique ability to drive media coverage in ways that present practical challenges for the competition.\", \"id\": \"allsides_2121_864_29_\\\"Donald Trump_0_5\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 31, \"to\": 33, \"sentence\": \"“And I believe absolutely that he is not only unprepared to be president, he is temperamentally unfit to be president.\", \"id\": \"allsides_2122_864_28_Clinton_31_33\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Sanders has promoted raising the federal minimum wage from $7.25 an hour to $15 an hour, while Clinton has supported a Senate bill to raise it to $12 an hour while encouraging cities and other communities to go higher.\", \"id\": \"allsides_2123_864_24_rival Bernie Sanders_0_7\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 78, \"to\": 85, \"sentence\": \"Campaigning in Culver City on Friday at an organizing event geared for women, Clinton told about 500 cheering supporters that “if all goes well, I will have the great honor as of Tuesday to be the Democratic nominee for president.”\", \"id\": \"allsides_2123_864_27_Clinton_78_85\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 1, \"from\": 7, \"to\": 22, \"sentence\": \"(AP) — Hillary Clinton is keeping the heat on Donald Trump, saying “we are trying to elect a president, not a dictator.”\", \"id\": \"allsides_2123_864_2_Clinton_7_22\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 46, \"to\": 58, \"sentence\": \"(AP) — Hillary Clinton is keeping the heat on Donald Trump, saying “we are trying to elect a president, not a dictator.”\", \"id\": \"allsides_2123_864_2_Trump_46_58\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 15, \"to\": 17, \"sentence\": \"“And look what he’s doing now.\", \"id\": \"allsides_2123_864_7_Clinton_15_17\"}\n{\"mention\": \"Krongard\", \"polarity\": 0, \"from\": 8, \"to\": 16, \"sentence\": \"But, as Krongard indicated, the May 25 IG report clearly stated that Rice did not use personal email for government business.\", \"id\": \"allsides_2132_868_15_Krongard_8_16\"}\n{\"mention\": \"Krongard\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Krongard resigned from the IG position in December 2007 after accusations he blocked Iraq-related investigations, charges he denied.\", \"id\": \"allsides_2132_868_20_Krongard_0_8\"}\n{\"mention\": \"IG\", \"polarity\": 0, \"from\": 27, \"to\": 29, \"sentence\": \"Krongard resigned from the IG position in December 2007 after accusations he blocked Iraq-related investigations, charges he denied.\", \"id\": \"allsides_2132_868_20_IG_27_29\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 19, \"to\": 26, \"sentence\": \"He also challenged Clinton and State Department claims that the emails in question were “retroactively classified.”\", \"id\": \"allsides_2132_868_27_Clinton_19_26\"}\n{\"mention\": \"Krongard\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Krongard noted that during Clinton’s four-year term, from January 2009 to January 2013, there was no Senate-confirmed inspector general in place.\", \"id\": \"allsides_2132_868_6_Krongard_0_8\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 40, \"to\": 47, \"sentence\": \"Instead, the thrust of the criticism of Clinton is that the Bureau of Diplomatic Security and the Bureau of Information Resource Management were not asked permission by Clinton to use her private server.\", \"id\": \"allsides_2133_868_24_Clinton_40_47\"}\n{\"mention\": \"the Bureau of Diplomatic Security\", \"polarity\": -1, \"from\": 56, \"to\": 89, \"sentence\": \"Instead, the thrust of the criticism of Clinton is that the Bureau of Diplomatic Security and the Bureau of Information Resource Management were not asked permission by Clinton to use her private server.\", \"id\": \"allsides_2133_868_24_the Bureau of Diplomatic Security_56_89\"}\n{\"mention\": \"the primary race\", \"polarity\": 0, \"from\": 29, \"to\": 45, \"sentence\": \"Sanders continues to stay in the primary 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Connecticut Gov.\", \"polarity\": 0, \"from\": 0, \"to\": 33, \"sentence\": \"Barney Frank and Connecticut Gov.\", \"id\": \"allsides_2136_870_3_Barney Frank and Connecticut Gov._0_33\"}\n{\"mention\": \"it\", \"polarity\": 0, \"from\": 194, \"to\": 196, \"sentence\": \"The question of Mr. Frank’s and Mr. Malloy’s qualifications had been settled in January, when they were first appointed, Ms. Miller and Mr. Roosevelt wrote, and there is no mechanism to revisit it.\", \"id\": \"allsides_2137_870_12_it_194_196\"}\n{\"mention\": \"Mr. Deutsch\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Mr. Deutsch’s letter indicates that if necessary, Mr. Sanders will take his battle over the credentials of Mr. Frank and Mr. Malloy to the convention in Philadelphia.\", \"id\": \"allsides_2137_870_18_Mr. Sanders’s lawyer Brad Deutsch_0_11\"}\n{\"mention\": \"Mr. Deutsch\", \"polarity\": 0, \"from\": 204, \"to\": 215, \"sentence\": \"“Their criticisms of Senator Sanders have gone beyond 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\"allsides_214_87_18_Le Quéré_24_27\"}\n{\"mention\": \"the United States\", \"polarity\": 0, \"from\": 101, \"to\": 118, \"sentence\": \"She saw Macron’s video and, weary of short-term grants and worried about growing budget pressures in the United States, applied.\", \"id\": \"allsides_214_87_20_the United States_101_118\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 215, \"to\": 222, \"sentence\": \"Simon Rosenberg, a Democratic strategist and founder of the center-left thinktank New Democrat Network, wrote in a column this week that the California debate should proceed as initially planned between Clinton and Sanders.\", \"id\": \"allsides_2150_875_27_Bernie Sanders_215_222\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 105, \"to\": 112, \"sentence\": \"On ABC's \\\"Jimmy Kimmel Live,\\\" Trump said he enjoyed watching Clinton's increasingly heated sparring with Sanders.\", \"id\": \"allsides_2151_875_3_Donald Trump-Bernie Sanders_105_112\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He put down women based on their looks.\", \"id\": \"allsides_2152_876_26_Cameron Linton of Pittsburgh_0_2\"}\n{\"mention\": \"Presumptive Republican nominee Donald Trump\", \"polarity\": 1, \"from\": 0, \"to\": 43, \"sentence\": \"Presumptive Republican nominee Donald Trump has officially secured a majority of GOP delegates, giving him the \\\"magic number\\\" required to clinch the GOP nomination.\", \"id\": \"allsides_2154_876_1_Presumptive Republican nominee Donald Trump_0_45\"}\n{\"mention\": \"Wasserman Schultz\", \"polarity\": -1, \"from\": 0, \"to\": 17, \"sentence\": \"Wasserman Schultz has long been accused of favoritism by Bernie Sanders supporters, who claimed that her decision to schedule and limit Democratic debates was meant to protect Hillary Clinton.\", \"id\": \"allsides_2157_878_2_DNC chair Debbie Wasserman Schultz_0_17\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 39, \"to\": 46, \"sentence\": \"Clinton got to fill six positions, and Sanders chose five.\", \"id\": \"allsides_2159_878_13_Sanders_39_46\"}\n{\"mention\": \"Macron\", \"polarity\": 1, \"from\": 87, \"to\": 93, \"sentence\": \"In an address from the Elysée Palace, shortly after the U.S. president’s announcement, Macron urged scientists who were annoyed with the move to “come to France and work with us together” on climate policy-related research.\", \"id\": \"allsides_215_87_3_Emmanuel Macron_87_93\"}\n{\"mention\": \"Macron\", \"polarity\": -1, \"from\": 182, \"to\": 188, \"sentence\": \"> Sadiq Khan Tells Everyone Who Doesn’t Like Trump: Move to London https://t.co/YcvLk0Khh0 pic.twitter.com/XgR0ypbt6B > — Breitbart London (@BreitbartLondon) November 17, 2016 While Macron’s attacks on Trump over the Paris agreement were hailed by an admiring French and international media, the Guardian reported that the French leader’s “tough stance” may have “backfired”, and likely prompted the U.S. leader to remind people he “was elected to serve the citizens of Pittsburgh — not Paris” Speaking in the Rose Garden after his announcement that the U.S. would be leaving the Paris agreement, President Trump said that the accord signed by the Obama administration in 2015 without the consent of Congress “disadvantages the United States to the exclusive benefit of other countries” “In order to fulfill my solemn duty to protect America and its citizens, the United States will withdraw from the Paris Climate Accord,” Trump said at the time, explaining the agreement would have left American taxpayers having to “absorb the cost in terms of lost jobs, lower wages, shuttered factories, and vastly diminished economic production.”\", \"id\": \"allsides_215_87_6_Emmanuel Macron_182_188\"}\n{\"mention\": \"Facebook CEO Mark Zuckerberg\", \"polarity\": 0, \"from\": 0, \"to\": 28, \"sentence\": \"Facebook CEO Mark Zuckerberg arranged a meeting with conservative figures last week to talk out the issue — a 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media breathlessly following each twist and tweet.\", \"id\": \"allsides_2350_954_12_\\\\--Ted Cruz_117_121\"}\n{\"mention\": \"His\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"His identity is defined by his desire to rise above the fray.\", \"id\": \"allsides_2350_954_34_President Obama_0_3\"}\n{\"mention\": \"\\\\--Ted Cruz\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"\\\\--Ted Cruz is the most unlikable man in Washington, maybe the world, and such a nutty right-winger he’d probably like to shut down the government forever.\", \"id\": \"allsides_2350_954_9_\\\\--Ted Cruz_0_11\"}\n{\"mention\": \"Democratic frontrunner Hillary Clinton\", \"polarity\": 1, \"from\": 0, \"to\": 38, \"sentence\": \"Democratic frontrunner Hillary Clinton chimed in on Twitter, saying, \\\"Just when you thought it couldn't get worse.\", \"id\": \"allsides_2351_955_14_Democratic frontrunner Hillary Clinton_0_38\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 1, \"to\": 3, 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\"id\": \"allsides_2407_976_159_Clinton_12_19\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 20, \"to\": 27, \"sentence\": \"But polls also show Clinton far ahead in Florida and in North Carolina, setting up the possibility of an outcome parallel to last week’s contests, when Sanders scored a narrow and surprising victory in Michigan, yet Clinton came away with a widened lead in the delegate count because of her resounding victory in Mississippi,” John Wagner and Jose A. 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Rubio gets 10 of the delegates and Kasich takes 9.\", \"id\": \"allsides_2412_978_3_Rubio_0_11\"}\n{\"mention\": \"Ted Cruz (Tex.)\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"Ted Cruz (Tex.) trailed by substantial margins.\", \"id\": \"allsides_2412_978_9_Ted Cruz (Tex.)_0_15\"}\n{\"mention\": \"Carson\", \"polarity\": 1, \"from\": 19, \"to\": 25, \"sentence\": \"The endorsement by Carson, who last week suspended his campaign for the Republican presidential nomination, is perhaps the most high-profile nod for Trump since New Jersey Gov.\", \"id\": \"allsides_2416_981_2_Ben Carson_19_25\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He’s actually a very intelligent man who cares deeply about America,\\\" Carson said.\", \"id\": \"allsides_2417_981_16_Donald Trump_0_2\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 76, \"to\": 81, \"sentence\": \"Carson also laid out his argument for the party and country to unify around Trump 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\"sentence\": \"The fact that Clinton and Sanders made such a promise at all shows just how influential those advocacy efforts have been.\", \"id\": \"allsides_2420_983_23_Clinton_14_21\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 93, \"to\": 100, \"sentence\": \"And on Wednesday night, the businessman was the recipient of criticism from both Clinton and Sanders.\", \"id\": \"allsides_2420_983_34_Sanders_93_100\"}\n{\"mention\": \"Sanders\", \"polarity\": -1, \"from\": 29, \"to\": 36, \"sentence\": \"Clinton at one point accused Sanders of supporting legislation that would have led to indefinite detention of people facing deportation, and for standing with Minutemen vigilantes.\", \"id\": \"allsides_2422_983_21_Bernie Sanders_29_36\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 0, \"from\": 42, \"to\": 57, \"sentence\": \"MIAMI -- Fighting for Florida and beyond, Hillary Clinton and Bernie Sanders tangled in an intense debate Wednesday night over who's the true 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201, \"to\": 242, \"sentence\": \"Mr. Flanagan, 41, who went by the name Bryce Williams in recent years, had not been convicted of a crime or adjudicated mentally ill, so he apparently passed a background check in June, when he bought the Glock 19 handgun used in the killings.\", \"id\": \"allsides_2937_1199_23_the Glock 19 handgun used in the killings_201_242\"}\n{\"mention\": \"Biden\", \"polarity\": 1, \"from\": 29, \"to\": 34, \"sentence\": \"And a Quinnipiac Poll showed Biden running strong in head-to-head match-ups with Republican candidates in key states.\", \"id\": \"allsides_2946_1204_12_Biden_29_34\"}\n{\"mention\": \"Warren\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Warren has so far decline.\", \"id\": \"allsides_2946_1204_4_Warren_0_6\"}\n{\"mention\": \"Clinton\", \"polarity\": 0, \"from\": 87, \"to\": 94, \"sentence\": \"Earlier this year, campaign-watchers focused on Warren and whether she would challenge Clinton, prompting a vibrant \\\"Draft 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\"allsides_2953_1207_39_Former president Jimmy Carter_18_30\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 22, \"to\": 25, \"sentence\": \"Bar and I are wishing him the very best as he fights the good fight.\", \"id\": \"allsides_2953_1207_41_Former president Jimmy Carter_22_25\"}\n{\"mention\": \"Carter\", \"polarity\": 1, \"from\": 38, \"to\": 44, \"sentence\": \"In a frank discussion with reporters, Carter said he is “in the hands of God” and feels “prepared for anything that comes.”\", \"id\": \"allsides_2954_1207_4_Jimmy Carter_38_44\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 60, \"to\": 67, \"sentence\": \"Unlike his key Democratic opponent whom he refuses to bash, Sanders appears both honest and trustworthy.\", \"id\": \"allsides_2967_1214_2_Bernie Sanders'_60_67\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Obama wanted to be a Reagan of the left, a \\\"transformative\\\" president who moved the magnetic poles of 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\"allsides_297_119_23_(AP) Conyers, 88, the longest-serving House member_0_51\"}\n{\"mention\": \"Carly\", \"polarity\": 1, \"from\": 1, \"to\": 6, \"sentence\": \"“Carly obviously struck a sweet spot with politically engaged seniors during the first debate.”\", \"id\": \"allsides_2981_1219_12_Carly_1_6\"}\n{\"mention\": \"Carly\", \"polarity\": 1, \"from\": 26, \"to\": 31, \"sentence\": \"“For those of us who know Carly, her dominating performance was no surprise,” Anna Epstein, press secretary for Fiorina’s campaign told TheBlaze.\", \"id\": \"allsides_2981_1219_5_Carly_26_31\"}\n{\"mention\": \"Donald Trump's\", \"polarity\": -1, \"from\": 0, \"to\": 14, \"sentence\": \"Donald Trump's war on Megyn Kelly\", \"id\": \"allsides_2983_1220_0_Donald Trump's_0_14\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump’s spat with Fox News began after Kelly asked him during the debate about disparaging comments he had made towards women in the past.\", \"id\": \"allsides_2984_1220_9_Real estate tycoon Donald Trump_0_5\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 78, \"to\": 82, \"sentence\": \"But, Kasich is popular with moderates who are skittish about electing another Bush, and this debate allowed him to reach a bigger audience.\", \"id\": \"allsides_2985_1221_28_Bush_78_82\"}\n{\"mention\": \"Kasich\", \"polarity\": 1, \"from\": 5, \"to\": 11, \"sentence\": \"But, Kasich is popular with moderates who are skittish about electing another Bush, and this debate allowed him to reach a bigger audience.\", \"id\": \"allsides_2985_1221_28_John Kasich_5_11\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 6, \"to\": 8, \"sentence\": \"Maybe he really is simply rusty.\", \"id\": \"allsides_2985_1221_32_Bush_6_8\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 4, \"to\": 6, \"sentence\": \"Did he make any great errors?\", \"id\": \"allsides_2987_1221_9_Jeb Bush_4_6\"}\n{\"mention\": \"the next president\", \"polarity\": 0, 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\"to\": 65, \"sentence\": \"Democratic National Committee Chairwoman Debbie Wasserman Schultz responded to Mr. Walker’s announcement by saying he’s “already brought the worst of Washington to Wisconsin” and that he has “the wrong priorities for America.”\", \"id\": \"allsides_3047_1246_16_Democratic National Committee Chairwoman Debbie Wasserman Schultz_0_65\"}\n{\"mention\": \"Walker\", \"polarity\": -1, \"from\": 118, \"to\": 124, \"sentence\": \"“To promote adherence to his rigid partisan views and to please the special interests that have backed his campaigns, Walker has pit the people of Wisconsin against each other in contentious ideological fights,” Ms. Wasserman Schultz said in a statement.\", \"id\": \"allsides_3047_1246_17_Mr. Walker_118_124\"}\n{\"mention\": \"Scott Walker\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Scott Walker announced Monday he is running for president in 2016, touting a combination of policy pursuits and electoral successes in his home 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Tweets: ‘Don’t Get to Pick and Choose’ When Harassment Matters https://t.co/RgOLCzaHjz pic.twitter.com/ko90tRse0D What Al Franken did was totally inappropriate, but @realDonaldTrump has no right criticize.\", \"id\": \"allsides_305_123_37_Franken_242_252\"}\n{\"mention\": \"Bill Cosby\", \"polarity\": -1, \"from\": 0, \"to\": 10, \"sentence\": \"Bill Cosby admitted to drugging women to have sex, rape accusers say they are vindicated\", \"id\": \"allsides_3067_1256_0_Bill Cosby_0_10\"}\n{\"mention\": \"Cosby\", \"polarity\": -1, \"from\": 94, \"to\": 99, \"sentence\": \"Click here to subscribe to FOX411’s YouTube channel Attorneys for some of the women now suing Cosby seized on the testimony as powerful evidence that what they have been saying all along is true: the comedian drugged and raped women.\", \"id\": \"allsides_3067_1256_12_Bill Cosby_94_99\"}\n{\"mention\": \"Mr. Cosby\", \"polarity\": -1, \"from\": 28, \"to\": 37, \"sentence\": \"\\\"This admission is one that Mr. Cosby has 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\"allsides_3069_1256_51_President Obama_59_74\"}\n{\"mention\": \"Twitter\", \"polarity\": 0, \"from\": 30, \"to\": 37, \"sentence\": \"Mr. Trump has said nothing on Twitter about Mr. Moore, who has been abandoned by many national Republicans.\", \"id\": \"allsides_307_123_35_Twitter_30_37\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 26, \"to\": 35, \"sentence\": \"A typical politician with Mr. Trump’s history would stay far away from discussing someone else’s behavior lest it dredge his own back into the spotlight.\", \"id\": \"allsides_307_123_8_Mr. Trump_26_35\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 7, \"to\": 16, \"sentence\": \"But as Mr. Trump has shown repeatedly during his 10-month presidency, he is rarely deterred by conventional political wisdom even as he leaves it to his staff to fend off the cries of hypocrisy.\", \"id\": \"allsides_307_123_9_Mr. Trump_7_16\"}\n{\"mention\": \"Breyer\", \"polarity\": 0, \"from\": 35, \"to\": 41, 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Yes https://t.co/TIoytO15Ca pic.twitter.com/TjkBS0mbB8 She said that when Perez won the party post early this year, “the very first conversation I had with him [was] to say, you have got to put together a Democratic Party in which everybody can have confidence that the party is working for Democrats, rather than Democrats are working for the party.”\", \"id\": \"allsides_375_151_6_Elizabeth Warren_0_16\"}\n{\"mention\": \"Cassidy\", \"polarity\": 0, \"from\": 114, \"to\": 121, \"sentence\": \"Maness was a U.S. Senate candidate in Louisiana’s jungle primary, campaigning against both now Senator-elect Bill Cassidy and outgoing Democratic Sen.\", \"id\": \"allsides_3761_1555_41_Cassidy_114_121\"}\n{\"mention\": \"Maness\", \"polarity\": 1, \"from\": 21, \"to\": 27, \"sentence\": \"During the campaign, Maness showed he’s willing to criticize fellow Republicans when he perceives them to be wrong on race.\", \"id\": \"allsides_3761_1555_51_Rob Maness_21_27\"}\n{\"mention\": \"fellow 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\"to\": 59, \"sentence\": \"A month ago, women favored Obama over Romney on the economy 56 percent to 40 percent.\", \"id\": \"allsides_6094_2617_30_the economy_48_59\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 4, \"to\": 9, \"sentence\": \"For Obama it is the natural urge to explain what he has done on foreign policy.\", \"id\": \"allsides_6104_2622_15_Obama_4_9\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 4, \"to\": 10, \"sentence\": \"For Romney it is the natural urge to prove he is competent on this turf and not just a businessman.\", \"id\": \"allsides_6104_2622_16_Mitt Romney_4_10\"}\n{\"mention\": \"Mitt Romney\", \"polarity\": 1, \"from\": 27, \"to\": 38, \"sentence\": \"President Barack Obama and Mitt Romney have had two of the most memorable debates in modern presidential history, and they get together for the last one in Boca Raton, Fla. tonight.\", \"id\": \"allsides_6104_2622_2_Mitt Romney_27_38\"}\n{\"mention\": \"Obama\", \"polarity\": 0, 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is considered a leading candidate to succeed Hillary Clinton as secretary of state if Obama wins a second term.\", \"id\": \"allsides_6105_2622_34_Romney_1_3\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 43, \"to\": 46, \"sentence\": \"And following the second debate, Obama had his best day of fundraising ever, including the 2008 campaign.\", \"id\": \"allsides_6106_2623_11_Mitt Romney_43_46\"}\n{\"mention\": \"the president\", \"polarity\": -1, \"from\": 58, \"to\": 71, \"sentence\": \"Romney has scored points on foreign policy by criticizing the president for not quickly and categorically ascribing the attack to terrorists.\", \"id\": \"allsides_6106_2623_17_Obama_58_71\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 4, \"to\": 9, \"sentence\": \"The Obama campaign immediately shot back, outlining the president’s pledges and accusing Romney of “empty promises, sketchy math, and blatant falsehood “Mitt Romney’s spent the last month hiding his true positions from the American people to win votes, but the truth is he’d take us back to the same failed policies that devastated the middle class in the first place,” campaign spokesman Danny Kanner said in a statement.\", \"id\": \"allsides_6107_2623_27_Obama_4_9\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 1, \"to\": 7, \"sentence\": \"“Romney is a man with a plan.\", \"id\": \"allsides_6107_2623_5_Romney_1_7\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 22, \"to\": 27, \"sentence\": \"NEW YORK –  President Obama and Mitt Romney squeezed a comedy break in between debates last night, drawing laughs at a New York charity dinner that's long been a required stop for anyone trying to capture the White House.\", \"id\": \"allsides_6108_2624_1_Obama_24_29\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 59, \"to\": 65, \"sentence\": \"Obama said he has been preparing for the final debate with Romney on Monday, which will focus on foreign policy.\", \"id\": \"allsides_6108_2624_21_Romney_59_65\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 50, \"to\": 55, \"sentence\": \"He said that in such tough campaigns, both he and Obama are lucky to have “one person who’s always in our corner.\", \"id\": \"allsides_6109_2624_22_Obama_50_55\"}\n{\"mention\": \"Bannon\", \"polarity\": 0, \"from\": 7, \"to\": 13, \"sentence\": \"WATCH: Bannon says firing of Comey was the biggest mistake in modern political history.\", \"id\": \"allsides_610_243_15_Steve Bannon_7_13\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 6, \"to\": 11, \"sentence\": \"While Obama appealed to women Tuesday on the issues of fair pay and contraceptive care, Romney made the case that he wants to help women by helping the economy grow.\", \"id\": \"allsides_6118_2628_49_Obama_6_11\"}\n{\"mention\": \"James Comey\", \"polarity\": 0, \"from\": 27, \"to\": 38, \"sentence\": \"Steve Bannon: Trump firing James Comey 'maybe' the worst mistake in 'modern political history'\", \"id\": \"allsides_611_243_0_Former White House chief strategist Steve Bannon_27_38\"}\n{\"mention\": \"Obama\", \"polarity\": 0, \"from\": 57, \"to\": 62, \"sentence\": \"Poll gives Romney national edge, underscoring stakes for Obama at debate\", \"id\": \"allsides_6120_2629_0_Obama_57_62\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Romney's running mate Paul Ryan took on the challenge, asserting in Ohio and Wisconsin that Obama had inherited a tough economic situation but made things worse.\", \"id\": \"allsides_6120_2629_36_Romney_0_6\"}\n{\"mention\": \"The president\", \"polarity\": 1, \"from\": 62, \"to\": 75, \"sentence\": \"But Obama’s attack will also be more explicitly gender-based: The president will look for an opportunity to talk about social issues, especially Romney’s flip from pro-abortion rights as a gubernatorial candidate to anti-abortion as Massachusetts governor — and the GOP nominee’s opposition to Planned Parenthood, top Democrats say.\", \"id\": \"allsides_6122_2629_14_the president_62_75\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 32, \"to\": 38, \"sentence\": \"The expectations are higher for Romney, who needs to match his previous showing without having the benefit of surprising the media and viewers.\", \"id\": \"allsides_6122_2629_6_Mitt Romney_32_38\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 73, \"to\": 79, \"sentence\": \"If Obama needs to recover from a flat performance in Denver, it is still Romney—as the candidate facing a steeper Electoral College path to victory—who has the most pressure on him, particularly as his strong first debate has heightened expectations for an even stronger second.\", \"id\": \"allsides_6127_2631_12_Romney_73_79\"}\n{\"mention\": \"Denver\", \"polarity\": 0, \"from\": 53, \"to\": 59, \"sentence\": \"If Obama needs to recover from a flat performance in Denver, it is still Romney—as the candidate facing a steeper Electoral College path to victory—who has the most pressure on him, particularly as his strong first debate has heightened expectations for an even stronger second.\", \"id\": \"allsides_6127_2631_12_Denver_53_59\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 28, \"to\": 33, \"sentence\": \"Rob Portman, who has played Obama during Romney’s debate rehearsals, said Sunday he also expects the president to “come out swinging.”\", \"id\": \"allsides_6128_2631_14_Obama_28_33\"}\n{\"mention\": \"It\", \"polarity\": -1, \"from\": 107, \"to\": 109, \"sentence\": \"The interview — and based on leaked bits of it, her new book— seem to be a self-justifying, wound-licking “It’s not about you” purge of what she endured during the campaign, from that on-stage stalking, to relentless sexism, to being labeled a “criminal” by a candidate whose business empire was built by skirting financial and legal norms... and while the FBI was investigating his campaign’s connections to Russian hackers and other Putin surrogates trying to disrupt the election.\", \"id\": \"allsides_612_244_16_her new book—_107_109\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 125, \"to\": 128, \"sentence\": \"Keep up with this story and more by subscribing now Leaks of her book, What Happened, to be published Tuesday, indicate that she takes swipes at Joe Biden for his weak support of her campaign, knocks primary rival Bernie Sanders for his attacks on her, and even gripes about former President Barack Obama for failing to publicize the interference in the election by Russia.\", \"id\": \"allsides_612_244_4_Hillary Clinton_125_128\"}\n{\"mention\": \"Ryan\", \"polarity\": -1, \"from\": 152, \"to\": 156, \"sentence\": \"The vice president, especially toward the beginning of the debate in Kentucky, could be seen grinning and laughing -- some have said smirking -- during Ryan's answers, as he prepared to dismiss Ryan's points as \\\"impossible\\\" and \\\"malarkey.\\\"\", \"id\": \"allsides_6131_2633_2_Paul Ryan_152_156\"}\n{\"mention\": \"his president\", \"polarity\": 1, \"from\": 78, \"to\": 91, \"sentence\": \"Like he did many times before, Biden served dutifully, not only in service to his president but to his party and his country.\", \"id\": \"allsides_6133_2633_14_his president_78_91\"}\n{\"mention\": \"Biden\", \"polarity\": 1, \"from\": 31, \"to\": 36, \"sentence\": \"Like he did many times before, Biden served dutifully, not only in service to his president but to his party and his country.\", \"id\": \"allsides_6133_2633_14_Joe Biden_31_36\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Obama-Biden received substantial momentum from tonight's debate.\", \"id\": \"allsides_6133_2633_34_Obama_0_5\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 21, \"to\": 26, \"sentence\": \"Better equipped than Obama and Romney -- distant and aloof standard-bearers -- Vice President Joe Biden and Congressman Paul Ryan 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better job.\", \"id\": \"allsides_6147_2640_3_President Obama_63_68\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 33, \"to\": 39, \"sentence\": \"Take that rise in enthusiasm for Romney.\", \"id\": \"allsides_6149_2640_16_Mitt Romney_33_39\"}\n{\"mention\": \"September\", \"polarity\": 0, \"from\": 150, \"to\": 159, \"sentence\": \"Although Obama still leads him by 29 points as better able to connect with ordinary Americans, the gap has narrowed by 14 percentage points since mid-September.\", \"id\": \"allsides_6149_2640_24_September_150_159\"}\n{\"mention\": \"Gallup\", \"polarity\": 0, \"from\": 26, \"to\": 32, \"sentence\": \"Over the last seven days, Gallup found Obama leading Romney among registered voters by five percentage points (50 percent to 45 percent).\", \"id\": \"allsides_6149_2640_5_Gallup_26_32\"}\n{\"mention\": \"Mr. Romney\", \"polarity\": 1, \"from\": 40, \"to\": 50, \"sentence\": \"The jobs news comes just two days after Mr. Romney seemed to be gaining 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Bush administration.\", \"id\": \"allsides_6158_2645_10_Mitt Romney_79_90\"}\n{\"mention\": \"Mr. Romney\", \"polarity\": 0, \"from\": 114, \"to\": 124, \"sentence\": \"Mr. Obama has emphasized that the economy is moving in the right direction after a severe financial crisis, while Mr. Romney has emphasized that it has improved more slowly than many voters hoped or than Mr. Obama predicted.\", \"id\": \"allsides_6158_2645_42_Mitt Romney_114_124\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 26, \"to\": 31, \"sentence\": \"Video potential worry for Obama\", \"id\": \"allsides_6166_2650_0_President Barack Obama_26_31\"}\n{\"mention\": \"President Barack Obama\", \"polarity\": 0, \"from\": 32, \"to\": 54, \"sentence\": \"The five-year old video showing President Barack Obama talking bluntly about race, Hurricane Katrina and the Rev.\", \"id\": \"allsides_6166_2650_1_President Barack Obama_34_56\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 7, \"to\": 12, \"sentence\": \"Barack Obama told a mostly black audience of ministers that the country's leaders \\\"don't care about\\\" New Orleans residents, suggesting the city was neglected in the aftermath of Hurricane Katrina because of institutional racism, according to an unedited video reported on by The Daily Caller.\", \"id\": \"allsides_6167_2650_3_Obama_7_12\"}\n{\"mention\": \"Democratic National Committee spokesman Brad Woodhouse\", \"polarity\": 0, \"from\": 0, \"to\": 54, \"sentence\": \"Democratic National Committee spokesman Brad Woodhouse tells Fox News he thinks Republican presidential nominee Mitt Romney will win.\", \"id\": \"allsides_6168_2651_4_Democratic National Committee spokesman Brad Woodhouse_0_54\"}\n{\"mention\": \"they\", \"polarity\": 1, \"from\": 78, \"to\": 82, \"sentence\": \"Woodhouse says the way the DNC sees it, challengers win the first debate when they are up against incumbents.\", \"id\": \"allsides_6168_2651_5_challengers_78_82\"}\n{\"mention\": \"Christie's\", \"polarity\": -1, \"from\": 0, \"to\": 10, \"sentence\": \"Christie's comments aside, Romney's campaign has worked hard to lower expectations, as has Obama's campaign.\", \"id\": \"allsides_6169_2651_23_Chris Christie (R)_0_10\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 139, \"to\": 144, \"sentence\": \"Its theme to supporters was \\\"Be the First,\\\" drawing a parallel between the state's first-in-the-nation presidential caucuses that launched Obama to the White House and its status as one of the earliest voting swing states.\", \"id\": \"allsides_6184_2658_10_President Obama_139_144\"}\n{\"mention\": \"Iowa\", \"polarity\": 0, \"from\": 110, \"to\": 114, \"sentence\": \"The Obama campaign worked for weeks to promote early voting, which it sees as a key advantage in the race for Iowa's six electoral votes, and was quick out of the gate.\", \"id\": \"allsides_6184_2658_9_Iowa_110_114\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He hasn't said what that income level would be.\", \"id\": \"allsides_6187_2659_11_Romney_0_2\"}\n{\"mention\": \"Mr. Romney\", \"polarity\": -1, \"from\": 25, \"to\": 35, \"sentence\": \"Mr. Rowe did not endorse Mr. Romney, saying instead his experience on “Dirty Jobs” has taught him thatthe nation is disconnected with the plumbers, public works employees and tradesman that make “civilized life possible for the rest of us.”\", \"id\": \"allsides_6189_2659_13_Romney_25_35\"}\n{\"mention\": \"China\", \"polarity\": -1, \"from\": 194, \"to\": 199, \"sentence\": \"Mr. Romney used the stops and another in Toledo to warn that Mr. Obama will continue to saddle future generations with trillions in debt and to hammer the president for failing to crack down on China’s unfair trade practices.\", \"id\": \"allsides_6189_2659_9_China_194_199\"}\n{\"mention\": \"Mr. Brat\", \"polarity\": 0, \"from\": 57, \"to\": 65, \"sentence\": \"It’s not about Harvey - everybody was going to do that,” Mr. Brat said.\", \"id\": \"allsides_618_247_30_Mr. Brat_57_65\"}\n{\"mention\": \"\\\" Trippi\", \"polarity\": 0, \"from\": 41, \"to\": 49, \"sentence\": \"\\\"The good news is it's 40 days or so out,\\\" Trippi says, adding, \\\"You've got time to do something about it.\\\"\", \"id\": \"allsides_6196_2662_9_Longtime Democratic strategist Joe Trippi_41_49\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": 1, \"from\": 112, \"to\": 121, \"sentence\": \"“America wants to resolve this issue through diplomacy, and we believe there is still time and space to do so,” Mr. Obama said.\", \"id\": \"allsides_6199_2663_29_Mr. Obama_112_121\"}\n{\"mention\": \"this issue\", \"polarity\": 0, \"from\": 26, \"to\": 36, \"sentence\": \"“America wants to resolve this issue through diplomacy, and we believe there is still time and space to do so,” Mr. Obama said.\", \"id\": \"allsides_6199_2663_29_the Iranian nuclear issue “_26_36\"}\n{\"mention\": \"Mulvaney\", \"polarity\": -1, \"from\": 27, \"to\": 35, \"sentence\": \"After leaving the meeting, Mulvaney dodged a question about whether he would have voted for the bill, choosing to praise Trump’s decision to reach across the aisle.\", \"id\": \"allsides_619_247_14_Mulvaney_27_35\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Obama’s forceful defense of free speech rights included a civics-class-style explanation of why allowing offensive speech and confronting it with other speech is preferable to trying to ban objectionable speech outright.\", \"id\": \"allsides_6200_2664_10_Obama_0_5\"}\n{\"mention\": \"Chris Stevens\", \"polarity\": 1, \"from\": 31, \"to\": 44, \"sentence\": \"\\\"I tell you this story because Chris Stevens embodied the best of America,\\\" Obama said.\", \"id\": \"allsides_6201_2664_14_Ambassador Chris Stevens_31_44\"}\n{\"mention\": \"Mitt Romney\", \"polarity\": -1, \"from\": 14, \"to\": 25, \"sentence\": \"But remember, Mitt Romney is callously dismissive and uncaring toward poor people and the '47 percent.'\", \"id\": \"allsides_6209_2668_30_Mitt Romney_16_27\"}\n{\"mention\": \"Mitt Romney\", \"polarity\": -1, \"from\": 14, \"to\": 25, \"sentence\": \"But remember, Mitt Romney is callously dismissive and uncaring toward poor people and the '47 percent.'\", \"id\": \"allsides_6209_2668_30_the Governor_16_27\"}\n{\"mention\": \"Mitt Romney\", \"polarity\": 1, \"from\": 4, \"to\": 15, \"sentence\": \"And Mitt Romney looks like the remarkably generous, law-abiding, productive member of society that he is.\", \"id\": \"allsides_6209_2668_38_the Governor_6_17\"}\n{\"mention\": \"Mitt Romney\", \"polarity\": 1, \"from\": 4, \"to\": 15, \"sentence\": \"And Mitt Romney looks like the remarkably generous, law-abiding, productive member of society that he is.\", \"id\": \"allsides_6209_2668_38_Mitt Romney_6_17\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 4, \"to\": 10, \"sentence\": \"The Romney campaign has released a detailed report of the the candidate's 2011 tax returns, as well as an extensive summary of the Romneys' taxes over the last two decades, prepared by analysts at PricewaterhouseCoopers.\", \"id\": \"allsides_6209_2668_3_Mitt Romney_6_12\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 23, \"to\": 25, \"sentence\": \"So the word’s out that he hasn’t paid any taxes for ten years.\", \"id\": \"allsides_6209_2668_48_Mitt Romney_23_25\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 15, \"to\": 21, \"sentence\": \"Brad Malt, the Romney family's trustee, summarizes the 2011 data: \\\\- In 2011, the Romneys paid $1,935,708 in taxes on $13,696,951 in mostly investment income.\", \"id\": \"allsides_6209_2668_5_Mitt Romney_17_23\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 30, \"to\": 36, \"sentence\": \"It's already been a bad week: Romney's \\\"47 percent\\\" secret video comments ensured that the Republican presidential nominee had already lost this week on the big political scoreboard.\", \"id\": \"allsides_6210_2668_20_Mitt Romney_30_36\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 25, \"to\": 31, \"sentence\": \"As we have noted before, Romney's financial life as a very wealthy person is significantly more exotic than the average person he needs to vote for him; that he made almost $14 million in 2011 (and $21 million in 2010) without drawing any salary is all the confirmation you need of that fact.\", \"id\": \"allsides_6210_2668_2_Mitt Romney_25_31\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 20, \"to\": 26, \"sentence\": \"And that's not what Romney wants.\", \"id\": \"allsides_6210_2668_30_Mitt Romney_21_27\"}\n{\"mention\": \"Washington Post\", \"polarity\": 0, \"from\": 208, \"to\": 223, \"sentence\": \"Must-reads: \\\"Romney Is Latest in a Long Line to Trip Over a Tongue\\\" -- John Harwood, New York Times \\\"Scott Gessler, Colorado’s ‘honey badger,’ may be most closely watched election official\\\" -- Robert Barnes, Washington Post \\\"Obama mocks Romney on ‘47 percent’ remarks during Univision forum\\\" -- David Nakamura, Washington Post \\\"Why early voting could  be pivotal\\\" -- Major Garrett, National Journal \\\"Obama pressed on failures at Univision forum\\\" -- Reid J. Epstein, Politico \\\"GOP retreat on taxes likely if Obama wins\\\" -- Lori Montgomery and Paul Kane, Washington Post \\\"Romney campaign hits a financial snag\\\" -- Dan Eggen, Washington Post\", \"id\": \"allsides_6211_2669_36_Washington Post_208_223\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 13, \"to\": 19, \"sentence\": \"Must-reads: \\\"Romney Is Latest in a Long Line to Trip Over a Tongue\\\" -- John Harwood, New York Times \\\"Scott Gessler, Colorado’s ‘honey badger,’ may be most closely watched election official\\\" -- Robert Barnes, Washington Post \\\"Obama mocks Romney on ‘47 percent’ remarks during Univision forum\\\" -- David Nakamura, Washington Post \\\"Why early voting could  be pivotal\\\" -- Major Garrett, National Journal \\\"Obama pressed on failures at Univision forum\\\" -- Reid J. 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election.\", \"id\": \"allsides_6215_2670_1_Romney_59_65\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Obama’s polling has been fairly robust in New Hampshire, a state in which Romney may have hurt himself by disavowing the moderate positions that he took as governor of Massachusetts.\", \"id\": \"allsides_6216_2670_49_Obama_0_5\"}\n{\"mention\": \"Romney\", \"polarity\": -1, \"from\": 74, \"to\": 80, \"sentence\": \"Obama’s polling has been fairly robust in New Hampshire, a state in which Romney may have hurt himself by disavowing the moderate positions that he took as governor of Massachusetts.\", \"id\": \"allsides_6216_2670_49_Romney_74_80\"}\n{\"mention\": \"Mitt Romney's\", \"polarity\": -1, \"from\": 0, \"to\": 13, \"sentence\": \"Mitt Romney's 47 Percent Remarks: Wrong on the Facts, Not Just the Rhetoric\", \"id\": \"allsides_6223_2674_0_Mitt Romney's_0_13\"}\n{\"mention\": \"Mitt Romney's\", \"polarity\": -1, \"from\": 0, \"to\": 13, 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\"allsides_6357_2736_8_Romney_18_24\"}\n{\"mention\": \"Romney\", \"polarity\": 1, \"from\": 80, \"to\": 86, \"sentence\": \"It is clear that President Obama wants nothing more than to talk about Governor Romney’s tax returns instead of the issues that matter to voters, like putting Americans back to work, fixing the economy and reining in spending.\", \"id\": \"allsides_6358_2736_7_Romney_80_86\"}\n{\"mention\": \"Mitt Romney's\", \"polarity\": -1, \"from\": 97, \"to\": 110, \"sentence\": \"In Boston, Murdoch was the featured guest for Bloomberg and, via the Boston Globe, he questioned Mitt Romney's approach to Hispanic voters:\", \"id\": \"allsides_6369_2741_2_Romney_97_110\"}\n{\"mention\": \"\\\" applicant Kristi Alarcon\", \"polarity\": 0, \"from\": 67, \"to\": 93, \"sentence\": \"We want to get our passport because Obama might be asking for them,\\\" applicant Kristi Alarcon told MyFoxHouston, as she stood in line outside Houston's Mexican consulate.\", \"id\": 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and has been through a lot,” Mr. Trump said, according to Mr. Comey’s testimony.\", \"id\": \"allsides_992_398_48_Mr. Trump_47_56\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He added: “I hope you can see your way clear to letting this go, to letting Flynn go.\", \"id\": \"allsides_992_398_49_Mr. Trump_0_2\"}\n{\"mention\": \"Wray\", \"polarity\": 1, \"from\": 37, \"to\": 41, \"sentence\": \"“I will be nominating Christopher A. Wray, a man of impeccable credentials, to be the new Director of the FBI,” the president announced on Twitter on Wednesday morning.\", \"id\": \"allsides_994_399_2_Christopher Wray_37_41\"}\n{\"mention\": \"Wray\", \"polarity\": 1, \"from\": 28, \"to\": 32, \"sentence\": \"Last week, Christie praised Wray as an “outstanding lawyer,” after it was revealed that he was under consideration.\", \"id\": \"allsides_994_399_7_Christopher Wray_28_32\"}\n{\"mention\": \"Christie\", \"polarity\": 1, \"from\": 11, \"to\": 19, \"sentence\": \"Last week, Christie praised Wray as an “outstanding lawyer,” after it was revealed that he was under consideration.\", \"id\": \"allsides_994_399_7_Governor Chris Christie_11_19\"}\n{\"mention\": \"FBI\", \"polarity\": 0, \"from\": 140, \"to\": 143, \"sentence\": \"“He has absolute integrity and honesty, and I think that the president certainly would not be making a mistake if he asked Chris Wray to be FBI director.”\", \"id\": \"allsides_995_399_62_FBI_140_143\"}\n{\"mention\": \"Chris Wray\", \"polarity\": 1, \"from\": 123, \"to\": 133, \"sentence\": \"“He has absolute integrity and honesty, and I think that the president certainly would not be making a mistake if he asked Chris Wray to be FBI director.”\", \"id\": \"allsides_995_399_62_Wray_123_133\"}\n{\"mention\": \"the N.S.A.\", \"polarity\": 0, \"from\": 100, \"to\": 110, \"sentence\": \"The F.B.I. affidavit said reporters for the news outlet, which it also did not name, had approached the N.S.A. with questions for their story and, in the course of that dialogue, provided a copy of the document in their possession.\", \"id\": \"allsides_999_401_12_N.S.A._100_110\"}\n{\"mention\": \"Sarah Huckabee Sanders\", \"polarity\": -1, \"from\": 4, \"to\": 26, \"sentence\": \"NB: Sarah Huckabee Sanders appears to have as tenuous a grasp on the separation of powers as her boss, as only utter and absolute misapprehension could explain why she’d argue that the executive’s meeting with legislators should dictate the judiciary’s actions in pending cases.\", \"id\": \"allsides_99_40_16_Sarah Huckabee Sanders_4_26\"}\n{\"mention\": \"Northam\", \"polarity\": -1, \"from\": 148, \"to\": 155, \"sentence\": \"At the same time that Gillespie released these advertisements, the Virginia Republican Party sent a new mailer, approved by Gillespie, that accused Northam of wanting to “tear down history while making life easier for illegal immigrants.”\", \"id\": \"polusa_v1_113704059_-1_35_Northam_148_155\"}\n{\"mention\": \"the cops\", \"polarity\": -1, \"from\": 96, \"to\": 104, \"sentence\": \"In a city—Chicago, no less, that favorite race-coded target of Trump’s dishonest rhetoric—where the cops can’t or won’t do their job, it falls to Willis to keep the peace, with increasingly small reservations and increasingly large guns.\", \"id\": \"polusa_v1_113705206_-1_7_the cops_96_104\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 63, \"to\": 68, \"sentence\": \"In a city—Chicago, no less, that favorite race-coded target of Trump’s dishonest rhetoric—where the cops can’t or won’t do their job, it falls to Willis to keep the peace, with increasingly small reservations and increasingly large guns.\", \"id\": \"polusa_v1_113705206_-1_7_Donald Trump_63_68\"}\n{\"mention\": \"Donald Trump's\", \"polarity\": -1, \"from\": 18, \"to\": 32, \"sentence\": \"“They do not want Donald Trump's populist, economic nationalist agenda to be implemented.\", \"id\": \"polusa_v1_113706422_-1_8_Donald Trump's_18_32\"}\n{\"mention\": \"Comey\", \"polarity\": 1, \"from\": 73, \"to\": 78, \"sentence\": \"After being fired for doing his job investigating government corruption, Comey—like so many whistleblowers before him—recognized the likely futility of an independent investigation being launched into potentially one of the most serious abuses of power in history without the power of the press.\", \"id\": \"polusa_v1_113706996_-1_41_former FBI Director James Comey_74_79\"}\n{\"mention\": \"Will Saletan, who just read it\", \"polarity\": 0, \"from\": 110, \"to\": 140, \"sentence\": \"Justin Sullivan/Getty Images\\nRight on: Michael Wolff’s book can be hard to believe in its particulars, writes Will Saletan, who just read it.\", \"id\": \"polusa_v1_113707351_-1_3_Will Saletan, who just read it_112_142\"}\n{\"mention\": \"Alexa\", \"polarity\": 1, \"from\": 43, \"to\": 48, \"sentence\": \"Even though I’m conscious of the fact that Alexa is an algorithm, I will still say thank you after she feeds me the information I’ve requested.”\", \"id\": \"polusa_v1_113708233_-1_112_Alexa_43_48\"}\n{\"mention\": \"myself\", \"polarity\": 0, \"from\": 103, \"to\": 109, \"sentence\": \"“When you’re in a house by yourself, which I am as a self-employed [person] a lot of times, talking to myself out loud is just not a thing I do.”\", \"id\": \"polusa_v1_113708233_-1_53_Emily_103_109\"}\n{\"mention\": \"Margolis\", \"polarity\": 1, \"from\": 1, \"to\": 9, \"sentence\": \"“Margolis was jovial and extroverted … and he enjoyed his food and his wine and made crass jokes.\", \"id\": \"polusa_v1_113708375_-1_73_Margolis_1_9\"}\n{\"mention\": \"Maduro\", \"polarity\": -1, \"from\": 113, \"to\": 119, \"sentence\": \"On Monday, National Security Advisor H.R. McMaster struggled to respond to a reporter’s question about what made Maduro’s power grab notably worse than the referendum that Trump had praised Erdogan for.\", \"id\": \"polusa_v1_113709000_-1_20_Maduro_113_119\"}\n{\"mention\": \"Kennedy\", \"polarity\": 1, \"from\": 82, \"to\": 89, \"sentence\": \"“A people confident in its laws and institutions should not be ashamed of mercy,” Kennedy said, perhaps drawing on his Catholic faith as he petitioned his audience of lawyers to make more such requests to presidents and governors.\", \"id\": \"polusa_v1_113709173_-1_31_Supreme Court Justice Anthony Kennedy_82_89\"}\n{\"mention\": \"Dr. Sanjay Gupta\", \"polarity\": 0, \"from\": 6, \"to\": 22, \"sentence\": \"CNN’s Dr. Sanjay Gupta suggested on air Wednesday night, after speaking with McCain’s doctors, that some combination of surgery, chemotherapy, and radiation would likely be required to combat the tumor.\", \"id\": \"polusa_v1_113711090_-1_10_Dr. Sanjay Gupta_7_23\"}\n{\"mention\": \"President George W. Bush\", \"polarity\": -1, \"from\": 28, \"to\": 52, \"sentence\": \"Advertisement\\nConsider that President George W. Bush is remembered for following the neocons Dick Cheney and Donald Rumsfeld down an ideological rabbit hole of invading Iraq.\", \"id\": \"polusa_v1_113711199_-1_10_Bush_29_53\"}\n{\"mention\": \"Dick Cheney\", \"polarity\": -1, \"from\": 93, \"to\": 104, \"sentence\": \"Advertisement\\nConsider that President George W. Bush is remembered for following the neocons Dick Cheney and Donald Rumsfeld down an ideological rabbit hole of invading Iraq.\", \"id\": \"polusa_v1_113711199_-1_10_Dick Cheney_94_105\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Donald Trump would promise some unbelievable benefit: an incredible investment opportunity, an unprecedented chance to learn valuable real estate skills, high-quality steaks for supermarket prices.\", \"id\": \"polusa_v1_113712974_-1_20_President Trump_0_12\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Gorsuch is equally clever when penning less freighted and consequential opinions.\", \"id\": \"polusa_v1_113713175_-1_28_Neil Gorsuch_1_8\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Gorsuch is equally clever when penning less freighted and consequential opinions.\", \"id\": \"polusa_v1_113713175_-1_28_Gorsuch_1_8\"}\n{\"mention\": \"Gorsuch\", \"polarity\": 0, \"from\": 28, \"to\": 35, \"sentence\": \"Alex Wong/Getty Images\\nNeil Gorsuch is strikingly different from the man who nominated him to the United States Supreme Court.\", \"id\": \"polusa_v1_113713175_-1_3_Gorsuch_30_37\"}\n{\"mention\": \"Mike Pence\", \"polarity\": 1, \"from\": 74, \"to\": 84, \"sentence\": \"Wouldn’t literally everyone everywhere feel more comfortable right now if Mike Pence were in charge?\", \"id\": \"polusa_v1_113713260_-1_1_Mike Pence_76_86\"}\n{\"mention\": \"Thomas\", \"polarity\": 1, \"from\": 9, \"to\": 15, \"sentence\": \"Clarence Thomas’ consistency handed Democrats—and the principle of equality—a remarkable victory.\", \"id\": \"polusa_v1_113713857_-1_14_Thomas_10_16\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 54, \"to\": 57, \"sentence\": \"More than 100 of the country’s best legal minds think she’s right.\", \"id\": \"polusa_v1_113714131_-1_15_Ayala_54_57\"}\n{\"mention\": \"Smith\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Smith is quite right (with the possible exception of when A.I. algorithms train themselves independent of human involvement—but that’s another story).\", \"id\": \"polusa_v1_113715046_-1_17_U.S. Magistrate Judge Stephen Smith_0_5\"}\n{\"mention\": \"Sue Gordon\", \"polarity\": 1, \"from\": 1, \"to\": 11, \"sentence\": \"\\\"Sue Gordon is a great professional with a long and distinguished career,\\\" the president tweeted late Thursday.\", \"id\": \"polusa_v1_113832214_-1_6_Sue Gordon_2_12\"}\n{\"mention\": \"Sao Paulo\", \"polarity\": 0, \"from\": 84, \"to\": 93, \"sentence\": \"In the end, it was funny because we never expect these kinds of things to happen in Sao Paulo.\\\"\", \"id\": \"polusa_v1_113832465_-1_12_Sao Paulo_84_93\"}\n{\"mention\": \"we\", \"polarity\": 1, \"from\": 33, \"to\": 35, \"sentence\": \"In the end, it was funny because we never expect these kinds of things to happen in Sao Paulo.\\\"\", \"id\": \"polusa_v1_113832465_-1_12_lawyer Hugo Vecchiatto, who works on the 17th floor of an office building on Paulista Avenue in Sao Paulo_33_35\"}\n{\"mention\": \"Stephen Miller\", \"polarity\": -1, \"from\": 47, \"to\": 61, \"sentence\": \"President Donald Trump's senior policy advisor Stephen Miller was \\\"escorted\\\" off a CNN TV set in Washington on Sunday by the network's security officers following a contentious interview with Jake Tapper, CNN has said.\", \"id\": \"polusa_v1_113833129_-1_2_Top Trump advisor Stephen Miller \\\"_49_63\"}\n{\"mention\": \"CNN\", \"polarity\": 0, \"from\": 83, \"to\": 86, \"sentence\": \"President Donald Trump's senior policy advisor Stephen Miller was \\\"escorted\\\" off a CNN TV set in Washington on Sunday by the network's security officers following a contentious interview with Jake Tapper, CNN has said.\", \"id\": \"polusa_v1_113833129_-1_2_CNN_85_88\"}\n{\"mention\": \"Neal\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Neal said fresher, hotter lava could emerge because magma has been moving down Kilauea's rift zone toward the area where the volcano is erupting.\", \"id\": \"polusa_v1_113834047_-1_17_Hawaiian Volcano Observatory Scientist Tina Neal_0_5\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She said hotter, fresher and gassier magma can result in more voluminous lava flows.\", \"id\": \"polusa_v1_113834047_-1_18_Hawaiian Volcano Observatory Scientist Tina Neal_1_4\"}\n{\"mention\": \"Klobuchar\", \"polarity\": 0, \"from\": 9, \"to\": 18, \"sentence\": \"However, Klobuchar stressed that all candidates should be focused on their foremost priority: thwarting President Trump's reelection bid next year.\", \"id\": \"polusa_v1_113834074_-1_13_Amy Klobuchar_10_19\"}\n{\"mention\": \"Stormy Daniels'\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Stormy Daniels' lawyer Michael Avenatti did not comment if there are photos, texts or videos relating to her alleged relationship with Trump\", \"id\": \"polusa_v1_113835015_-1_1_Stormy Daniels'_0_17\"}\n{\"mention\": \"Clifford\", \"polarity\": -1, \"from\": 24, \"to\": 32, \"sentence\": \"WASHINGTON -- Stephanie Clifford, the adult film star otherwise known as Stormy Daniels who alleges she had an affair with President Trump, is offering to return the $130,000 the president's personal lawyer Michael Cohen paid her in exchange for silence on the subject.\", \"id\": \"polusa_v1_113835015_-1_2_Clifford_26_34\"}\n{\"mention\": \"Franken\", \"polarity\": -1, \"from\": 64, \"to\": 71, \"sentence\": \"Sanders joined the chorus of more than 30 lawmakers calling for Franken to resign from the Senate after previously saying it should be up to the people of Minnesota to decide his fate.\", \"id\": \"polusa_v1_113835270_-1_7_Franken_65_72\"}\n{\"mention\": \"Epstein\", \"polarity\": -1, \"from\": 30, \"to\": 37, \"sentence\": \"Hoffenberg told CBS News that Epstein was in charge of the illegal transfer and sale of bonds and investments out of United Diversified accounts.\", \"id\": \"polusa_v1_113835627_-1_48_Jeffrey Epstein_30_37\"}\n{\"mention\": \"our nation\", \"polarity\": 1, \"from\": 45, \"to\": 55, \"sentence\": \"Ryan and Rebecca, you embody the goodness of our nation.\", \"id\": \"polusa_v1_113836094_-1_273_a compassionate nation_45_55\"}\n{\"mention\": \"Ryan\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Ryan and Rebecca, you embody the goodness of our nation.\", \"id\": \"polusa_v1_113836094_-1_273_Ryan Holets_0_4\"}\n{\"mention\": \"Morgenthau\", \"polarity\": 1, \"from\": 31, \"to\": 41, \"sentence\": \"Over the next quarter-century, Morgenthau was elected another seven times as head of one of the nation's largest law offices, with 550 prosecutors and 700 other staffers.\", \"id\": \"polusa_v1_113836369_-1_39_Morgenthau_32_42\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 38, \"to\": 43, \"sentence\": \"As some Republicans grumbled that Mr. Trump caved, McConnell lashed out at Democrats for failing to give Trump any of the $5 billion that he wanted for the wall.\", \"id\": \"polusa_v1_113836991_-1_34_President Trump_39_44\"}\n{\"mention\": \"Labor Secretary Alex Acosta\", \"polarity\": -1, \"from\": 0, \"to\": 27, \"sentence\": \"Labor Secretary Alex Acosta came under fire for his handling of the Jeffrey Epstein case and ultimately resigned, saying his role in the matter a distraction from the economy's success and the Trump administration's achievements.\", \"id\": \"polusa_v1_113837081_-1_24_Labor Secretary Alex Acosta_0_27\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 25, \"to\": 28, \"sentence\": \"\\\"Absolutely it matters,\\\" she said.\", \"id\": \"polusa_v1_113839127_-1_13_Cheri Bustos_26_29\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump has made the stock market a key barometer of his success, pointing to its strong performance earlier this year as proof his policies are working.\", \"id\": \"polusa_v1_113840224_-1_5_Donald Trump_1_10\"}\n{\"mention\": \"Jeff Sessions\", \"polarity\": 1, \"from\": 40, \"to\": 53, \"sentence\": \"\\\"I join the people of Alabama in giving Jeff Sessions my deep respect and unwavering support.\\\"\", \"id\": \"polusa_v1_113841683_-1_18_Jeff Sessions_41_54\"}\n{\"mention\": \"Michael Bloomberg\", \"polarity\": 1, \"from\": 0, \"to\": 17, \"sentence\": \"Michael Bloomberg: Reasonably self-confident.\", \"id\": \"polusa_v1_113842502_-1_62_Michael Bloomberg's_1_18\"}\n{\"mention\": \"Pompeo on Iran\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Pompeo on Iran: \\\"President Trump does not want war\\\"\", \"id\": \"polusa_v1_113842654_-1_0_Pompeo on Iran_0_14\"}\n{\"mention\": \"Riehl\", \"polarity\": 0, \"from\": 28, \"to\": 33, \"sentence\": \"When deputies later return, Riehl again talks to at least one deputy through a closed door.\", \"id\": \"polusa_v1_113842673_-1_16_Matthew Riehl_29_34\"}\n{\"mention\": \"Jared Diamond\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"Jared Diamond is a professor at UCLA and a Pulitzer Prize winning author.\", \"id\": \"polusa_v1_113842743_-1_4_Jared Diamond_0_14\"}\n{\"mention\": \"Jerusalem\", \"polarity\": 0, \"from\": 110, \"to\": 119, \"sentence\": \"While the embassy move is delayed, Morrison said his government would establish a defense and trade office in Jerusalem and would also start looking for an appropriate site for the embassy.\", \"id\": \"polusa_v1_113842860_-1_6_west Jerusalem_111_120\"}\n{\"mention\": \"Democrats\", \"polarity\": -1, \"from\": 80, \"to\": 89, \"sentence\": \"Testifying before the Senate Judiciary Committee last week, Kavanaugh lambasted Democrats for their handling of the accusations against him, at one point turning a question back on Democratic Sen.\", \"id\": 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Nelson_38_49\"}\n{\"mention\": \"Bill Nelson\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Bill Nelson, the three-time incumbent Democratic senator from Florida seeking his fourth term.\", \"id\": \"polusa_v1_113844599_-1_3_Bill Nelson_0_11\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 48, \"to\": 53, \"sentence\": \"His remarks come after media criticism that the Trump administration - the president as well as Tillerson and Mattis - had offered mixed messages as tension rose over North Korea's nuclear program.\", \"id\": \"polusa_v1_113845120_-1_6_President Trump_49_54\"}\n{\"mention\": \"Longshoreman Paul Moe\", \"polarity\": -1, \"from\": 0, \"to\": 21, \"sentence\": \"Longshoreman Paul Moe held one such job, earning $493,000 a year, until he was convicted of fraud and sentenced to federal prison in March.\", \"id\": \"polusa_v1_113847098_-1_21_Longshoreman Paul Moe_1_22\"}\n{\"mention\": \"Francis\", \"polarity\": 1, \"from\": 33, \"to\": 40, \"sentence\": 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arrested last month at the U.S.-Mexico border during a shopping trip, Wolf said.\", \"id\": \"polusa_v1_113849883_-1_10_Macrina Perez_0_6\"}\n{\"mention\": \"Warren\", \"polarity\": 0, \"from\": 315, \"to\": 321, \"sentence\": \"Some of the largest: Kohlberg, Kravis, Roberts & Co.'s 1989 purchase of RJR Nabiso, a deal that became a symbol of Wall Street greed; a $27 billion purchase of media company Clear Channel (now iHeartMedia) by Bain Capital and Thomas H. Lee Partners in 2006; and a 2013 deal in which 3G Capital Partners teamed with Warren Buffett's Berkshire Hathaway to buy H.J. Heinz (now part of food giant Kraft) for some $23 billion.\", \"id\": \"polusa_v1_113849933_-1_18_Elizabeth Warren_315_321\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 4, \"to\": 9, \"sentence\": \"Mr. Trump called climate change a hoax in November 2012 when he sent a tweet stating, \\\"The concept of global warming was created by and for the Chinese in order to make U.S. manufacturing non-competitive.\\\"\", \"id\": \"polusa_v1_113849951_-1_12_Mr. Trump_5_10\"}\n{\"mention\": \"Johnson\", \"polarity\": 0, \"from\": 22, \"to\": 29, \"sentence\": \"But the task ahead of Johnson may have been the most daunting any president has ever faced.\", \"id\": \"polusa_v1_113850040_-1_35_Tennessee's Andrew Johnson_23_30\"}\n{\"mention\": \"Rocca\", \"polarity\": 1, \"from\": 63, \"to\": 68, \"sentence\": \"Presidential historians have been making a list ... and our Mo Rocca may have the winner:\\nNo survey of forgotten presidents (such as James Buchanan, Chester A. 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Florida's large Cuban American population.\", \"id\": \"polusa_v1_113850206_-1_8_South Florida_265_278\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He noted, however, that he was \\\"confident in our plans and capabilities with respect to all five of those today.\\\"\", \"id\": \"polusa_v1_113850951_-1_15_former Defense Secretary Ash Carter_1_3\"}\n{\"mention\": \"our\", \"polarity\": 1, \"from\": 45, \"to\": 48, \"sentence\": \"He noted, however, that he was \\\"confident in our plans and capabilities with respect to all five of those today.\\\"\", \"id\": \"polusa_v1_113850951_-1_15_us_46_49\"}\n{\"mention\": \"his former staff secretary Rob Porter\", \"polarity\": -1, \"from\": 38, \"to\": 75, \"sentence\": \"But spousal abuse allegations against his former staff secretary Rob Porter continue to overshadow the president's legislative priorities.\", \"id\": \"polusa_v1_113851699_-1_8_Porter_39_76\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 38, \"to\": 41, \"sentence\": \"But spousal abuse allegations against his former staff secretary Rob Porter continue to overshadow the president's legislative priorities.\", \"id\": \"polusa_v1_113851699_-1_8_Trump_39_42\"}\n{\"mention\": \"Ailes\", \"polarity\": -1, \"from\": 71, \"to\": 76, \"sentence\": \"While he was never directly accused of the kind of behavior that ended Ailes' and O'Reilly's careers at Fox News, he was, the Associated Press noted, seen as vulnerable because some claimed he looked the other way when staffers came to him with reports of harassment or discrimination.\", \"id\": \"polusa_v1_113851854_-1_8_the late Fox News CEO Roger Ailes_71_76\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 6, \"to\": 8, \"sentence\": \"While he was never directly accused of the kind of behavior that ended Ailes' and O'Reilly's careers at Fox News, he was, the Associated Press noted, seen as vulnerable because some claimed he looked the other way when staffers came 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\"from\": 50, \"to\": 118, \"sentence\": \"Pence began his speech by bringing greetings from President Trump, whom he called a \\\"great champion of law enforcement.\\\"\", \"id\": \"polusa_v1_113903870_-1_5_Mr. Trump_51_119\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 0, \"from\": 115, \"to\": 124, \"sentence\": \"He has been pushing for the kind bilateral free trade deal that 20 other countries enjoy with the U.S.\\nJust before Mr. Trump's election in November 2016, Duterte appointed Philippine real estate developer Jose E.B. 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employees_1_3\"}\n{\"mention\": \"Bloomberg\", \"polarity\": 1, \"from\": 22, \"to\": 31, \"sentence\": \"Before this donation, Bloomberg had already donated a total of $1.5 billion to the university.\", \"id\": \"polusa_v1_115847567_-1_12_Bloomberg_23_32\"}\n{\"mention\": \"the university\", \"polarity\": 0, \"from\": 79, \"to\": 93, \"sentence\": \"Before this donation, Bloomberg had already donated a total of $1.5 billion to the university.\", \"id\": \"polusa_v1_115847567_-1_12_the university_80_94\"}\n{\"mention\": \"House Speaker Paul Ryan\", \"polarity\": -1, \"from\": 169, \"to\": 192, \"sentence\": \"On Saturday -- hours after Donald Trump tweeted to his followers, “Watch @JudgeJeanine on @FoxNews tonight at 9:00 P.M.” – Jeanine Pirro opened her show with a call for House Speaker Paul Ryan to step down. http://abcn.ws/2o6hFaJ\\nSPEED READ with ABC's ADAM KELSEY\\nROGER STONE: ‘I’VE HAD NO CONTACTS OR COLLUSION’ WITH RUSSIANS.\", \"id\": \"polusa_v1_115848162_-1_29_House 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displayed Eleanor Roosevelt’s penchant for shamelessly flouting the wishes of her husband, as Roosevelt did with her campaign to end lynching, half the country and cable news could have erupted in faux outrage.\", \"id\": \"polusa_v1_115868271_-1_8_Michelle Obama_4_9\"}\n{\"mention\": \"her husband\", \"polarity\": -1, \"from\": 88, \"to\": 99, \"sentence\": \"Had Obama displayed Eleanor Roosevelt’s penchant for shamelessly flouting the wishes of her husband, as Roosevelt did with her campaign to end lynching, half the country and cable news could have erupted in faux outrage.\", \"id\": \"polusa_v1_115868271_-1_8_her husband’s_88_99\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She was wearing a thong with a lace front.”\", \"id\": \"polusa_v1_115868518_-1_7_defense attorney Elizabeth O’Connell_0_3\"}\n{\"mention\": \"Omar\", \"polarity\": -1, \"from\": 62, \"to\": 66, \"sentence\": \"Attacks on Israel\\nWHAT TRUMP SAID: On Monday, Trump also said Omar \\\"says horrible things about Israel, hates Israel, hates Jews, it's very simple.\\\"\", \"id\": \"polusa_v1_115868970_-1_32_Omar_63_67\"}\n{\"mention\": \"Butina\", \"polarity\": 1, \"from\": 39, \"to\": 45, \"sentence\": \"J.D. Gordon was among the people Maria Butina befriended during her time in D.C.\", \"id\": \"polusa_v1_115869592_-1_1_Ms. Butina_41_47\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 91, \"to\": 93, \"sentence\": \"For the past decade, \\\"she has been harassed on a regular basis when she goes to airports,\\\" he said.\", \"id\": \"polusa_v1_115870821_-1_47_hard-line President Mahmoud Ahmadinejad_92_94\"}\n{\"mention\": \"Senate\", \"polarity\": -1, \"from\": 60, \"to\": 66, \"sentence\": \"NEED TO READ with ABC News' Daksha Sthipam\\nTrump criticizes Senate GOP for not doing \\\"their job\\\" in Obamacare fight.\", \"id\": \"polusa_v1_115872639_-1_27_Senate_61_67\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 48, \"to\": 50, \"sentence\": \"Not because I agreed with every policy position he took, but because, like Senator Kennedy, he was guided by a loyalty to public service and the American people.\", \"id\": \"polusa_v1_115873329_-1_11_McCain_48_50\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 8, \"to\": 10, \"sentence\": \"\\\"I know he's a busy man.\", \"id\": \"polusa_v1_115873895_-1_50_Debich_8_10\"}\n{\"mention\": \"Rozi Mehmet\", \"polarity\": 1, \"from\": 31, \"to\": 42, \"sentence\": \"———\\nFEARLESS 'PAWNS'\\nLike Ali, Rozi Mehmet wanted to do something to help his people fight Chinese oppression.\", \"id\": \"polusa_v1_115874320_-1_84_Rozi Mehmet_32_43\"}\n{\"mention\": \"Lowe\", \"polarity\": 1, \"from\": 175, \"to\": 179, \"sentence\": \"The bonuses, which will be given out to both part-time and full-time hourly workers across all its U.S. facilities including distribution centers, will be paid in addition to Lowe's long-standing, store-level bonus program.\", \"id\": \"polusa_v1_115874785_-1_6_Lowe_176_180\"}\n{\"mention\": \"Godbolt\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Godbolt's stepfather-in-law, Vincent Mitchell, says the slayings \\\"all stemmed from domestic violence.\\\"\", \"id\": \"polusa_v1_115875282_-1_8_the stepfather-in-law of suspect Willie Corey Godbolt_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 38, \"to\": 43, \"sentence\": \"Hillary Clinton: US did not 'deserve' Trump presidency\", \"id\": \"polusa_v1_115876071_-1_0_Trump_38_43\"}\n{\"mention\": \"Conor Lamb\", \"polarity\": 0, \"from\": 131, \"to\": 141, \"sentence\": \"“Secretary Clinton carried my district by 3800 votes and I was honored to carry it by 38,000 votes, and I analyzed last night that Conor Lamb ran as a conservative Democrat,” Lance said.\", \"id\": \"polusa_v1_115877076_-1_18_Conor Lamb’s_132_142\"}\n{\"mention\": \"Others\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Others wore patches inside their robes that said \\\"Trump Pence MUST GO!\\\"\", \"id\": \"polusa_v1_115877943_-1_5_Others_1_7\"}\n{\"mention\": \"Trump Pence\", \"polarity\": -1, \"from\": 50, \"to\": 61, \"sentence\": \"Others wore patches inside their robes that said \\\"Trump Pence MUST GO!\\\"\", \"id\": \"polusa_v1_115877943_-1_5_Vice President Mike Pence_51_62\"}\n{\"mention\": \"Sentsov\", \"polarity\": -1, \"from\": 15, \"to\": 22, \"sentence\": \"In the photos, Sentsov looks gaunt and weak, noticeably reduced from the 220 pounds he weighed when he entered prison.\", \"id\": \"polusa_v1_115878064_-1_13_Sentsov_15_22\"}\n{\"mention\": \"Sentsov\", \"polarity\": -1, \"from\": 15, \"to\": 22, \"sentence\": \"In the photos, Sentsov looks gaunt and weak, noticeably reduced from the 220 pounds he weighed when he entered prison.\", \"id\": \"polusa_v1_115878064_-1_13_Oleg Sentsov_15_22\"}\n{\"mention\": \"Ashton\", \"polarity\": 1, \"from\": 69, \"to\": 75, \"sentence\": \"The Leeds Family\\nThis drug could provide new hope for thousands like Ashton.\", \"id\": \"polusa_v1_115878583_-1_23_Ashton_70_76\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 3, \"to\": 5, \"sentence\": \"So he slaughtered the animal instead of his son.\", \"id\": \"polusa_v1_115878690_-1_42_Abraham_4_6\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 56, \"to\": 58, \"sentence\": \"\\\"The city may have been safer after his stay there, but he really polluted the city along racial lines.\", \"id\": \"polusa_v1_115878761_-1_52_Giuliani_57_59\"}\n{\"mention\": \"The city\", \"polarity\": -1, \"from\": 1, \"to\": 9, \"sentence\": \"\\\"The city may have been safer after his stay there, but he really polluted the city along racial lines.\", \"id\": \"polusa_v1_115878761_-1_52_the city_2_10\"}\n{\"mention\": \"Isaacs\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Isaacs' candidacy had been clouded by U.S. policies like travel bans and migrant family separations — and his own comments that critics have called anti-Muslim.\", \"id\": \"polusa_v1_115879258_-1_12_Isaacs_1_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 202, \"to\": 207, \"sentence\": \"The employees with which Menendez met were fired after publicly revealing 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\"sentence\": \"\\\"The doses were so high and it did it so fast and all over the body so it would have affected his heart, it would have affected his lungs, it would have affected everything.\\\"\", \"id\": \"polusa_v1_115882885_-1_9_Kim_94_97\"}\n{\"mention\": \"Lee Ming-che\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Lee Ming-che is serving a five-year prison sentence after being convicted by a Chinese court in November of the vaguely defined charge of \\\"subversion of state power.\\\"\", \"id\": \"polusa_v1_115883761_-1_5_Lee_1_13\"}\n{\"mention\": \"Gates\", \"polarity\": 1, \"from\": 13, \"to\": 18, \"sentence\": \"In the U.S., Gates and his wife focus on reshaping America's struggling school systems.\", \"id\": \"polusa_v1_115883804_-1_7_Bill Gates_13_18\"}\n{\"mention\": \"19-year-old Nikolas Cruz\", \"polarity\": -1, \"from\": 183, \"to\": 207, \"sentence\": \"Anthony Borges was shot five times -- both in the gut and legs -- while attempting to shield other pupils by locking a classroom door when he was struck by bullets allegedly fired by 19-year-old Nikolas Cruz.\", \"id\": \"polusa_v1_115884352_-1_3_19-year-old Nikolas Cruz_184_208\"}\n{\"mention\": \"Hyten\", \"polarity\": -1, \"from\": 124, \"to\": 129, \"sentence\": \"Last week, Spletstoser detailed her sexual assault allegations in a New York Times interview where she claimed that in 2017 Hyten came to her hotel room and \\\"pulled her to him and kissed her on the lips while pressing himself against her,\\\" and ejaculated.\", \"id\": \"polusa_v1_115885383_-1_5_Hyten_125_130\"}\n{\"mention\": \"Obamacare\", \"polarity\": -1, \"from\": 28, \"to\": 37, \"sentence\": \"The Latest: Trump says 'let Obamacare implode'\", \"id\": \"polusa_v1_115886648_-1_0_Obamacare_28_37\"}\n{\"mention\": \"Barr\", \"polarity\": 0, \"from\": 105, \"to\": 109, \"sentence\": \"Other Democratic presidential hopefuls like South Bend, Indiana Mayor Pete Buttigieg, say the release of Barr's summary underscores the point that the party can never fully rely on the famed prosecutor's mysterious report as the sole rationale for denying Trump a second term in office.\", \"id\": \"polusa_v1_115887199_-1_54_U.S. Attorney General William Barr_106_110\"}\n{\"mention\": \"Bauman\", \"polarity\": 0, \"from\": 217, \"to\": 223, \"sentence\": \"\\\"In a liquid modern life there are no permanent bonds, and any that we take up for a time must be tied loosely so that they can be untied again, as quickly and as effortlessly as possible, when circumstances change,\\\" Bauman wrote.\", \"id\": \"polusa_v1_115888446_-1_12_Bauman_218_224\"}\n{\"mention\": \"Poland\", \"polarity\": 0, \"from\": 3, \"to\": 9, \"sentence\": \"In Poland, he was a controversial figure in some circles.\", \"id\": \"polusa_v1_115888446_-1_14_Poland_4_10\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 11, \"to\": 13, \"sentence\": \"In Poland, he was a controversial figure in some circles.\", \"id\": 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4, 1946 pogrom in the town of Kielce — where a mob and secret security forces killed at least 40 Jews and two Poles who were defending them — Rosen said that Hlond \\\"did not condemn the pogrom nor urge Poles to stop murdering Jews.\", \"id\": \"polusa_v1_115894413_-1_31_the pogrom_204_214\"}\n{\"mention\": \"Yusuf\", \"polarity\": -1, \"from\": 29, \"to\": 34, \"sentence\": \"As condition of his release, Yusuf is barred from social media and accessing content with extremist views.\", \"id\": \"polusa_v1_115895188_-1_5_Yusuf_30_35\"}\n{\"mention\": \"his release\", \"polarity\": 0, \"from\": 16, \"to\": 27, \"sentence\": \"As condition of his release, Yusuf is barred from social media and accessing content with extremist views.\", \"id\": \"polusa_v1_115895188_-1_5_21-year-old Abdullahi Mohamud Yusuf's release to his family Thursday_17_28\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 156, \"to\": 161, \"sentence\": \"\\\"Nobody is above the law in this country and that 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interviewer called the Russian leader \\\"a killer,\\\" Trump said the United States has many of them.\", \"id\": \"polusa_v1_115903739_-1_2_Putin_42_56\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 22, \"sentence\": \"President Donald Trump said he respects Vladimir Putin, and when an interviewer called the Russian leader \\\"a killer,\\\" Trump said the United States has many of them.\", \"id\": \"polusa_v1_115903739_-1_2_Trump_0_24\"}\n{\"mention\": \"America\", \"polarity\": 1, \"from\": 89, \"to\": 96, \"sentence\": \"While saying he would not critique \\\"every utterance\\\" by Trump, McConnell said he thinks \\\"America's exceptional, America is different, we don't operate in any way the way the Russians do.\", \"id\": \"polusa_v1_115903739_-1_34_America_90_97\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 56, \"to\": 61, \"sentence\": \"While saying he would not critique \\\"every utterance\\\" by Trump, McConnell said he thinks \\\"America's exceptional, America is different, we don't operate in any way the way the Russians do.\", \"id\": \"polusa_v1_115903739_-1_34_Trump_57_62\"}\n{\"mention\": \"her\", \"polarity\": -1, \"from\": 85, \"to\": 88, \"sentence\": \"Four months later, the 19-year-old was arrested for allegedly setting small fires on her former college campus in St. Paul in what prosecutors say was a self-proclaimed act of jihad.\", \"id\": \"polusa_v1_115904184_-1_5_Tnuza Jamal Hassan_86_89\"}\n{\"mention\": \"Maduro\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Maduro spoke Saturday in the capital of Caracas during a celebration of the National Guard's 81 anniversary.\", \"id\": \"polusa_v1_115905126_-1_5_Venezuelan President Nicolas Maduro_0_7\"}\n{\"mention\": \"Hurricane Irma\", \"polarity\": -1, \"from\": 169, \"to\": 183, \"sentence\": \"2. 'IT'S SAD WHEN YOU COME HOME TO THIS'\\nHundreds of people across St. Martin, an island shared by the Dutch and French, are trying to rebuild the lives they had before Hurricane Irma hit.\", \"id\": \"polusa_v1_115905594_-1_4_Irma_170_184\"}\n{\"mention\": \"Charlie\", \"polarity\": 1, \"from\": 32, \"to\": 39, \"sentence\": \"\\\"It was three years after I met Charlie and bonded a fast friendship that I learned he was a Medal of Honor recipient\\\" when Liteky told him about his plans to renounce the medal, Olive said.\", \"id\": \"polusa_v1_115906714_-1_17_Charlie_32_39\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 12, \"to\": 17, \"sentence\": \"Trump fired Flynn early in his term as national security adviser for allegedly misleading Vice President Mike Pence about his contacts with Russian officials.\", \"id\": \"polusa_v1_115908474_-1_12_Flynn_13_18\"}\n{\"mention\": \"Poroshenko\", \"polarity\": -1, \"from\": 110, \"to\": 120, \"sentence\": \"Former Georgian president Mikhail Saakashvili, who leads a Ukrainian opposition party, said at the rally that Poroshenko was responsible for \\\"poverty and humiliation.\\\"\", \"id\": \"polusa_v1_115908637_-1_3_President Petro Poroshenko_111_121\"}\n{\"mention\": \"Pelosi\", \"polarity\": -1, \"from\": 81, \"to\": 87, \"sentence\": \"RADDATZ: -- traded some very big jabs, one (ph) about the State of the Union but Pelosi calling on the president to delay that.\", \"id\": \"polusa_v1_115909542_-1_412_Speaker Pelosi_82_88\"}\n{\"mention\": \"the president\", \"polarity\": -1, \"from\": 130, \"to\": 143, \"sentence\": \"So why does Nancy Pelosi or any other Democrat on Capitol Hill, coming off of this election where they just won big, look at what the president has put on the table and say anything but \\\"no way?\\\"\", \"id\": \"polusa_v1_115909542_-1_425_President Trump_130_143\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 24, \"to\": 26, \"sentence\": \"It's one of the reasons he tells users never to take drugs alone.\", \"id\": \"polusa_v1_115910200_-1_29_overdose survivor Richie Webber_24_26\"}\n{\"mention\": \"Tudor\", \"polarity\": 0, \"from\": 9, \"to\": 14, \"sentence\": \"However, Tudor then received a call from a Southeastern employee who informed her that \\\"Southeastern’s Vice President for Academic Affairs, Dr. Douglas McMillan, had inquired whether Dr. Tudor could be fired because her 'transgender lifestyle' offended his religious beliefs,\\\" the lawsuit states.\", \"id\": \"polusa_v1_115911497_-1_10_Tudor_9_14\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 21, \"to\": 26, \"sentence\": \"Interested in Donald Trump?\", \"id\": \"polusa_v1_115912256_-1_4_— Donald J. Trump (@realDonaldTrump)_22_27\"}\n{\"mention\": \"Gushungo\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Gushungo is one of Mugabe's family names.\", \"id\": \"polusa_v1_115912696_-1_19_Gushungo_0_8\"}\n{\"mention\": \"Mnangagwa\", \"polarity\": 0, \"from\": 14, \"to\": 23, \"sentence\": \"For his part, Mnangagwa did not mention the mug in a statement released Wednesday but criticized \\\"some elements\\\" for trying to turn Mugabe against him.\", \"id\": \"polusa_v1_115912696_-1_24_Mnangagwa_15_24\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 86, \"to\": 91, \"sentence\": \"In taking to the podium himself, Sessions provided another reminder of his loyalty to Trump's core agenda and to the president himself.\", \"id\": \"polusa_v1_115912857_-1_10_President Donald Trump_86_91\"}\n{\"mention\": \"himself\", \"polarity\": 1, \"from\": 24, \"to\": 31, \"sentence\": \"In taking to the podium himself, Sessions provided another reminder of his loyalty to Trump's core agenda and to the president himself.\", \"id\": \"polusa_v1_115912857_-1_10_himself_24_31\"}\n{\"mention\": \"Jobson\", \"polarity\": 0, \"from\": 32, \"to\": 38, \"sentence\": \"She gets along with everybody,” Jobson said.\", \"id\": \"polusa_v1_115913556_-1_16_Trump_32_38\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 21, \"to\": 23, \"sentence\": \"At eight months old, he weighed 2.9 kilograms (6 pounds), a third of the normal weight.\", \"id\": \"polusa_v1_115914193_-1_42_Fadl_21_23\"}\n{\"mention\": \"Johnson\", \"polarity\": 0, \"from\": 24, \"to\": 31, \"sentence\": \"Having traveled so far, Johnson implored Banton to drive the two hours to Sarasota and finally see his sailboat.\", \"id\": \"polusa_v1_115914436_-1_57_Johnson_24_31\"}\n{\"mention\": \"Comey\", \"polarity\": 0, \"from\": 41, \"to\": 46, \"sentence\": \"Trump is disputing reports that he asked Comey for loyalty.\", \"id\": \"polusa_v1_115914577_-1_12_FBI Director James Comey_42_47\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 79, \"to\": 94, \"sentence\": \"Former Director of National Intelligence James Clapper said Russia likely sees President Trump's firing of FBI Director James Comey as \\\"another victory on the scoreboard for them.\\\"\", \"id\": \"polusa_v1_115914577_-1_2_President Trump_81_96\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 4, \"to\": 6, \"sentence\": \"But he said it’s a “professional courtesy” to accept an invitation from the president for dinner.\", \"id\": \"polusa_v1_115914577_-1_9_The former DNI_5_7\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 39, \"to\": 44, \"sentence\": \"In a February interview with Fox News, Trump fondly recalled that he “loved that evening” and “had a great time.”\", \"id\": \"polusa_v1_115914890_-1_11_President Donald Trump_40_45\"}\n{\"mention\": \"Thompson\", \"polarity\": 0, \"from\": 117, \"to\": 125, \"sentence\": \"\\\"You already have Republican governors in some blue states that have their own brand separate from Washington,\\\" said Thompson, pointing to Charlie Baker of Massachusetts and Larry Hogan of Maryland.\", \"id\": \"polusa_v1_115915971_-1_23_Republican Governors Association spokesman Jon Thompson_118_126\"}\n{\"mention\": \"Arpaio\", \"polarity\": -1, \"from\": 14, \"to\": 20, \"sentence\": \"If convicted, Arpaio could face up to six months in jail, though lawyers who have followed his case doubt that a man of his age would be put behind bars.\", \"id\": \"polusa_v1_115916190_-1_10_Arpaio_15_21\"}\n{\"mention\": \"Ivanka Trump\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Ivanka Trump was named assistant to the president last week.\", \"id\": \"polusa_v1_115916526_-1_1_Ivanka Trump_0_14\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said he also knew the suspected gunman, whom he described as \\\"a nice kid most of the times\\\" and said he often joked with the classmates.\", \"id\": \"polusa_v1_115916986_-1_11_science teacher Jason Seaman_1_3\"}\n{\"mention\": \"Pompeo\", \"polarity\": 0, \"from\": 88, \"to\": 94, \"sentence\": \"We will continue to explore additional measures to hold those responsible accountable,\\\" Pompeo said, including possible sanctions against Saudi officials.\", \"id\": \"polusa_v1_115919324_-1_22_Pompeo_88_94\"}\n{\"mention\": \"Tina\", \"polarity\": 1, \"from\": 108, \"to\": 112, \"sentence\": \"The Stewart’s are now vowing to bring awareness to an issue they think is often overlooked but important on Tina’s behalf — domestic violence.\", \"id\": \"polusa_v1_115921240_-1_14_Tina_108_112\"}\n{\"mention\": \"Meng\", \"polarity\": -1, \"from\": 68, \"to\": 72, \"sentence\": \"China has also sentenced a third man to death on drug charges since Meng's arrest in Canada.\", \"id\": \"polusa_v1_115921323_-1_15_Meng_68_72\"}\n{\"mention\": \"Shepard\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Shepard was remembered on Monday by about 800 people who attended a memorial service on Prexy's Pasture, the sprawling green on the University of Wyoming campus that students cross several times a day.\", \"id\": \"polusa_v1_115921381_-1_32_Shepard_1_8\"}\n{\"mention\": \"McKinney\", \"polarity\": -1, \"from\": 81, \"to\": 89, \"sentence\": \"Morales and Herrera said they were the victims of an unprovoked attack, in which McKinney and Henderson repeatedly swore at them on a Laramie street corner.\", \"id\": \"polusa_v1_115921381_-1_43_Aaron McKinney_82_90\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 35, \"to\": 40, \"sentence\": \"Kevin McCarthy, adamantly defended Trump, asserting that the president bears no responsibility for the chants of \\\"send her back\\\" after a week-long back-and-forth with progressive Democrats and charges of racist rhetoric.\", \"id\": \"polusa_v1_115923529_-1_8_Trump_35_40\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 32, \"to\": 35, \"sentence\": \"And for this, I’d never forgive him.\\\"\", \"id\": \"polusa_v1_115923701_-1_11_Donald Trump_32_35\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 34, \"to\": 36, \"sentence\": \"\\\"I absolutely believe it's good,\\\" he said.\", \"id\": \"polusa_v1_115923891_-1_27_President Donald Trump_35_37\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 29, \"to\": 32, \"sentence\": \"\\\"No matter what came her way she tried to make a positive out of the situation.\\\"\", \"id\": \"polusa_v1_115923898_-1_15_college friend Rachel Macdonald_29_32\"}\n{\"mention\": \"the companies\", \"polarity\": -1, \"from\": 57, \"to\": 70, \"sentence\": \"Twitter's CEO will also face angry Republicans who claim the companies have shown evidence of bias against conservatives.\", \"id\": \"polusa_v1_115924511_-1_4_the companies_58_71\"}\n{\"mention\": \"Bibi\", \"polarity\": 1, \"from\": 52, \"to\": 56, \"sentence\": \"If Pakistan's top court upholds its earlier ruling, Bibi will be free to leave for Canada, where her daughters have already been granted asylum.\", \"id\": \"polusa_v1_115924936_-1_6_Aasia Bibi_53_57\"}\n{\"mention\": \"Jonathan Alpeyrie\\nAlpeyrie\", \"polarity\": 1, \"from\": 0, \"to\": 26, \"sentence\": \"Jonathan Alpeyrie\\nAlpeyrie got his big break covering the conflict in East Africa, where he took the iconic picture of a female fighter in Kenya that he calls a \\\"very interesting version of feminism.\\\"\", \"id\": \"polusa_v1_115925060_-1_22_Alpeyrie_0_27\"}\n{\"mention\": \"Jonathan Alpeyrie\", \"polarity\": 1, \"from\": 0, \"to\": 17, \"sentence\": \"Jonathan Alpeyrie\\nAlpeyrie got his big break covering the conflict in East Africa, where he took the iconic picture of a female fighter in Kenya that he calls a \\\"very interesting version of feminism.\\\"\", \"id\": \"polusa_v1_115925060_-1_22_War photographer Jonathan Alpeyrie_1_18\"}\n{\"mention\": \"Meadows\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Meadows would not disclose whether he would oppose the measures as they’re currently crafted.\", \"id\": \"polusa_v1_115925931_-1_18_Meadows_0_7\"}\n{\"mention\": \"Merkel\", \"polarity\": -1, \"from\": 23, \"to\": 29, \"sentence\": \"The pressure is on for Merkel, who in recent weeks has been threatened by German Interior Minister Horst Seehofer -- a longtime rival from Bavarian sister party Christian Social Union -- to close Germany's border with Austria to asylum-seekers previously registered in other EU countries.\", \"id\": \"polusa_v1_115927711_-1_3_Merkel_24_30\"}\n{\"mention\": \"Yellen\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Yellen calls risks of inflation 'two-sided'\", \"id\": \"polusa_v1_115929117_-1_0_Yellen_0_6\"}\n{\"mention\": \"Malaysia\", \"polarity\": 0, \"from\": 216, \"to\": 224, \"sentence\": \"The Exchange 106 skyscraper, which is near completion, is in the heart of the Tun Razak Exchange, a financial district being built by TRX City in Kuala Lumpur and named by Najib after his father Abdul Razak, who was Malaysia's second prime minister.\", \"id\": \"polusa_v1_115929466_-1_12_Malaysia_217_225\"}\n{\"mention\": \"Franklin\", \"polarity\": -1, \"from\": 1, \"to\": 9, \"sentence\": \"\\\"Franklin starts to kick him, once again making contact and kicking Luis in the face,\\\" the inspector wrote.\", \"id\": \"polusa_v1_115929607_-1_43_Franklin_2_10\"}\n{\"mention\": \"William G. Gale, a senior fellow in the Economic Studies Program at the Brookings Institution and former senior economist for the Council of Economic Advisers under President George H.W. Bush\", \"polarity\": 0, \"from\": 0, \"to\": 191, \"sentence\": \"William G. Gale, a senior fellow in the Economic Studies Program at the Brookings Institution and former senior economist for the Council of Economic Advisers under President George H.W. Bush, said while it is important to understand this relationship between corporate tax cuts, growth, and wages, the estimates \\\"are way too high and not well-justified.\\\"\", \"id\": \"polusa_v1_115929913_-1_10_Gale_0_192\"}\n{\"mention\": \"Macri\", \"polarity\": -1, \"from\": 111, \"to\": 116, \"sentence\": \"Then in December, officials announced a rise in the inflation target, which caused investors to begin doubting Macri's commitment to taming price rises.\", \"id\": \"polusa_v1_115930129_-1_20_President Mauricio Macri_112_117\"}\n{\"mention\": \"Strzok\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Strzok has spent much of his law enforcement career working counterintelligence cases and has been unanimously praised by government officials who spoke with ABC News.\", \"id\": \"polusa_v1_115931509_-1_12_Strzok_1_7\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He was previously deported, once after being taken into custody in 2006 when he got caught driving with a fake driver’s license, and another time in 2010 following traffic citation, his lawyer said.\", \"id\": \"polusa_v1_115932242_-1_16_\\\" the 30-year-old Berrones_1_3\"}\n{\"mention\": \"Adam Koenig\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Adam Koenig from the northern Kentucky suburbs of Cincinnati, where Bevin has some of his strongest support.\", \"id\": \"polusa_v1_115932580_-1_38_Adam Koenig_0_11\"}\n{\"mention\": \"Murphy\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Murphy has argued that a Guadagno’s governorship would represent a continuation of Christie’s tenure, while Guadagno has pointed to moments of disagreement with her boss to attempt to distance herself from the two-term governor and former Republican presidential primary candidate.\", \"id\": \"polusa_v1_115932661_-1_18_Murphy_0_6\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 5, \"to\": 8, \"sentence\": \"Lock him up, lock him up, lock him up, lock him up.\", \"id\": \"polusa_v1_115933569_-1_8_Flynn_6_9\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 41, \"to\": 46, \"sentence\": \"To help ease that pain and help shore up Trump's political support in farm states, the Trump administration has rolled out a $12 billion aid package for farmers who have lost markets for their soybeans in China and elsewhere.\", \"id\": \"polusa_v1_115933870_-1_20_President Donald Trump_41_46\"}\n{\"mention\": \"the president\", \"polarity\": 0, \"from\": 9, \"to\": 22, \"sentence\": \"\\\"Whoever the president is, regardless of your political party you want a president to feel welcome and be safe,\\\" Frankel said.\", \"id\": \"polusa_v1_115934564_-1_29_President Trump_10_23\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He also donated $50,000 to the Committee to Protect Journalists.\", \"id\": \"polusa_v1_115934587_-1_21_Gianforte_0_2\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 142, \"to\": 149, \"sentence\": \"Add Interest\\nJason Sullivan, a social media specialist who worked for Stone’s political action committee in 2016, received two subpoenas from Mueller last week, Knut Johnson, a lawyer for Sullivan, told ABC News.\", \"id\": \"polusa_v1_115937474_-1_5_Robert Mueller_142_149\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 13, \"to\": 18, \"sentence\": \"AP\\nPresident Trump also blamed the Democrats for inflating the numbers, a statement that is also not supported by any facts.\", \"id\": \"polusa_v1_115938164_-1_22_Donald Trump_14_19\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 21, \"to\": 24, \"sentence\": \"But Yellen said that she was grateful for the Fed career she did have which covered not only a four-year term as Fed chair but also serving as Fed vice chair for four years before that and also service as president of the Fed's San Francisco regional bank.\", \"id\": \"polusa_v1_115938245_-1_10_Federal Reserve Chair Janet Yellen, the first woman to head the nation's central bank_22_25\"}\n{\"mention\": \"Simson\", \"polarity\": 1, \"from\": 20, \"to\": 26, \"sentence\": \"\\\"I'm for the bill,\\\" Simson said, adding that he's known as someone who has fought for artists before his time at the Sound Exchange.\", \"id\": \"polusa_v1_115938781_-1_26_Simson_21_27\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 45, \"to\": 47, \"sentence\": \"\\\"I'm for the bill,\\\" Simson said, adding that he's known as someone who has fought for artists before his time at the Sound Exchange.\", \"id\": \"polusa_v1_115938781_-1_26_Friedman_46_48\"}\n{\"mention\": \"Assad\", \"polarity\": -1, \"from\": 43, \"to\": 48, \"sentence\": \"Bolton warned Syria's president, Bashar al-Assad, not to use the U.S. drawdown as a pretext to use chemical weapons against Syrians, saying there is \\\"no change\\\" to the U.S. position that their use is a \\\"red line.\\\"\", \"id\": \"polusa_v1_115939145_-1_12_Assad_44_49\"}\n{\"mention\": \"national security adviser John Bolton\", \"polarity\": 1, \"from\": 25, \"to\": 62, \"sentence\": \"The White House has sent national security adviser John Bolton on a mission to allay Israel's concerns about President Donald Trump's decision to withdraw U.S. troops from Syria.\", \"id\": \"polusa_v1_115939145_-1_3_national security adviser John Bolton_27_64\"}\n{\"mention\": \"Israel\", \"polarity\": 0, \"from\": 85, \"to\": 91, \"sentence\": \"The White House has sent national security adviser John Bolton on a mission to allay Israel's concerns about President Donald Trump's decision to withdraw U.S. troops from Syria.\", \"id\": \"polusa_v1_115939145_-1_3_Israel_87_93\"}\n{\"mention\": \"Aisyah\", \"polarity\": 1, \"from\": 56, \"to\": 62, \"sentence\": \"Her former father-in-law Tjia Liang Kiong, wko last saw Aisyah on Jan. 28, described her as a \\\"very kind, polite and respectful person.\\\"\", \"id\": \"polusa_v1_115939719_-1_27_Aisyah_56_62\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 85, \"to\": 88, \"sentence\": \"Her former father-in-law Tjia Liang Kiong, wko last saw Aisyah on Jan. 28, described her as a \\\"very kind, polite and respectful person.\\\"\", \"id\": \"polusa_v1_115939719_-1_27_Quyen_85_88\"}\n{\"mention\": \"O'Rourke\", \"polarity\": -1, \"from\": 54, \"to\": 62, \"sentence\": \"It's also not the first time the president has called O'Rourke \\\"phony\\\" for using the Spanish nickname despite being of Irish heritage.\", \"id\": \"polusa_v1_115940225_-1_14_O'Rourke_55_63\"}\n{\"mention\": \"Manchin\", \"polarity\": 0, \"from\": 97, \"to\": 104, \"sentence\": \"Unless 60 senators support Gorsuch — which would require six more Democrats to join Heitkamp and Manchin — Republicans would have to unilaterally change Senate rules to allow Gorsuch to be confirmed with a simple majority vote in the 100-member Senate.\", \"id\": \"polusa_v1_115940821_-1_12_Manchin_97_104\"}\n{\"mention\": \"Sharif\", \"polarity\": -1, \"from\": 119, \"to\": 125, \"sentence\": \"The manipulation is seen as seeking to prevent the Pakistan Muslim League, the party of disgraced Prime Minister Nawaz Sharif, from returning to power, while giving a shot at running the country to former cricket star Imran Khan and his Pakistan Tehreek-e-Insaf party, or PTI.\", \"id\": \"polusa_v1_115941489_-1_6_Sharif_120_126\"}\n{\"mention\": \"The cabinet secretary\", \"polarity\": -1, \"from\": 13, \"to\": 34, \"sentence\": \"Add Interest\\nThe cabinet secretary came under sharp questioning at the hearing last month and was called out on Twitter for mishearing the housing term “REO” as an OREO cookie.\", \"id\": \"polusa_v1_115941603_-1_5_Housing Secretary Ben Carson_13_34\"}\n{\"mention\": \"the hearing\", \"polarity\": 0, \"from\": 67, \"to\": 78, \"sentence\": \"Add Interest\\nThe cabinet secretary came under sharp questioning at the hearing last month and was called out on Twitter for mishearing the housing term “REO” as an OREO cookie.\", \"id\": \"polusa_v1_115941603_-1_5_the hearing_67_78\"}\n{\"mention\": \"Salvini\", \"polarity\": 0, \"from\": 19, \"to\": 26, \"sentence\": \"In a Twitter post, Salvini wrote he wanted to host Putin and Trump next.\", \"id\": \"polusa_v1_115941775_-1_26_Salvini_19_26\"}\n{\"mention\": \"The Body Shop\", \"polarity\": 1, \"from\": 6, \"to\": 19, \"sentence\": \"While The Body Shop became known for its activist efforts against animal testing, Natura is known for environmental and social efforts.\", \"id\": \"polusa_v1_115941959_-1_6_Body Shop_6_19\"}\n{\"mention\": \"Natura\", \"polarity\": 1, \"from\": 82, \"to\": 88, \"sentence\": \"While The Body Shop became known for its activist efforts against animal testing, Natura is known for environmental and social efforts.\", \"id\": \"polusa_v1_115941959_-1_6_Brazil's Natura_82_88\"}\n{\"mention\": \"McDonald\", \"polarity\": -1, \"from\": 8, \"to\": 16, \"sentence\": \"He said McDonald apologized for what occurred and for embarrassing the department.\", \"id\": \"polusa_v1_115942775_-1_13_Robert McDonald_9_17\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said McDonald apologized for what occurred and for embarrassing the department.\", \"id\": \"polusa_v1_115942775_-1_13_Gwinnett County Police Chief Butch Ayers_1_3\"}\n{\"mention\": \"McDonald\", \"polarity\": 0, \"from\": 41, \"to\": 49, \"sentence\": \"\\\"It shouldn't have happened,\\\" Ayers said McDonald told him.\", \"id\": \"polusa_v1_115942775_-1_14_Robert McDonald_42_50\"}\n{\"mention\": \"Zhang\", \"polarity\": 0, \"from\": 148, \"to\": 153, \"sentence\": \"According to an affidavit filed in federal court, Christensen was under surveillance Thursday when agents overheard him explaining he had kidnapped Zhang.\", \"id\": \"polusa_v1_115943049_-1_13_Professor Lance Cooper_149_154\"}\n{\"mention\": \"Zhang\", \"polarity\": 0, \"from\": 101, \"to\": 106, \"sentence\": \"One belonging to Christensen was first seen in an apartment complex parking lot June 12 — days after Zhang went missing — and investigators questioned him.\", \"id\": \"polusa_v1_115943049_-1_31_Professor Lance Cooper_101_106\"}\n{\"mention\": \"Le Pen\", \"polarity\": -1, \"from\": 4, \"to\": 10, \"sentence\": \"But Le Pen won't win the decisive May 7 runoff unless large numbers break with past voting habits and, like Evrard, abandon traditional, even life-long, allegiances.\", \"id\": \"polusa_v1_115943964_-1_11_presidential candidate Marine Le Pen_4_10\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 132, \"to\": 137, \"sentence\": \"He also expressed deep appreciation for his \\\"symbolic and timely visit immediately after the meetings at the G-20 in Hamburg\\\" where Trump met with Putin.\", \"id\": \"polusa_v1_115944764_-1_6_Donald Trump_132_137\"}\n{\"mention\": \"Putin\", \"polarity\": 0, \"from\": 147, \"to\": 152, \"sentence\": \"He also expressed deep appreciation for his \\\"symbolic and timely visit immediately after the meetings at the G-20 in Hamburg\\\" where Trump met with Putin.\", \"id\": \"polusa_v1_115944764_-1_6_Vladimir Putin_147_152\"}\n{\"mention\": \"Carter\", \"polarity\": 0, \"from\": 124, \"to\": 130, \"sentence\": \"\\\"The Joe Biden in my picture is a close friend helping someone get through a big day, for which I will always be grateful,\\\" Carter wrote.\", \"id\": \"polusa_v1_115945078_-1_11_Carter_125_131\"}\n{\"mention\": \"Pope Francis\", \"polarity\": 0, \"from\": 4, \"to\": 16, \"sentence\": \"Add Pope Francis as an interest to stay up to date on the latest Pope Francis news, video, and analysis from ABC News.\", \"id\": \"polusa_v1_115945237_-1_4_Pope Francis_4_16\"}\n{\"mention\": \"President Uhuru Kenyatta\", \"polarity\": -1, \"from\": 228, \"to\": 252, \"sentence\": \"However, Mahama says election observers don't have the capacity to investigate allegations by 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Department of Public Safety_1_3\"}\n{\"mention\": \"Madonna\", \"polarity\": 1, \"from\": 75, \"to\": 82, \"sentence\": \"Like John Paul, the Argentinian-born Francis is exceedingly devoted to the Madonna, thanks in large part to the strong role that Marian devotions play in the popular piety of Latin American Catholics.\", \"id\": \"polusa_v1_115946796_-1_18_\\\"the real Madonna_76_83\"}\n{\"mention\": \"Jetter\", \"polarity\": -1, \"from\": 1, \"to\": 7, \"sentence\": \"(Jetter eventually pleaded guilty to public consumption of marijuana, and was fined $100.\", \"id\": \"polusa_v1_115947083_-1_40_Jetter_2_8\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He was a big man and he had a big heart to go with it,\\\" Smith said.\", \"id\": \"polusa_v1_115947408_-1_23_Peters_2_4\"}\n{\"mention\": \"Nasheed\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Nasheed's release would have allowed him to contest a presidential election later this 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adventurer, VanHecke had planned a spring break trip to drive from Texas to the Grand Canyon.\", \"id\": \"polusa_v1_115954199_-1_16_the Grand Canyon_178_194\"}\n{\"mention\": \"Senate Majority Leader Mitch McConnell\", \"polarity\": 1, \"from\": 13, \"to\": 51, \"sentence\": \"Add Interest\\nSenate Majority Leader Mitch McConnell thanked President Donald Trump on Wednesday for helping keep the Senate in Republican hands though Democrats won the House.\", \"id\": \"polusa_v1_115956189_-1_5_Senate Majority Leader Mitch McConnell_13_51\"}\n{\"mention\": \"Assad\", \"polarity\": -1, \"from\": 94, \"to\": 99, \"sentence\": \"April 4, 2017: President Donald Trump issues a statement saying that the \\\"heinous\\\" actions of Assad's government are the direct result of Obama administration's \\\"weakness and irresolution.\\\"\", \"id\": \"polusa_v1_115957742_-1_38_President Bashar Assad_95_100\"}\n{\"mention\": \"Arthur\", \"polarity\": -1, \"from\": 106, \"to\": 112, \"sentence\": \"After her conviction, she changed her story and testified that she had discussed killing her husband with Arthur, who wore a wig and painted his face in an attempt to look like a black man.\", \"id\": \"polusa_v1_115958277_-1_18_Arthur_106_112\"}\n{\"mention\": \"Barrow\", \"polarity\": 1, \"from\": 81, \"to\": 87, \"sentence\": \"Jammeh has resisted strong international pressure for him to step down and allow Barrow to take office and allow a peaceful resolution to Gambia's crisis.\", \"id\": \"polusa_v1_115958928_-1_7_Adama Barrow_82_88\"}\n{\"mention\": \"Gambia\", \"polarity\": -1, \"from\": 138, \"to\": 144, \"sentence\": \"Jammeh has resisted strong international pressure for him to step down and allow Barrow to take office and allow a peaceful resolution to Gambia's crisis.\", \"id\": \"polusa_v1_115958928_-1_7_Gambia_139_145\"}\n{\"mention\": \"Braun\", \"polarity\": -1, \"from\": 50, \"to\": 55, \"sentence\": \"Federal Department of Transportation records show Braun's operation has been cited 55 times since September 2015 for unsafe driving violations and 41 times for truck driver \\\"hours of service\\\" violations.\", \"id\": \"polusa_v1_115960218_-1_25_Mike Braun_51_56\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She appeared tired from swimming into the current and was even moving backward as other whales sprinted by her.\", \"id\": \"polusa_v1_115961996_-1_13_Hanson_0_3\"}\n{\"mention\": \"Boudou\", \"polarity\": -1, \"from\": 20, \"to\": 26, \"sentence\": \"In a separate case, Boudou was arrested in early November 2017 on charges of money laundering and illicit association.\", \"id\": \"polusa_v1_115962366_-1_10_former Vice President Amado Boudou_21_27\"}\n{\"mention\": \"Boudou\", \"polarity\": -1, \"from\": 43, \"to\": 49, \"sentence\": \"The decision is a hard fall from grace for Boudou, 55, who also served as economy minister during the 2007-2015 administration of President Cristina Fernandez, and who was the first 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Bailly told him that he remembered the street well because he helped deliver a baby there 27 years ago when he was a \\\"rookie cop,\\\" according to police.\", \"id\": \"polusa_v1_115963047_-1_6_Trooper Michael Patterson_6_15\"}\n{\"mention\": \"McConnell\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"McConnell, who has expressed confidence in Mueller's work, said the Senate's role in the investigation is being performed by the chamber's Intelligence committee.\", \"id\": \"polusa_v1_115963354_-1_9_McConnell_1_10\"}\n{\"mention\": \"Mueller\", \"polarity\": 1, \"from\": 43, \"to\": 50, \"sentence\": \"McConnell, who has expressed confidence in Mueller's work, said the Senate's role in the investigation is being performed by the chamber's Intelligence committee.\", \"id\": \"polusa_v1_115963354_-1_9_Robert Mueller_44_51\"}\n{\"mention\": \"Walter\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Walter is the 63rd member of Virginia State Police to be killed 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reports, policy staff for the tax-writing committee and members of the Trump transition team discussed a proposal in Trump's childcare plan that would allow parents to deduct some childcare expenses from their income taxes. http://abcn.ws/2jpFnwa\\nIN CASE YOU MISSED IT\\nPRESIDENT OBAMA SURPRISES VICE PRESIDENT BIDEN WITH PRESIDENTIAL MEDAL OF FREEDOM.\", \"id\": \"polusa_v1_115988046_-1_46_http://abcn.ws/2hiExTh\\nTRUMP TEAM_89_114\"}\n{\"mention\": \"President-elect Donald Trump\", \"polarity\": -1, \"from\": 51, \"to\": 79, \"sentence\": \"Al Franken of Minnesota says he doesn't trust what President-elect Donald Trump says about the role that Russia played during the 2016 presidential campaign.\", \"id\": \"polusa_v1_115988046_-1_9_DONALD TRUMP_51_79\"}\n{\"mention\": \"the 2016 presidential campaign\", \"polarity\": 0, \"from\": 126, \"to\": 156, \"sentence\": \"Al Franken of Minnesota says he doesn't trust what President-elect Donald Trump says about the role that Russia played 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\"Tweet firestorm\\nAmid an uproar over President Donald Trump's attacks on four Democratic congresswomen of color, in which he tweeted at them to \\\"go back\\\" to where they came from, Democrats in Congress voted to condemn his remarks and to put Republicans on the record with their disapproval.\", \"id\": \"polusa_v1_115989507_-1_8_President Donald Trump_36_58\"}\n{\"mention\": \"Mr. O'Reilly\", \"polarity\": 1, \"from\": 0, \"to\": 12, \"sentence\": \"Mr. O'Reilly is fully committed to supporting our efforts to improve the environment for all our employees at Fox News,\\\" the statement continued.\", \"id\": \"polusa_v1_115989968_-1_20_Bill O'Reilly_0_12\"}\n{\"mention\": \"retired Judge Barbara Jones\", \"polarity\": 0, \"from\": 47, \"to\": 74, \"sentence\": \"\\\"The special master has concluded her review,\\\" retired Judge Barbara Jones said in her latest court filing.\", \"id\": \"polusa_v1_115991634_-1_4_retired Judge Barbara Jones_48_75\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She eventually told family members, including her children when they became teens.\", \"id\": \"polusa_v1_115993020_-1_25_Corfman_0_3\"}\n{\"mention\": \"Gomez\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Gomez says fake news poses \\\"a direct threat to our democracy.\\\"\", \"id\": \"polusa_v1_115993688_-1_8_Assemblyman Jimmy Gomez_1_6\"}\n{\"mention\": \"Ted Cruz\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Ted Cruz and Democratic Congressman Beto O'Rourke faced off in an at-times-testy debate in San Antonio Tuesday evening, as both men sought to paint their opponent as the wrong choice to represent the nation's third-largest state.\", \"id\": \"polusa_v1_115995234_-1_7_Cruz_0_8\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 17, \"to\": 19, \"sentence\": \"Late last night, he issued what many online are calling a \\\"bizarre\\\" statement, condemning recent reports.\", \"id\": 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letter that Vigano chose to read, Benedict confirmed that Francis has a solid theological and philosophical training and he praised the book initiative for showing the \\\"interior continuity\\\" between the two papacies.\", \"id\": \"polusa_v1_116001330_-1_18_Pope Francis_86_93\"}\n{\"mention\": \"Jeff Flake from Arizona\", \"polarity\": 0, \"from\": 0, \"to\": 23, \"sentence\": \"Jeff Flake from Arizona comes a day after Kavanaugh testified before the committee, as did Christine Blasey Ford, who alleges that Kavanaugh sexually assaulted her in high school.\", \"id\": \"polusa_v1_116001449_-1_6_Jeff Flake from Arizona_0_23\"}\n{\"mention\": \"Epstein\", \"polarity\": -1, \"from\": 73, \"to\": 80, \"sentence\": \"In that ruling, Marra cited findings from the Florida investigation into Epstein’s alleged misconduct, and wrote in his opinion “Epstein directed other persons to abuse the girls sexually.\", \"id\": \"polusa_v1_116002479_-1_27_multimillionaire financier Jeffrey Epstein’s 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as it could be dangerous to her case.\", \"id\": \"polusa_v1_116008492_-1_21_British Foreign Minister Johnson_1_8\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 9, \"to\": 11, \"sentence\": \"Instead, he met with the minister for the first time after his wife’s arrest and asked Johnson to take him to Iran in his planned diplomatic visit to Tehran before the end of the New Year.\", \"id\": \"polusa_v1_116008492_-1_26_Richard Ratcliffe_9_11\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 64, \"to\": 69, \"sentence\": \"Senate Minority Leader Chuck Schumer says by picking Kavanaugh, Trump is delivering on his pledge to \\\"punish\\\" women for their choices.\", \"id\": \"polusa_v1_116008846_-1_47_President Trump_65_70\"}\n{\"mention\": \"Fowler\", \"polarity\": -1, \"from\": 46, \"to\": 52, \"sentence\": \"Kalanick on Sunday called the descriptions in Fowler's post \\\"abhorrent,\\\" saying that the actions described have no place at Uber.\", \"id\": 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but, \\\"Others without rehabilitation would have continued to suffer substantially.\\\"\", \"id\": \"polusa_v1_116012876_-1_27_Smith_105_110\"}\n{\"mention\": \"Smith\", \"polarity\": 0, \"from\": 4, \"to\": 9, \"sentence\": \"But Smith, who heads the Center for Brain Injury and Repair and leads the team that has examined 21 of the affected individuals, says they still do not know what kind of exposure is responsible, with microwaves one of a handful of possibilities.\", \"id\": \"polusa_v1_116012876_-1_8_Smith_5_10\"}\n{\"mention\": \"The company\", \"polarity\": 1, \"from\": 0, \"to\": 11, \"sentence\": \"The company says in a statement that its mission is to make roads safer.\", \"id\": \"polusa_v1_116013373_-1_16_Waymo_1_12\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 62, \"to\": 84, \"sentence\": \"Burciaga says no matter what, immigrants deserve respect from President Donald Trump's administration.\", \"id\": \"polusa_v1_116013453_-1_39_President Donald Trump_62_84\"}\n{\"mention\": \"Systrom\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Systrom told ABC News that Instagram plans to add features in the future that will notify users when they may be spending too much time on their phone.\", \"id\": \"polusa_v1_116015487_-1_26_Systrom_0_8\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 75, \"to\": 80, \"sentence\": \"Zervos' lawyers have issued subpoenas seeking a range of information about Trump's behavior toward women, including any Trump campaign documents concerning any woman who accused him of inappropriate touching and any unaired \\\"Apprentice\\\" footage that might feature Trump discussing female contestants in a sexual or inappropriate way.\", \"id\": \"polusa_v1_116015770_-1_21_Trump_76_81\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He was considered a protector of the moderates, but many reformers distrusted him because he was such an insider and because 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\"polusa_v1_131715819_-1_0_Mark Steyn_0_5\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He said his work and his speaking tours have done more for gay people in \\\"flyover states\\\" than pro-gay special interest groups.\", \"id\": \"polusa_v1_131715926_-1_16_Yiannopoulous_1_3\"}\n{\"mention\": \"Pirro\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Pirro: 'There Is a Traitor in the People's House'\", \"id\": \"polusa_v1_131716034_-1_0_Judge Jeanine Pirro_0_5\"}\n{\"mention\": \"Hannity\", \"polarity\": -1, \"from\": 4, \"to\": 11, \"sentence\": \"The Hannity portion, when read alone, is a grim, troubling text, but true art is supposed to challenge you.\", \"id\": \"polusa_v1_131718429_-1_6_Sean Hannity's_4_11\"}\n{\"mention\": \"Rice\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Rice on Sunday retweeted a message that noted Collins had at one point praised Rice and her ties to Maine.\", \"id\": \"polusa_v1_131720075_-1_15_Susan Rice_0_4\"}\n{\"mention\": \"Lamb\", \"polarity\": 1, \"from\": 83, \"to\": 87, \"sentence\": \"Alex Wong/Getty Images\\nNancy Pelosi would prefer not to claim any credit for Conor Lamb’s surprise victory in Pennsylvania’s 18th District on Tuesday.\", \"id\": \"polusa_v1_131720366_-1_4_Conor Lamb the beginning of the end for Nancy Pelosi_83_87\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 32, \"to\": 35, \"sentence\": \"Pelosi said she was rooting for him anyway.\", \"id\": \"polusa_v1_131720366_-1_7_Conor Lamb the beginning of the end for Nancy Pelosi_32_35\"}\n{\"mention\": \"Duncan Hunter\", \"polarity\": -1, \"from\": 0, \"to\": 13, \"sentence\": \"Duncan Hunter and wife indicted for rampant misuse of campaign funds.\", \"id\": \"polusa_v1_131720569_-1_1_Duncan Hunter_0_13\"}\n{\"mention\": \"journalists\", \"polarity\": 1, \"from\": 15, \"to\": 26, \"sentence\": \"At their best, journalists are everything that Trump is not: careful with 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\"polarity\": -1, \"from\": 4, \"to\": 6, \"sentence\": \"But he’s basically a 1 percent guy.\", \"id\": \"polusa_v1_131722214_-1_14_Biden_4_6\"}\n{\"mention\": \"Forrest\", \"polarity\": 0, \"from\": 75, \"to\": 82, \"sentence\": \"In a short time a second flag of truce appeared, with a communication from Forrest, that he would allow Major Bradford twenty minutes in which to move his troops out of the fort, and if it was not done within that time an assault would be ordered.\", \"id\": \"polusa_v1_131722436_-1_76_Forrest_75_82\"}\n{\"mention\": \"Escobar\", \"polarity\": 1, \"from\": 21, \"to\": 28, \"sentence\": \"An eloquent speaker, Escobar was flamboyant, charming, and a man of deep political ambitions.\", \"id\": \"polusa_v1_131722795_-1_12_Escobar_21_28\"}\n{\"mention\": \"Escobar\", \"polarity\": -1, \"from\": 66, \"to\": 73, \"sentence\": \"Narcos captures it all, along with Colombia’s struggle to contain Escobar’s destructive ambitions and the country’s battle against the 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\"id\": \"polusa_v1_131723539_-1_0_Ed Whelan_0_9\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 12, \"to\": 14, \"sentence\": \"And the man he pushed for the job was none other than his own close friend, and former colleague, Brett Kavanaugh.\", \"id\": \"polusa_v1_131723539_-1_39_Ed Whelan_12_14\"}\n{\"mention\": \"Tom Cotton:\\n“\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"Tom Cotton:\\n“We do not recall the President saying these comments specifically but what he did call out was the imbalance in our current immigration system, which does not protect American workers and our national interest,” [the senators] said in a statement.\", \"id\": \"polusa_v1_131724089_-1_30_Tom Cotton:\\n“_0_13\"}\n{\"mention\": \"Cohen\", \"polarity\": 0, \"from\": 14, \"to\": 19, \"sentence\": \"On Wednesday, Cohen’s own attorney, David Schwartz, said explicitly on CNN that Trump was not aware of the NDA or the $130,000 payment when it was made.\", \"id\": 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like Acosta_35_51\"}\n{\"mention\": \"Gillum\", \"polarity\": -1, \"from\": 92, \"to\": 98, \"sentence\": \"He took to Twitter to declare “a great debate victory” for DeSantis and to warn voters that Gillum, if given the chance, would “make Florida the next Venezuela!”\", \"id\": \"polusa_v1_131726081_-1_46_Andrew Gillum_92_98\"}\n{\"mention\": \"Missouri Governor Eric Greitens\", \"polarity\": 0, \"from\": 0, \"to\": 31, \"sentence\": \"Missouri Governor Eric Greitens speaks to the media on February 22, 2017 in University City, Missouri.\", \"id\": \"polusa_v1_131726083_-1_3_Eric Greitens_0_33\"}\n{\"mention\": \"Sloppy Steve\", \"polarity\": -1, \"from\": 8, \"to\": 20, \"sentence\": \"He used Sloppy Steve Bannon, who cried when he got fired and begged for his job.\", \"id\": \"polusa_v1_131726433_-1_17_“sloppy Steve_8_20\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 4, \"to\": 6, \"sentence\": \"But he added, “There’s a danger in pretending each new rally is immediate, urgent.”\", \"id\": \"polusa_v1_131726495_-1_43_Ben Sasse_4_6\"}\n{\"mention\": \"Lewis\", \"polarity\": -1, \"from\": 15, \"to\": 20, \"sentence\": \"It wasn’t just Lewis who used the “Sexual harassment is no big deal” defense on Cain’s behalf.\", \"id\": \"polusa_v1_131726780_-1_28_Jason Lewis_16_21\"}\n{\"mention\": \"Judge Kavanaugh\", \"polarity\": -1, \"from\": 3, \"to\": 18, \"sentence\": \"If Judge Kavanaugh claims to be a mentor and booster of women, his supporters should be extremely careful about even implicitly tarnishing the women who came forward in good faith with truthful complaints.\", \"id\": \"polusa_v1_131727172_-1_48_Judge Kavanaugh_4_19\"}\n{\"mention\": \"Schreck\", \"polarity\": 1, \"from\": 113, \"to\": 120, \"sentence\": \"In What the Constitution Means to Me, which opened Sunday at New York Theatre Workshop and runs through Oct. 28, Schreck takes the stage surrounded by wood-paneled walls and endless rows of white men in military uniforms, attended by a stopwatch-wielding legionnaire as she runs through a re-creation of her prize-winning teenage talk.\", \"id\": \"polusa_v1_131727344_-1_5_Heidi Schreck_114_121\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 34, \"to\": 36, \"sentence\": \"A Southern California Republican, he is the board chairman of the National District Attorneys Association, a powerful group of more than 4,000 prosecutors that meets regularly with the Department of Justice to offer its views on criminal justice policy.\", \"id\": \"polusa_v1_131727349_-1_113_San Bernardino County District Attorney Michael Ramos_34_36\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": 1, \"from\": 6, \"to\": 15, \"sentence\": \"Judge Kavanaugh has also expressed his willingness to discuss the issue with the Committee.\", \"id\": \"polusa_v1_131727552_-1_54_Judge Kavanaugh_6_15\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": -1, \"from\": 86, \"to\": 95, \"sentence\": \"But after Christine Blasey Ford went public over the weekend with her allegation that Kavanaugh sexually assaulted her when the two were in high school, the nomination has taken center stage in the dozen or so races that are most likely to decide control of the Senate.\", \"id\": \"polusa_v1_131727552_-1_5_Judge Kavanaugh_86_95\"}\n{\"mention\": \"Richard Nixon\", \"polarity\": -1, \"from\": 24, \"to\": 37, \"sentence\": \"Gerald Ford’s pardon of Richard Nixon, certainly the broadest in American history, extended to “all offenses against the United States which he … has committed or may have committed or taken part in during the period from January 20, 1969, through August 9, 1974.”\", \"id\": \"polusa_v1_131727629_-1_17_Richard Nixon_24_37\"}\n{\"mention\": \"Barr\", \"polarity\": -1, \"from\": 11, \"to\": 15, \"sentence\": \"As I said, Barr should recuse himself from the Mueller investigation.\", \"id\": \"polusa_v1_131727926_-1_51_“Barr_12_16\"}\n{\"mention\": \"Bernie Sanders\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Bernie Sanders speaks during a rally at Howard University on Monday in Washington, D.C. Alex Wong/Getty Images\\nAs the clear front-runner for the Democratic nomination, Joe Biden knows that he’s all but guaranteed to face attacks from several of his rivals at the first primary debate next month.\", \"id\": \"polusa_v1_131728375_-1_3_Bernie Sanders_0_14\"}\n{\"mention\": \"Biden\", \"polarity\": 0, \"from\": 29, \"to\": 34, \"sentence\": \"It’s simply that Sanders and Biden may not share the stage at all in June.\", \"id\": \"polusa_v1_131728375_-1_6_Joe Biden_29_34\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 148, \"to\": 152, \"sentence\": \"During the course of our conversation, which has been edited and condensed for clarity, we discussed the effect Scott Pruitt had on EPA morale, the Bush administration’s role in undermining faith in the science of climate change, and the myth that environmental protection and a good economy cannot go hand in hand.\", \"id\": \"polusa_v1_131728681_-1_9_Bush_148_152\"}\n{\"mention\": \"Schumer\", \"polarity\": -1, \"from\": 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but that it amounted to “the kind of inappropriate behavior that makes many women feel uncomfortable and unequal in the workplace.”\", \"id\": \"polusa_v1_131730016_-1_41_Former Vice President Joe Biden_21_26\"}\n{\"mention\": \"Kim Jong Un\", \"polarity\": 0, \"from\": 30, \"to\": 41, \"sentence\": \"BREAKING: President Trump and Kim Jong Un just shook hands ahead of their historic summit.\", \"id\": \"polusa_v1_131730135_-1_2_Kim Jong Un_32_43\"}\n{\"mention\": \"Singapore\", \"polarity\": 0, \"from\": 66, \"to\": 75, \"sentence\": \"WATCH: President Trump and Kim Jong Un meet at historic summit in Singapore. https://t.co/MmLKv5K6vV pic.twitter.com/rlVlIPEYLn — NBC News (@NBCNews) June 12, 2018\\n\\\"It's my honor -- we will have a terrific relationship, no doubt,\\\" President Trump says as he sits down with Kim Jong Un. https://t.co/SBcHAGxnM4 pic.twitter.com/47Jw6TdbNu — NBC News (@NBCNews) June 12, 2018\\n“The old prejudices and practices worked as obstacles on our way forward, but we’ve overcome all of them and we are here today,” Kim Jong Un says as he sits down with President Trump in Singapore. pic.twitter.com/2N9opWxsZK — NBC News (@NBCNews) June 12, 2018\\nTrump and Kim conclude their first face-to-face meeting of the day:\\nJUST IN: President Trump and Kim emerge from first meeting.\", \"id\": \"polusa_v1_131730135_-1_6_Singapore_67_76\"}\n{\"mention\": \"a complaint against Trump and Trump’s presidential campaign\", \"polarity\": -1, \"from\": 68, \"to\": 127, \"sentence\": \"On Jan. 22, campaign finance reform organization Common Cause filed a complaint against Trump and Trump’s presidential campaign, accusing them of violating federal election law in relation to the Daniels payment.\", \"id\": \"polusa_v1_131730283_-1_16_a complaint against Trump and Trump’s presidential campaign_69_128\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 10, \"to\": 15, \"sentence\": \"Get ready Comey, because they will be coming, nice and new and “smart!”\", 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accusations of sexual misconduct took a particularly delicious turn Tuesday afternoon, when scrutiny over the pretty clearly fabricated charges turned towards random right wing twitter nut and apparent disgraced hedge fund bro, Jacob Wohl.\", \"id\": \"polusa_v1_131732366_-1_4_Right wing MAGA troll Jacob Wohl_325_329\"}\n{\"mention\": \"Collins\", \"polarity\": 0, \"from\": 19, \"to\": 26, \"sentence\": \"Technically, then, Collins or Manchin alone couldn’t have kept Kavanaugh off the high court.\", \"id\": \"polusa_v1_131733815_-1_20_Susan Collins_19_26\"}\n{\"mention\": \"Dahlia Lithwick\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Dahlia Lithwick is joined by Ted Boutrous, who represented CNN and Jim Acosta in their case against the White House.\", \"id\": \"polusa_v1_131734412_-1_8_Dahlia Lithwick_0_16\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 22, \"to\": 25, \"sentence\": \"The cutaway collar of his shirt hints at his self-conception as a bold, 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\"polarity\": -1, \"from\": 60, \"to\": 71, \"sentence\": \"Musk seems particularly prone to lash out at the press when his company is under the greatest pressure.\", \"id\": \"polusa_v1_131735138_-1_38_Tesla_61_72\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 113, \"to\": 118, \"sentence\": \"“It’s a regime that, frankly, could be toppled very quickly by the military if the military decides to do that,” Trump said.\", \"id\": \"polusa_v1_131735316_-1_21_President Trump_113_118\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 124, \"to\": 126, \"sentence\": \"Flynn, who was facing a judge who has been very tough on prosecutors in the past, likely believed that whatever cooperation he gave was sufficient to ensure that he faced no jail time.\", \"id\": \"polusa_v1_131735425_-1_31_Michael Flynn_124_126\"}\n{\"mention\": \"Epstein\", \"polarity\": -1, \"from\": 84, \"to\": 91, \"sentence\": \"The latest arrest is good news for the long march to justice, but terrible news 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copyright Reuters Image caption Mr Mnangagwa is associated by many with some of the worst atrocities committed under Zanu-PF\\nImage copyright Reuters Image caption In his speech, he paid tribute to his predecessor, Robert Mugabe\\nImage copyright Reuters Image caption He also promised to serve all Zimbabweans, not just members of Zanu-PF\\nImage copyright Reuters Image caption Leaders from several of Zimbabwe's neighbours were present\\nImage copyright Reuters Image caption He is a former minister of defence, and security, and has always enjoyed close ties to the military...\", \"id\": \"polusa_v1_17864917_-1_5_Robert Mugabe_454_467\"}\n{\"mention\": \"Bibi\", \"polarity\": 0, \"from\": 5, \"to\": 9, \"sentence\": \"Asia Bibi: Pakistan Supreme Court's 'historic' ruling\", \"id\": \"polusa_v1_17865008_-1_0_Bibi_5_9\"}\n{\"mention\": \"Bibi\", \"polarity\": -1, \"from\": 60, \"to\": 64, \"sentence\": \"Apart from meeting the quid pro-quo, this would have turned Bibi into a legally 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\"id\": \"polusa_v1_18088798_-1_147_London_97_103\"}\n{\"mention\": \"Cecília Apalai\", \"polarity\": 1, \"from\": 36, \"to\": 50, \"sentence\": \"This would cost a lot of money, but Cecília Apalai says it's essential because indigenous people are obliged to travel to cities to take advantage of their rights as Brazilian citizens.\", \"id\": \"polusa_v1_18090234_-1_53_Cecília Apalai_37_51\"}\n{\"mention\": \"indigenous people\", \"polarity\": 1, \"from\": 79, \"to\": 96, \"sentence\": \"This would cost a lot of money, but Cecília Apalai says it's essential because indigenous people are obliged to travel to cities to take advantage of their rights as Brazilian citizens.\", \"id\": \"polusa_v1_18090234_-1_53_indigenous people_80_97\"}\n{\"mention\": \"Uganda\", \"polarity\": -1, \"from\": 119, \"to\": 125, \"sentence\": \"Julius Kaggwa was born intersex, which made for a confusing, isolating and sometimes dangerous childhood growing up in Uganda.\", \"id\": \"polusa_v1_18090420_-1_1_Uganda_121_127\"}\n{\"mention\": \"\\\" Mr Campbell\", \"polarity\": 0, \"from\": 101, \"to\": 114, \"sentence\": \"\\\"He thinks, probably rightly, that the country has decided it will not put Jeremy Corbyn into office,\\\" Mr Campbell continued.\", \"id\": \"polusa_v1_18093557_-1_10_\\\" Mr Campbell_102_115\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He eventually plead guilty ahead of his trial.\", \"id\": \"polusa_v1_18096846_-1_6_McGilloway_1_3\"}\n{\"mention\": \"Maupin\", \"polarity\": 0, \"from\": 102, \"to\": 108, \"sentence\": \"I've always wanted a gay man to play Michael Tolliver, for instance, he's sort of my alter ego,\\\" says Maupin.\", \"id\": \"polusa_v1_18097042_-1_21_Maupin_102_108\"}\n{\"mention\": \"Maupin\", \"polarity\": 1, \"from\": 126, \"to\": 132, \"sentence\": \"Younger generations of LGBT people may not be aware of Tales of the City existing prior to this Netflix series launching, but Maupin 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\"polusa_v1_39051594_-1_10_Matthew_0_2\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 0, \"from\": 38, \"to\": 50, \"sentence\": \"Facebook Twitter Pinterest From left, Donald Trump and his future wife, Melania Knauss, financier Jeffrey Epstein, and Ghislaine Maxwell pose together at Mar-a-Lago in 2000.\", \"id\": \"polusa_v1_39051772_-1_13_Trump_39_51\"}\n{\"mention\": \"Epstein\", \"polarity\": -1, \"from\": 167, \"to\": 174, \"sentence\": \"Because of his support, I feel I can do anything I want Martin Nowack\\nLawrence Krauss, a physicist who retired from Arizona State University, even continued defending Epstein after his 2008 conviction, telling the Daily Beast in 2011, “As a scientist I always judge things on empirical evidence and he always has women ages 19 to 23 around him, but I’ve never seen anything else, so as a scientist, my presumption is that whatever the problems were I would believe him over other people.”\", \"id\": 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commission] will not be a cure for the problem, but it will go a long way towards holding those who abuse their powers accountable, and towards deterring those who may be tempted to break the rules,” wrote John Raphling, a senior researcher at Human Rights Watch, in a letter to Cuomo in support of the commission.\", \"id\": \"polusa_v1_3960761_-1_18_The commission_59_61\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 23, \"to\": 35, \"sentence\": \"Our selected president Donald Trump isn't only delusional, but his behavior also demonstrates the man chosen, not by Americans but by the outmoded Electoral College, has no inhibitions about shameful conduct.\", \"id\": \"polusa_v1_3960888_-1_4_Donald Trump_23_35\"}\n{\"mention\": \"Our\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"Our selected president Donald Trump isn't only delusional, but his behavior also demonstrates the man chosen, not by Americans but by the outmoded Electoral College, has no inhibitions about shameful conduct.\", \"id\": \"polusa_v1_3960888_-1_4_Our_0_3\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 96, \"to\": 101, \"sentence\": \"As Pride 2016 rolled around, I was still in my own bubble of idealism thanks to the idealism of Obama and my support for Hillary Clinton.\", \"id\": \"polusa_v1_3961434_-1_66_Barack Obama_97_102\"}\n{\"mention\": \"Sarah Huckabee Sanders\", \"polarity\": -1, \"from\": 27, \"to\": 49, \"sentence\": \"An embarrassing tweet from Sarah Huckabee Sanders has reemerged just in time for the bombshell revelation that President Donald Trump was the target of an FBI probe.\", \"id\": \"polusa_v1_3961516_-1_3_Sarah Huckabee Sanders_29_51\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 111, \"to\": 133, \"sentence\": \"An embarrassing tweet from Sarah Huckabee Sanders has reemerged just in time for the bombshell revelation that President Donald Trump was the target of an FBI probe.\", \"id\": \"polusa_v1_3961516_-1_3_President Donald Trump_113_135\"}\n{\"mention\": \"Shafer\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Shafer has been helping at a shelter for those who have been displaced as he works to track down his students, who are spread out between shelters, tents, trailers and houses of family members and friends in other communities.\", \"id\": \"polusa_v1_3961718_-1_43_youth counselor Greg Shafer_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 19, \"to\": 24, \"sentence\": \"Earlier this year, Trump initially denied knowledge of the payment to Daniels, but later admitted Cohen “represented him in this crazy Stormy Daniels deal,” making it more difficult for him to distance himself from Cohen.\", \"id\": \"polusa_v1_3962693_-1_9_President Donald Trump_20_25\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She was responding to conservative commentator Charlie Sykes’ belief that Trump really doesn’t want a 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decades-long history of trustworthiness and professionalism, that no one in the U.S. media has supplied for its American audience previous examples of meticulously detailed, 35-page intelligence memos written by an intelligence agent with a strong reputation and excellent sources that turned out to be—as Mitchell was suggesting of Steele’s work—entirely false and malevolently salacious.\", \"id\": \"polusa_v1_3965205_-1_72_Steele_45_51\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 4, \"to\": 7, \"sentence\": \"But his own words of years past lingered in the air, as acrid as smoke.\", \"id\": \"polusa_v1_3965459_-1_14_President Donald Trump_4_7\"}\n{\"mention\": \"” El-Sayed\", \"polarity\": 0, \"from\": 100, \"to\": 110, \"sentence\": \"“Freshwater is going to become, and it’s quickly becoming, the most important resource in the world,” El-Sayed told HuffPost.\", \"id\": \"polusa_v1_3966056_-1_68_Abdul El-Sayed_101_111\"}\n{\"mention\": \"Manigault Newman\", \"polarity\": 0, 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bullying, bombastic nature toward a more presidential demeanor, it is the Republican Party en masse that has pivoted.\", \"id\": \"polusa_v1_3966847_-1_28_the Republican Party_124_144\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 28, \"to\": 33, \"sentence\": \"But instead of the promised Trump pivot away from his bullying, bombastic nature toward a more presidential demeanor, it is the Republican Party en masse that has pivoted.\", \"id\": \"polusa_v1_3966847_-1_28_Donald Trump_28_33\"}\n{\"mention\": \"Milo Yiannopoulos\", \"polarity\": 1, \"from\": 65, \"to\": 82, \"sentence\": \"Robert Mercer Sells Stake In Breitbart News, Recants Support For Milo Yiannopoulos\", \"id\": \"polusa_v1_3967064_-1_0_Milo Yiannopoulos_65_82\"}\n{\"mention\": \"Moore\", \"polarity\": 0, \"from\": 116, \"to\": 121, \"sentence\": \"That night, in the back row of a theater a few blocks from the state capitol, I watched the first U.S. screening of Moore’s latest movie, SiCKO.\", \"id\": 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\"sentence\": \"Susan Bro Wants To Shift The Focus From Heather Heyer’s Death To Racial Injustice\", \"id\": \"polusa_v1_3976803_-1_0_Heather_40_47\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 310, \"to\": 313, \"sentence\": \"“Alaskans have Lisa Murkowski to thank:” Anchorage rally praises senator for votes against repealing Obamacare https://t.co/keRg53Osqr pic.twitter.com/wf0KZzYcKI — KTVA 11 News (@ktva) July 29, 2017\\nAmong the attendees were some Democrats who had not typically supported Murkowski but said they wanted to show her their gratitude for her role in the health care debate.\", \"id\": \"polusa_v1_3977027_-1_9_Collins_311_314\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 194, \"to\": 197, \"sentence\": \"The proposed town halls sounded doubly ironic because they implied Cosby to be a truth teller who has been wronged and should be believed, instead of the many women who made allegations against him and whom such sanctimonious forums threatened to 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him.\", \"id\": \"polusa_v1_4003199_-1_4_Stephen Wynn_1_9\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 23, \"to\": 26, \"sentence\": \"Democratic voters view him in overwhelmingly favorable terms, as a thoroughly qualified commander-in-chief and an emblem of the Obama administration.\", \"id\": \"polusa_v1_4004167_-1_5_Biden_23_26\"}\n{\"mention\": \"Mr. Rubio\", \"polarity\": 1, \"from\": 30, \"to\": 39, \"sentence\": \"Whether they think so or not, Mr. Rubio and Ms. Trump are lighting the way toward an effective system of paid family leave a quarter-century after we enacted unpaid leave during the first Clinton administration.\", \"id\": \"polusa_v1_4005414_-1_36_Mr. Rubio_31_40\"}\n{\"mention\": \"Ms. Abrams\", \"polarity\": 1, \"from\": 44, \"to\": 54, \"sentence\": \"Ms. Winfrey was energetic in her praise for Ms. Abrams and her policy proposals, but she focused her most impassioned remarks on voting rights, delivering a pointed rebuke to people who might willfully stay 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\"polusa_v1_4021436_-1_8_Bernie Sanders_4_15\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 7, \"to\": 9, \"sentence\": \"There, he showed a pragmatic style and an ability to balance the interests of powerful officials and big business.\", \"id\": \"polusa_v1_4026579_-1_8_Mr. Xi_7_9\"}\n{\"mention\": \"climate change\", \"polarity\": 0, \"from\": 70, \"to\": 84, \"sentence\": \"Like the president he serves, Mr. Wheeler displays little concern for climate change and its epochal challenges.\", \"id\": \"polusa_v1_4027342_-1_8_climate change_70_84\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 37, \"to\": 46, \"sentence\": \"He wants to ask why, time and again, Mr. Trump expressed no concerns with whether Mr. Comey had abided by policy.\", \"id\": \"polusa_v1_4029587_-1_17_Mr. Trump_37_46\"}\n{\"mention\": \"Mr. Mueller\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"Mr. Mueller was apparently unsatisfied.\", \"id\": 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He studied at the Kiev Higher Engineering Radio-Technical College of the Soviet Air Force.\", \"id\": \"polusa_v1_4050274_-1_11_Colonel Petrov_57_59\"}\n{\"mention\": \"Mr. Kilimnik\", \"polarity\": -1, \"from\": 43, \"to\": 55, \"sentence\": \"Mr. Gates, Mr. Manafort’s deputy, believed Mr. Kilimnik to be a “spy.”\", \"id\": \"polusa_v1_4050489_-1_11_Mr. Kilimnik_43_55\"}\n{\"mention\": \"the data\", \"polarity\": 0, \"from\": 28, \"to\": 36, \"sentence\": \"Mr. Gates sent Mr. Kilimnik the data regularly, deleting the WhatsApp messages after he did so.\", \"id\": \"polusa_v1_4050489_-1_14_“internal polling data” private to the campaign with Mr. Kilimnik_28_36\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 124, \"to\": 131, \"sentence\": \"After his July 27 comment, the report states, Mr. Trump “asked individuals affiliated with his Campaign to find the deleted Clinton emails” — including Michael Flynn.\", \"id\": \"polusa_v1_4050489_-1_2_Clinton_126_133\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He swept to re-election in 1936 with 61 percent of the vote, winning all but two states in one of the biggest landslides in American history, and his approval ratings remained high.\", \"id\": \"polusa_v1_4052760_-1_36_Roosevelt_0_2\"}\n{\"mention\": \"a campaign against the conservative Democrats\", \"polarity\": -1, \"from\": 45, \"to\": 90, \"sentence\": \"So Roosevelt put together a team to organize a campaign against the conservative Democrats.\", \"id\": \"polusa_v1_4052760_-1_42_a campaign against the conservative Democrats_45_90\"}\n{\"mention\": \"President Niinisto\", \"polarity\": 0, \"from\": 32, \"to\": 50, \"sentence\": \"But the closest competition for President Niinisto came from Pekka Haavisto, a gay, left-wing Green who reached a second round against Mr. Niinisto in 2012 — a campaign that enchanted liberal-minded celebrities and electrified younger voters, especially in Helsinki.\", \"id\": \"polusa_v1_4053357_-1_2_President Niinisto_34_52\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 61, \"to\": 64, \"sentence\": \"Confronting one of the most serious leadership challenges of his career, Mr. McConnell used all the tools at his disposal — special benefits for some states, appeals to party loyalty, plain old arm-twisting — to win the vote by the narrowest margin possible.\", \"id\": \"polusa_v1_4053812_-1_27_the president_62_65\"}\n{\"mention\": \"Mayor Bill de Blasio\", \"polarity\": -1, \"from\": 0, \"to\": 20, \"sentence\": \"Mayor Bill de Blasio offered no apology for the missives, which provided an unvarnished look at his criticisms of his staff and the media in New York City.\", \"id\": \"polusa_v1_4056024_-1_1_Mayor Bill de Blasio_0_22\"}\n{\"mention\": \"Mr. Pappas\", \"polarity\": 1, \"from\": 7, \"to\": 17, \"sentence\": \"Should Mr. Pappas win in November, he would be the state’s first openly gay representative in Congress.\", \"id\": \"polusa_v1_4056729_-1_12_Chris Pappas_7_17\"}\n{\"mention\": \"former President George W. 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recent days has been vocal in her support of women who have stepped forward to reveal that the producer sexually harassed them or worse.\", \"id\": \"polusa_v1_4085034_-1_12_Mr. Weinstein_48_61\"}\n{\"mention\": \"Mr. Frawley\", \"polarity\": 0, \"from\": 0, \"to\": 11, \"sentence\": \"Mr. Frawley described a different, perhaps more Australian, sensibility.\", \"id\": \"polusa_v1_4089726_-1_12_Mr. Frawley_1_12\"}\n{\"mention\": \"Bernie Sanders\", \"polarity\": 1, \"from\": 4, \"to\": 18, \"sentence\": \"How Bernie Sanders Learned to Walk the Line\", \"id\": \"polusa_v1_4090270_-1_1_Bernie Sanders_4_18\"}\n{\"mention\": \"Mr. Bolton\", \"polarity\": -1, \"from\": 0, \"to\": 10, \"sentence\": \"Mr. Bolton also was accused of attempting to inflate the dangers of Syria’s biological and nuclear weapons programs, by trying to sneak exaggerated assertions into speeches and congressional testimony before being called on it by intelligence officials.\", \"id\": \"polusa_v1_4091030_-1_5_John 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what he said was China’s attempts at backtracking on several commitments it had made during months of negotiations.\", \"id\": \"polusa_v1_4095571_-1_10_President Trump_78_83\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He just wrote me a beautiful letter.\", \"id\": \"polusa_v1_4095571_-1_16_President Trump_1_3\"}\n{\"mention\": \"a beautiful letter\", \"polarity\": 1, \"from\": 18, \"to\": 36, \"sentence\": \"\\\"He just wrote me a beautiful letter.\", \"id\": \"polusa_v1_4095571_-1_16_a beautiful letter_18_36\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 27, \"to\": 32, \"sentence\": \"By the end of this circus, Trump was practically mewling, begging for Putin’s approval, saying that Putin’s denials were “extremely powerful and strong,” almost in a kind of weirdly erotic tone of admiration.\", \"id\": \"polusa_v1_4096279_-1_45_Donald Trump_28_33\"}\n{\"mention\": \"Putin\", \"polarity\": -1, \"from\": 70, \"to\": 75, \"sentence\": 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John Kelly_47_54\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 3, \"to\": 6, \"sentence\": \"In his first year, Trump has delivered fiery speeches to campaign rallies around the country.\", \"id\": \"polusa_v1_4099478_-1_18_President Obama_4_7\"}\n{\"mention\": \"Italy\", \"polarity\": -1, \"from\": 63, \"to\": 68, \"sentence\": \"CLOSE Amanda Knox is getting $20,000 in financial damages from Italy for failing to provide her with legal assistance and a translator in 2007.\", \"id\": \"polusa_v1_4099539_-1_9_Italy_64_69\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 94, \"to\": 99, \"sentence\": \"“Being president has cost me a fortune — a tremendous fortune like you’ve never seen before,” Trump said to reporters last year.\", \"id\": \"polusa_v1_4099972_-1_15_Donald Trump_95_100\"}\n{\"mention\": \"Lamb\", \"polarity\": 1, \"from\": 69, \"to\": 73, \"sentence\": \"To win consistently again, Democrats must understand what helped put Lamb over the top in that corner of 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\"polusa_v1_4101796_-1_13_Heyer_39_44\"}\n{\"mention\": \"Heyer\", \"polarity\": 1, \"from\": 18, \"to\": 23, \"sentence\": \"Friends described Heyer as a woman with a generous spirit and strong sense of justice.\", \"id\": \"polusa_v1_4101796_-1_97_Heyer_19_24\"}\n{\"mention\": \"Tenney\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Tenney's Democratic opponent, state Assemblyman Anthony Brindisi, was graded an \\\"F.\\\" Brindisi has gone against the majority of Democrats in the Assembly and voted against the SAFE Act, which is not favored by gun owners.\", \"id\": \"polusa_v1_4103516_-1_26_\\\"Congresswoman Claudia Tenney_0_6\"}\n{\"mention\": \"Evers\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Evers formed The Historic Preservation Society Inc. days after the judgement in what he said was an effort to “preserve historic monuments that are threatened with destruction.”\", \"id\": \"polusa_v1_4105137_-1_24_Greg Evers_1_6\"}\n{\"mention\": \"Jack 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and so I think that's what we're really seeing, even though things are hitting the fan right now, we're seeing people activate and educate themselves.\\\"\", \"id\": \"polusa_v1_4111567_-1_11_Alexandria Ocasio-Cortez_1_4\"}\n{\"mention\": \"we\", \"polarity\": 1, \"from\": 126, \"to\": 128, \"sentence\": \"She continued: \\\"But you know, times of great challenge can also bring out the best in people, too, and so I think that's what we're really seeing, even though things are hitting the fan right now, we're seeing people activate and educate themselves.\\\"\", \"id\": \"polusa_v1_4111567_-1_11_we_127_129\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": -1, \"from\": 9, \"to\": 18, \"sentence\": \"Fighting Kavanaugh's confirmation is hopeless\\nIn the eyes of many Democratic party activists, of course, votes for confirmation by the three endangered senators and a few others somewhat less vulnerable would be selling out for the cheapened coin of incumbency.\", \"id\": \"polusa_v1_4113215_-1_31_Judge Brett Kavanaugh outside Sen._10_19\"}\n{\"mention\": \"Jim Acosta\", \"polarity\": -1, \"from\": 77, \"to\": 87, \"sentence\": \"— Anne Frank Center (@AnneFrankCenter) August 2, 2017\\nStephen Miller calling Jim Acosta ignorant on live TV is officially the best thing I've seen this week.\", \"id\": \"polusa_v1_4113667_-1_27_Jim Acosta_77_87\"}\n{\"mention\": \"media professor Mira Sotirovic\", \"polarity\": 1, \"from\": 98, \"to\": 128, \"sentence\": \"The eight-week course, scheduled for the second half of the fall 2018 semester, will be taught by media professor Mira Sotirovic for both journalism and non-journalism students at the university's Urbana-Champaign campus.\", \"id\": \"polusa_v1_4114400_-1_5_media professor Mira Sotirovic_99_129\"}\n{\"mention\": \"House Speaker Nancy Pelosi\", \"polarity\": -1, \"from\": 70, \"to\": 96, \"sentence\": \"CLOSE\\nWhite House counselor Kellyanne Conway is taking verbal jabs at House Speaker Nancy Pelosi 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ground beef spiced with chili peppers, onions and tomato sauce – mend her up, urge her to stay and pray as Ramirez slipped back into the streets, again and again.\", \"id\": \"polusa_v1_4147287_-1_46_Benavides_0_3\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 23, \"to\": 28, \"sentence\": \"Throughout his tenure, Trump has tried to repeal the ACA.\", \"id\": \"polusa_v1_4147304_-1_42_Trump_23_28\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 11, \"to\": 14, \"sentence\": \"Throughout his tenure, Trump has tried to repeal the ACA.\", \"id\": \"polusa_v1_4147304_-1_42_Brown_11_14\"}\n{\"mention\": \"Taylor\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Taylor says they no longer count as campaign material.\", \"id\": \"polusa_v1_4149725_-1_69_Taylor_0_6\"}\n{\"mention\": \"Martin Luther King Jr.\", \"polarity\": 0, \"from\": 0, \"to\": 22, \"sentence\": \"Martin Luther King Jr. quotes: 10 most popular\", \"id\": \"polusa_v1_4154894_-1_0_Martin Luther King 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President Vladimir Putin\", \"polarity\": 0, \"from\": 35, \"to\": 67, \"sentence\": \"Skip in Skip x Embed x Share CLOSE Russian President Vladimir Putin says Donald Trump asked him numerous questions about Russia's alleged interference in the US election, and he said there are no grounds to think Russia interfered in the US election.\", \"id\": \"polusa_v1_4160469_-1_2_Russian President Vladimir Putin_37_69\"}\n{\"mention\": \"Amash\", \"polarity\": 1, \"from\": 20, \"to\": 25, \"sentence\": \"Trump lashed out at Amash in the following days, but Amash has held strong on his call for impeachment.\", \"id\": \"polusa_v1_4164921_-1_29_Justin Amash_20_25\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 71, \"to\": 76, \"sentence\": \"Reed died last year — but that advice bears repeating now, in light of Trump's visit Friday to Lake Okeechobee in Florida to talk about Everglades funding and the Herbert Hoover Dike that encircles the giant lake.\", \"id\": \"polusa_v1_4165143_-1_12_Donald Trump's_72_77\"}\n{\"mention\": \"Franken\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Franken was elected to the Senate in 2008.\", \"id\": \"polusa_v1_4169215_-1_75_Al Franken_0_8\"}\n{\"mention\": \"Republican U.S. Rep.\", \"polarity\": 0, \"from\": 56, \"to\": 76, \"sentence\": \"Sherrill got into the race last year to take on 12-term Republican U.S. Rep.\", \"id\": \"polusa_v1_4169834_-1_163_Republican U.S. Rep._57_77\"}\n{\"mention\": \"Texas\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Texas Monthly recently reported that those survivors even now believe that Koresh “was not a crazed cult leader, or a delusional narcissist, or even merely a gifted interpreter of scripture, but a genuine prophet of God.”\", \"id\": \"polusa_v1_4170097_-1_35_Texas_1_6\"}\n{\"mention\": \"Facebook\", \"polarity\": -1, \"from\": 6, \"to\": 14, \"sentence\": \"Notes Facebook CEO Mark Zuckerberg brought with him as he testified before 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victory over Roy Moore in Alabama\\nRepublican party in-fighting is another challenge for Trump's White House.\", \"id\": \"polusa_v1_4177916_-1_44_Alabama_143_151\"}\n{\"mention\": \"Moore\", \"polarity\": -1, \"from\": 45, \"to\": 50, \"sentence\": \"► Analysis: Trump mocks Franken, reticent on Moore despite his own history\\n► Top takeaways: On Doug Jones' shocking victory over Roy Moore in Alabama\\nRepublican party in-fighting is another challenge for Trump's White House.\", \"id\": \"polusa_v1_4177916_-1_44_scandal-ridden Roy Moore_46_51\"}\n{\"mention\": \"Among Bolton's fans: Donald J. Trump\", \"polarity\": 0, \"from\": 0, \"to\": 36, \"sentence\": \"Among Bolton's fans: Donald J. Trump.\", \"id\": \"polusa_v1_4178742_-1_43_Among Bolton's fans: Donald J. Trump_0_37\"}\n{\"mention\": \"Kemp\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Kemp \\\"ran a great race in Georgia – he won,\\\" Trump wrote \\\"It is time to move on!\\\"\", \"id\": \"polusa_v1_4180752_-1_19_Kemp_1_5\"}\n{\"mention\": \"Georgia\", \"polarity\": 0, \"from\": 26, \"to\": 33, \"sentence\": \"Kemp \\\"ran a great race in Georgia – he won,\\\" Trump wrote \\\"It is time to move on!\\\"\", \"id\": \"polusa_v1_4180752_-1_19_Georgia_27_34\"}\n{\"mention\": \"Escobar\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Escobar said it’s a temporary site with roll-out mattresses, showers, medical facilities and air conditioning.\", \"id\": \"polusa_v1_4181573_-1_17_Veronica Escobar_0_7\"}\n{\"mention\": \"CLOSE Thirteen KKK members\", \"polarity\": -1, \"from\": 0, \"to\": 26, \"sentence\": \"CLOSE Thirteen KKK members cooked hot dogs, gave poorly-heard speeches as hundreds protest them in Madison, Indiana.\", \"id\": \"polusa_v1_4187643_-1_2_CLOSE Thirteen KKK members_0_28\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 1, \"to\": 4, \"sentence\": \"\\\"She loved it here, she really did.\", \"id\": \"polusa_v1_4189499_-1_16_Kate_2_5\"}\n{\"mention\": \"Bernie Sanders\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Bernie Sanders takes in the crowd at a presidential campaign event in New York last year.\", \"id\": \"polusa_v1_4190673_-1_2_Sanders_0_16\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 41, \"to\": 56, \"sentence\": \"Mike Pence: 'No comparison' between his, Hillary Clinton's email practices\", \"id\": \"polusa_v1_4190915_-1_0_Hillary Clinton_41_56\"}\n{\"mention\": \"the President\", \"polarity\": -1, \"from\": 110, \"to\": 123, \"sentence\": \"House Speaker Nancy Pelosi announced the resolution Monday in a letter to those in her caucus, writing that, \\\"the President went beyond his own low standards using disgraceful language about Members of Congress.\\\"\", \"id\": \"polusa_v1_4191194_-1_5_President Donald Trump_111_124\"}\n{\"mention\": \"Warren\", \"polarity\": -1, \"from\": 152, \"to\": 158, \"sentence\": \"Big tech companies provide many free services and should not be penalized \\\"for earning market share and operating at scale—yet that is exactly what the Warren proposal would do,\\\" said Rob Atkinson, president of the Information Technology & Innovation Foundation, a non-profit Washington, D.C. think tank, in a statement.\", \"id\": \"polusa_v1_4192518_-1_22_Warren_153_159\"}\n{\"mention\": \"Warren\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Warren’s plan may be warranted.\\\"\", \"id\": \"polusa_v1_4192518_-1_25_Elizabeth Warren Medium_0_6\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 12, \"to\": 15, \"sentence\": \"Warren says her administration would recommend the passage of legislation requiring tech companies with annual global revenue of $25 billion or more be designated as “Platform Utilities” and not be allowed to have \\\"any participant on that platform.\\\"\", \"id\": \"polusa_v1_4192518_-1_31_she_13_16\"}\n{\"mention\": \"John F. Kennedy\", \"polarity\": 0, \"from\": 137, \"to\": 152, \"sentence\": \"Arlington National Cemetery served as the backdrop for Wednesday's memorial service to remember RFK, the younger brother of President of John F. Kennedy and once presidential hopeful who was assassinated in a Los Angeles hotel on June 6, 1968.\", \"id\": \"polusa_v1_4193944_-1_1_Robert F. Kennedy_139_154\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He did not say what those amendments entail.\", \"id\": \"polusa_v1_4194247_-1_6_Boston Mayor Marty Walsh_0_2\"}\n{\"mention\": \"Joe Biden\", \"polarity\": -1, \"from\": 25, \"to\": 34, \"sentence\": \"Kamala Harris went after Joe Biden for his past on busing.\", \"id\": \"polusa_v1_4194254_-1_4_\\\" Biden_25_34\"}\n{\"mention\": \"Venable\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Venable, who had been implicated in a prior violent assault against a fellow prisoner while housed at the Lewisburg, Pennsylvania federal prison in 2014, was pronounced dead at a local hospital.\", \"id\": \"polusa_v1_4195116_-1_10_Venable_1_8\"}\n{\"mention\": \"President Donald Trump's former campaign manager Paul Manafort\", \"polarity\": -1, \"from\": 18, \"to\": 80, \"sentence\": \"In one afternoon, President Donald Trump's former campaign manager Paul Manafort was found guilty of eight criminal counts, including fraud; and his former fixer Michael Cohen pleaded guilty to, among other things, making illegal payoffs to benefit the president's campaign.\", \"id\": \"polusa_v1_4195650_-1_9_President Donald Trump's former campaign manager Paul Manafort_19_81\"}\n{\"mention\": \"Michael Cohen\", \"polarity\": -1, \"from\": 162, \"to\": 175, \"sentence\": \"In one afternoon, President Donald Trump's former campaign manager Paul Manafort was found guilty of eight criminal counts, including fraud; and his former fixer Michael Cohen pleaded guilty to, among other things, making illegal payoffs to benefit the president's campaign.\", \"id\": \"polusa_v1_4195650_-1_9_Michael Cohen_163_176\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He’s more than earned the right to speak out on these matters.\", \"id\": \"polusa_v1_4196667_-1_15_Jones_1_3\"}\n{\"mention\": \"Pluto\", \"polarity\": 0, \"from\": 5, \"to\": 10, \"sentence\": \"Will Pluto 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of Foreign Wars.\", \"id\": \"polusa_v1_4206620_-1_6_Donald Trump_123_130\"}\n{\"mention\": \"last week\", \"polarity\": 0, \"from\": 82, \"to\": 91, \"sentence\": \"USA TODAY\\nA Connecticut man who received a phone call from President Donald Trump last week died on Wednesday, eight days after the president had fulfilled the man's bucket list wish.\", \"id\": \"polusa_v1_4206886_-1_3_last week_82_91\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": 1, \"from\": 59, \"to\": 81, \"sentence\": \"USA TODAY\\nA Connecticut man who received a phone call from President Donald Trump last week died on Wednesday, eight days after the president had fulfilled the man's bucket list wish.\", \"id\": \"polusa_v1_4206886_-1_3_President Donald Trump_59_81\"}\n{\"mention\": \"Samantha Bee\", \"polarity\": -1, \"from\": 93, \"to\": 105, \"sentence\": \"— Britt McHenry (@BrittMcHenry) May 31, 2018\\n\\\"If Roseanne lost her show for tweeting a joke, Samantha Bee should be on the same list for spewing real, vile hatred on live TV.\", \"id\": \"polusa_v1_4207420_-1_34_Samantha Bee_93_105\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 6, \"to\": 11, \"sentence\": \"While Trump's anti-Franken tweets reflect his life-long penchant to counter-attack enemies, they also opened the door for the president's critics to revive the many sexual misconduct allegations against him.\", \"id\": \"polusa_v1_4208360_-1_7_Trump_7_12\"}\n{\"mention\": \"Rehnquist\", \"polarity\": 1, \"from\": 49, \"to\": 58, \"sentence\": \"Race and gay rights\\nFormer chief justice William Rehnquist, shown here with President Ronald Reagan and former associate justice Antonin Scalia, is among Supreme Court nominee Brett Kavanaugh's heroes.\", \"id\": \"polusa_v1_4209693_-1_38_Rehnquist_50_59\"}\n{\"mention\": \"Moon\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Moon briefed reporters on his surprise Saturday meeting with Kim, which took place on the North Korean side of the Panmunjom border village inside the Demilitarized Zone that divides the peninsula.\", \"id\": \"polusa_v1_4211187_-1_5_Moon_0_5\"}\n{\"mention\": \"FaceApp\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"FaceApp, which lets you take a photo of yourself and add a filter that shows you much older, is raising some concerns with privacy experts.\", \"id\": \"polusa_v1_4212589_-1_1_#FaceApp_2_9\"}\n{\"mention\": \"FaceApp\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"FaceApp, which lets you take a photo of yourself and add a filter that shows you much older, is raising some concerns with privacy experts.\", \"id\": \"polusa_v1_4212589_-1_1_FaceApp_2_9\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 39, \"to\": 44, \"sentence\": \"In one of his first acts as president, Trump signed an executive order in February 2017 to undo the clean water rule and instructed the EPA and the U.S. Army Corps of Engineers to come up with a new approach.\", \"id\": \"polusa_v1_4214219_-1_11_President Donald Trump_40_45\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 130, \"to\": 135, \"sentence\": \"Video provided by AFP Newslook 32 of 60 CLOSE Skip in Skip x Embed x Share TRUMP IN TRANSITION Palin seems eager to win a spot in Trump's cabinet | 1:27 She shared a video touting her commitment to veterans after reports surfaced that she's being considered for secretary of Veterans Affairs.\", \"id\": \"polusa_v1_4214894_-1_49_| 0:42 Donald Trump_130_135\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 13, \"to\": 15, \"sentence\": \"But it seems he also wanted to make peace.\", \"id\": \"polusa_v1_4214894_-1_68_Donald Trump's_13_15\"}\n{\"mention\": \"Manafort\", \"polarity\": -1, \"from\": 11, \"to\": 19, \"sentence\": \"Last week, Manafort was ordered to jail pending trial after he was accused in a witness tampering scheme.\", \"id\": \"polusa_v1_4215785_-1_8_\\\"Manafort_12_20\"}\n{\"mention\": \"Putin\", \"polarity\": -1, \"from\": 18, \"to\": 23, \"sentence\": \"That is something Putin has been loath to do since the Syrian leader is one of his few allies in the Middle East.\", \"id\": \"polusa_v1_4216529_-1_15_Putin_18_23\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She eventually spent five days in jail for refusing to follow court orders.\", \"id\": \"polusa_v1_4216832_-1_12_Matthew Barzun_0_3\"}\n{\"mention\": \"Mariah Carey\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Mariah Carey knew nothing about this.\", \"id\": \"polusa_v1_4217579_-1_13_Mariah Carey_0_12\"}\n{\"mention\": \"Harry Potter\", \"polarity\": 1, \"from\": 43, \"to\": 55, \"sentence\": \"USA TODAY\\nThe Internet is 9¾ obsessed with Harry Potter today\\nThanks, Harry, for making Muggles everywhere feel old.\", \"id\": \"polusa_v1_4218292_-1_17_Harry Potter_43_55\"}\n{\"mention\": \"USA TODAY\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"USA TODAY\\nThe Internet is 9¾ obsessed with Harry Potter today\\nThanks, Harry, for making Muggles everywhere feel old.\", \"id\": \"polusa_v1_4218292_-1_17_USA TODAY_0_10\"}\n{\"mention\": \"Harry Potter\", \"polarity\": 1, \"from\": 46, \"to\": 58, \"sentence\": \"And this magical thing happens when you type \\\"Harry Potter\\\" into Facebook.\", \"id\": \"polusa_v1_4218292_-1_22_Harry Potter_46_58\"}\n{\"mention\": \"Hogg\", \"polarity\": 0, \"from\": 97, \"to\": 101, \"sentence\": \"\\\"The apology ... was kind of expected, especially after so many of her advertisers dropped out,\\\" Hogg said.\", \"id\": \"polusa_v1_4220142_-1_26_Hogg_97_101\"}\n{\"mention\": \"Apuron\", \"polarity\": -1, \"from\": 22, \"to\": 28, \"sentence\": \"Archbishop Anthony S. Apuron was found guilty of 'certain accusations' of crimes related to the sexual abuse of minors.\", \"id\": \"polusa_v1_4220220_-1_1_Apuron_24_30\"}\n{\"mention\": \"Archbishop Anthony S. Apuron\", \"polarity\": -1, \"from\": 0, \"to\": 28, \"sentence\": \"Archbishop Anthony S. Apuron was found guilty of 'certain accusations' of crimes related to the sexual abuse of minors.\", \"id\": \"polusa_v1_4220220_-1_1_Archbishop Anthony S. 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\"sentence\": \"More: President Donald Trump on Anthony Scaramucci: He was 'totally incapable of handling' White House job\\nMore: Anthony Scaramucci: Replace Donald Trump as Republican nominee in 2020\\nMore: Scaramucci on Trump: 'Very clear that it’s impossible for him to win'\\nTrump has recently escalated his rhetorical war with his former staffer and has called him \\\"totally incapable of handling\\\" his White House job.\", \"id\": \"polusa_v1_4221104_-1_12_WASHINGTON – President Donald Trump_205_210\"}\n{\"mention\": \"Anthony Scaramucci\", \"polarity\": -1, \"from\": 32, \"to\": 50, \"sentence\": \"More: President Donald Trump on Anthony Scaramucci: He was 'totally incapable of handling' White House job\\nMore: Anthony Scaramucci: Replace Donald Trump as Republican nominee in 2020\\nMore: Scaramucci on Trump: 'Very clear that it’s impossible for him to win'\\nTrump has recently escalated his rhetorical war with his former staffer and has called him \\\"totally incapable of handling\\\" his White House job.\", \"id\": \"polusa_v1_4221104_-1_12_Anthony Scaramucci_33_51\"}\n{\"mention\": \"Scaramucci\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Scaramucci, for his part, has called for the Republican Party to drop Trump as its nominee, anhe was noncommital on future support for Trump.\", \"id\": \"polusa_v1_4221104_-1_13_Scaramucci_0_10\"}\n{\"mention\": \"Porter\", \"polarity\": -1, \"from\": 52, \"to\": 58, \"sentence\": \"Hours later, after pictures surfaced showing one of Porter's ex-wives with a black eye, Kelly issued a more critical statement saying he \\\"was shocked\\\" by \\\"the new allegations released today.\\\"\", \"id\": \"polusa_v1_4221190_-1_20_White House staff secretary Rob Porter_52_58\"}\n{\"mention\": \"Rachel McCauley\", \"polarity\": -1, \"from\": 0, \"to\": 15, \"sentence\": \"Rachel McCauley told board investigators she wrote prescriptions for people she suspected were not taking the pills, but selling them, and that she felt only about half the patients she saw at Hanson's clinic had legitimate needs for oxycodone, which she estimated made up 65% of all her prescriptions.\", \"id\": \"polusa_v1_4222396_-1_26_Rachel McCauley_0_15\"}\n{\"mention\": \"Driscoll\", \"polarity\": -1, \"from\": 34, \"to\": 42, \"sentence\": \"To the DEA, those numbers suggest Driscoll is \\\"likely prescribing Oxycodone to patients without a legitimate medical purpose.\\\"\", \"id\": \"polusa_v1_4222396_-1_36_Julie Driscoll_35_43\"}\n{\"mention\": \"Brown\", \"polarity\": 0, \"from\": 110, \"to\": 115, \"sentence\": \"\\\"She stayed on the ground the whole time — never saw him, just saw his boots as he walked around the church,\\\" Brown said.\", \"id\": \"polusa_v1_4222809_-1_24_David Brown_111_116\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 99, \"to\": 101, \"sentence\": \"Grassley said the president should refrain from nominating a justice during campaign season and if he does, the Senate should refuse to consider the nomination\\nRead more commentary:\\nConservatives are already packing the courts.\", \"id\": \"polusa_v1_4223374_-1_12_President Barack Obama_99_101\"}\n{\"mention\": \"Grassley\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Grassley, meanwhile, is dodging responsibility for keeping his word.\", \"id\": \"polusa_v1_4223374_-1_34_Grassley_0_9\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 7, \"to\": 10, \"sentence\": \"I wish him and his family all the best.\\\"\", \"id\": \"polusa_v1_4226506_-1_26_Ducey_7_10\"}\n{\"mention\": \"Ducey\", \"polarity\": 0, \"from\": 51, \"to\": 56, \"sentence\": \"Other names have been mentioned as well, including Ducey's former chief-of-staff, Kirk Adams, and state Treasurer Eileen Klein.\", \"id\": \"polusa_v1_4226506_-1_36_Ducey_52_57\"}\n{\"mention\": \"Koch\", \"polarity\": -1, \"from\": 14, \"to\": 18, \"sentence\": \"The globalist Koch Brothers, who have become a total joke in real Republican circles, are against Strong Borders and Powerful Trade.\", \"id\": \"polusa_v1_4229879_-1_25_David Koch_15_19\"}\n{\"mention\": \"Leonard\", \"polarity\": 0, \"from\": 51, \"to\": 58, \"sentence\": \"— Donald J. Trump (@realDonaldTrump) July 31, 2018\\nLeonard explained the rift between the Kochs and Trump:\\n\\\"The Koch network is seeking to maintain this idea that Republicans stand for limited government, free markets and open trade, whereas Trump is trying to push it toward America first, nationalism, pro-middle class interventions in the market,\\\" he said.\", \"id\": \"polusa_v1_4229879_-1_29_Leonard_51_58\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 13, \"to\": 18, \"sentence\": \"But ahead of Trump's live televised address, media analysts and skeptics voiced concern over the potential for on-air falsehoods from a president with a documented history of straying from fact.\", \"id\": \"polusa_v1_4229941_-1_5_CLOSE President Trump_14_19\"}\n{\"mention\": \"Nunes'\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Nunes' lawsuit now attributes the close race to Twitter, as well.\", \"id\": \"polusa_v1_4230267_-1_28_Devin Nunes'_1_7\"}\n{\"mention\": \"Cuomo\", \"polarity\": -1, \"from\": 23, \"to\": 28, \"sentence\": \"Nixon referred back to Cuomo's recent comment that America \\\"was never that great,\\\" which drew a rebuke from Trump.\", \"id\": \"polusa_v1_4230790_-1_16_Cuomo_24_29\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 63, \"to\": 66, \"sentence\": \"He'd just taken a bottle full of antidepressant pills, he told her.\", \"id\": \"polusa_v1_4230846_-1_70_Sandy Metzmeier_63_66\"}\n{\"mention\": \"Kraft\", \"polarity\": 0, \"from\": 198, \"to\": 203, \"sentence\": \"#DemDebates#CNNDebate@KSMKidScoop#BehindTheScenespic.twitter.com/0Nj0auy6Tb — Nico Maounis (@nicomaounis) July 31, 2019\\nWhen asked what animal she would take with her to Washington, Williamson told Kraft, \\\"I love cats but I had a dog when I was a child.\", \"id\": \"polusa_v1_4231813_-1_13_Jeffrey Kraft_198_203\"}\n{\"mention\": \"Delaware\", \"polarity\": 0, \"from\": 148, \"to\": 156, \"sentence\": \"The News Journal\\nAfter graduating from Archmere 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\"polusa_v1_4233015_-1_7_Shelley Moore Capito of West Virginia_71_77\"}\n{\"mention\": \"Tuesday\", \"polarity\": 0, \"from\": 82, \"to\": 89, \"sentence\": \"\\\"As I have said before, I did not come to Washington to hurt people,\\\" Capito said Tuesday in a statement.\", \"id\": \"polusa_v1_4233015_-1_7_Tuesday_83_90\"}\n{\"mention\": \"Jean Cramer\", \"polarity\": -1, \"from\": 33, \"to\": 44, \"sentence\": \"Marysville Mayor Dan Damman said Jean Cramer submitted a letter withdrawing Monday, after she said she wanted the town to be as white \\\"as possible.\\\"\", \"id\": \"polusa_v1_4233587_-1_1_Marysville council candidate Jean Cramer_35_46\"}\n{\"mention\": \"Marysville\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Marysville Mayor Dan Damman said Jean Cramer submitted a letter withdrawing Monday, after she said she wanted the town to be as white \\\"as possible.\\\"\", \"id\": \"polusa_v1_4233587_-1_1_Marysville_2_12\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": 1, \"from\": 77, \"to\": 86, \"sentence\": \"Earlier Saturday, Trump praised Senate Republicans for their work in getting Kavanaugh confirmed and said he believes a speech he made earlier this week attacking the credibility of accuser Christine Blasey Ford helped generate support for the embattled nominee.\", \"id\": \"polusa_v1_4233698_-1_27_Kavanaugh_78_87\"}\n{\"mention\": \"Monday\", \"polarity\": 0, \"from\": 92, \"to\": 98, \"sentence\": \"I’m just so happy that I and my family have finally had justice in this case,\\\" Godfrey said Monday.\", \"id\": \"polusa_v1_4234648_-1_10_Monday_92_98\"}\n{\"mention\": \"Paul Ryan\", \"polarity\": 1, \"from\": 1, \"to\": 10, \"sentence\": \"“Paul Ryan is a leader.\", \"id\": \"polusa_v1_4235345_-1_17_House speaker Paul Ryan_1_10\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 18, \"to\": 23, \"sentence\": \"Also on Thursday: Trump attacked McConnell, Clapper and spelling in general, while the Secret Service still struggled to get paid.\", \"id\": \"polusa_v1_4237513_-1_10_pro-Trump_19_24\"}\n{\"mention\": \"Clapper\", \"polarity\": -1, \"from\": 44, \"to\": 51, \"sentence\": \"Also on Thursday: Trump attacked McConnell, Clapper and spelling in general, while the Secret Service still struggled to get paid.\", \"id\": \"polusa_v1_4237513_-1_10_Clapper_45_52\"}\n{\"mention\": \"Tennessee\", \"polarity\": 0, \"from\": 19, \"to\": 28, \"sentence\": \"They cite parts of Tennessee law that suggest Brown could be eligible for release after 51 years behind bars.\", \"id\": \"polusa_v1_4237874_-1_14_Tennessee_19_28\"}\n{\"mention\": \"Mr. NN\", \"polarity\": 1, \"from\": 13, \"to\": 19, \"sentence\": \"For example, Mr. NN, whose identity is also being withheld, won asylum in October after he was forced to flee his native Uganda to the U.S., according to his lawyer, Gregory Asciolla, also of the Labaton Sucharow law firm.\", \"id\": \"polusa_v1_4238452_-1_26_Mr. NN_14_20\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 36, \"to\": 41, \"sentence\": \"Ahead of his United Nations speech, Trump applied one of his patented nicknames to Kim, one that combined a 1972 ballad by Elton John with a dig at the North Korean leader's lack of height: \\\"Little Rocket Man.\\\"\", \"id\": \"polusa_v1_4240114_-1_34_CLOSE President Donald Trump_37_42\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 67, \"to\": 72, \"sentence\": \"(Photo: AP)\\nYet some comments are too offensive to be ignored, and Trump is making it impossible to overlook his racism in all its grim venality.\", \"id\": \"polusa_v1_4240143_-1_24_Donald J. Trump_67_72\"}\n{\"mention\": \"Larson\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Larson identifies himself as a \\\"quasi-neoreactionary libertarian.\\\"\", \"id\": \"polusa_v1_4240331_-1_6_\\\" Larson_0_6\"}\n{\"mention\": \"President Obama\", \"polarity\": 1, \"from\": 0, \"to\": 15, \"sentence\": \"President Obama won Bergdahl’s freedom in 2014 by agreeing to release five Taliban militants from captivity in exchange for the soldier.\", \"id\": \"polusa_v1_4241230_-1_30_President Obama_1_16\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": 0, \"from\": 29, \"to\": 51, \"sentence\": \"The move came in response to President Donald Trump's recent tariffs on imported steel and aluminum.\", \"id\": \"polusa_v1_4242634_-1_2_President Donald Trump_29_51\"}\n{\"mention\": \"Robertson\", \"polarity\": -1, \"from\": 40, \"to\": 49, \"sentence\": \"As the officers began to pat them down, Robertson bolted.\", \"id\": \"polusa_v1_4243451_-1_16_\\\"Robertson_41_50\"}\n{\"mention\": \"Robertson\", \"polarity\": 0, \"from\": 149, \"to\": 158, \"sentence\": \"This undated photo provided by the Chicago Police Department shows LaRoyce Tankson. who was charged with first-degree murder in the shooting of Chad Robertson, outside a Chicago train station feb. 7, 2017.\", \"id\": \"polusa_v1_4243451_-1_2_\\\"Robertson_151_160\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He spoke at a time of rising Israel-Iran tensions.\", \"id\": \"polusa_v1_4243571_-1_6_NATO Secretary General Jens Stoltenberg_1_3\"}\n{\"mention\": \"Bolton\", \"polarity\": -1, \"from\": 1, \"to\": 7, \"sentence\": \"“Bolton should not be called a security adviser who works to secure security, but an adviser for security destruction who destroys peace and security,” the spokesman said.\", \"id\": \"polusa_v1_4243897_-1_15_John Bolton_2_8\"}\n{\"mention\": \"Beshear\", \"polarity\": -1, \"from\": 121, \"to\": 128, \"sentence\": \"She was out of her office Friday and didn't reply to an email, but Staver said litigation would have been unnecessary if Beshear had accommodated Davis’ religious beliefs as Bevin later did.\", \"id\": \"polusa_v1_4247428_-1_34_Beshear_121_128\"}\n{\"mention\": \"Ted Cruz\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Ted Cruz, Beto O'Rourke duke it out in Texas\", \"id\": \"polusa_v1_4247922_-1_0_Cruz_0_8\"}\n{\"mention\": \"Cruz\", \"polarity\": -1, \"from\": 25, \"to\": 29, \"sentence\": \"— Glenda Hart\\nEvery time Cruz gets elected, Texas' reputation as tough and independent takes a hit.\", \"id\": \"polusa_v1_4247922_-1_33_Ted Cruz_26_30\"}\n{\"mention\": \"Tommy Le\", \"polarity\": -1, \"from\": 29, \"to\": 37, \"sentence\": \"Deputies received calls that Tommy Le was threatening residents in a Seattle neighborhood with a sharp object.\", \"id\": \"polusa_v1_4248865_-1_27_Tommy Le_29_37\"}\n{\"mention\": \"Seattle\", \"polarity\": 0, \"from\": 69, \"to\": 76, \"sentence\": \"Deputies received calls that Tommy Le was threatening residents in a Seattle neighborhood with a sharp object.\", \"id\": \"polusa_v1_4248865_-1_27_Seattle_69_76\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 11, \"to\": 14, \"sentence\": \"Evans used her life to show the truth\\n“The folks you’re shutting out of the church today will be leading it tomorrow.\", \"id\": \"polusa_v1_4250435_-1_33_A writer by the church door\\nEvans_12_15\"}\n{\"mention\": \"Evans\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Evans used her life to show the truth\\n“The folks you’re shutting out of the church today will be leading it tomorrow.\", \"id\": \"polusa_v1_4250435_-1_33_Evans_1_6\"}\n{\"mention\": \"Selva\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Selva has specialized in technology and future warfare.\", \"id\": \"polusa_v1_4250817_-1_9_General Paul J. 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\"Turkish president Recep Tayyip Erdoğan\", \"polarity\": 0, \"from\": 119, \"to\": 157, \"sentence\": \"Both Kurz and Strache have railed against some members of the Turkish community in Austria, particularly supporters of Turkish president Recep Tayyip Erdoğan.\", \"id\": \"polusa_v1_4282018_-1_14_Turkish president Recep Tayyip Erdoğan_120_158\"}\n{\"mention\": \"Santos\", \"polarity\": -1, \"from\": 1, \"to\": 7, \"sentence\": \"“Santos is facing local charges for assault and other offenses.\", \"id\": \"polusa_v1_4282255_-1_5_Santos_1_7\"}\n{\"mention\": \"She\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"She added: “I would much rather, from the standpoint of handicapping, be Democrats than Republicans today.\", \"id\": \"polusa_v1_4282661_-1_13_Would-be Speaker Nancy Pelosi_1_4\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 216, \"to\": 221, \"sentence\": \"His comments came after the two outlets on Saturday published an article alleging the Texas migrant 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\"id\": \"polusa_v1_4329134_-1_67_Barr_59_68\"}\n{\"mention\": \"Papadopoulos\", \"polarity\": 0, \"from\": 176, \"to\": 188, \"sentence\": \"The report said that an FBI agent — a “seasoned counterintelligence investigator out of New York” had asked Halper, a trusted FBI informant, to set up a meeting in London with Papadopoulos.\", \"id\": \"polusa_v1_4329583_-1_21_Papadopoulos_177_189\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She should inspire everyone in the medical arena, doctors and patients alike.\", \"id\": \"polusa_v1_4330116_-1_13_McGrath_0_3\"}\n{\"mention\": \"they\", \"polarity\": 0, \"from\": 273, \"to\": 277, \"sentence\": \"“Joe Biden walked in the door tonight with more experience on big debates stages than just about anyone, but delivered an often fumbling performance that will likely be best remembered for his visible anger when Kamala Harris called him out on his history against busing,” they wrote.\", \"id\": \"polusa_v1_4330425_-1_12_Chamberlain and Simpson_274_278\"}\n{\"mention\": \"Elizabeth Warren\", \"polarity\": 1, \"from\": 7, \"to\": 23, \"sentence\": \"“While Elizabeth Warren delivered a dominant performance on Wednesday that will undoubtedly help her build on her growing momentum over the last few weeks, Kamala Harris’ pitch-perfect strong performance tonight will catapult her to a new level in the race,” they wrote.\", \"id\": \"polusa_v1_4330425_-1_5_Elizabeth Warren_8_24\"}\n{\"mention\": \"The iconic comic book publisher\", \"polarity\": 1, \"from\": 0, \"to\": 31, \"sentence\": \"The iconic comic book publisher leveraged its tentpole character to push for “what’s right” with a tweet, sent Wednesday, reminding fans that Superman is a “refugee.”\", \"id\": \"polusa_v1_4330683_-1_3_The iconic comic book publisher_1_32\"}\n{\"mention\": \"This #WorldRefugeeDay\", \"polarity\": 1, \"from\": 0, \"to\": 21, \"sentence\": \"This #WorldRefugeeDay, be like Superman and stand up for what’s right.\", \"id\": \"polusa_v1_4330683_-1_6_This #WorldRefugeeDay_0_21\"}\n{\"mention\": \"Superman\", \"polarity\": 1, \"from\": 31, \"to\": 39, \"sentence\": \"This #WorldRefugeeDay, be like Superman and stand up for what’s right.\", \"id\": \"polusa_v1_4330683_-1_6_DC Comics Tweets Superman_31_39\"}\n{\"mention\": \"Weinstein\", \"polarity\": 0, \"from\": 79, \"to\": 88, \"sentence\": \"The brunette — who often appears dressed as a nun — eventually lures Diamond’s Weinstein into a room, pushes him on the bed, and proceeds to stab him several times.\", \"id\": \"polusa_v1_4330689_-1_5_Harvey Weinstein_79_88\"}\n{\"mention\": \"Sharlet\", \"polarity\": -1, \"from\": 98, \"to\": 105, \"sentence\": \"— Nicholas A. Christakis (@NAChristakis) January 19, 2019\\nAfter the criticism started to pile up, Sharlet doubled down, arguing that the Covington students are worse than the “violent anti-semitic bullies” that he knew as a child.\", \"id\": \"polusa_v1_4330731_-1_17_Dartmouth Professor Jeff Sharlet_98_105\"}\n{\"mention\": \"Wednesday\", \"polarity\": 0, \"from\": 37, \"to\": 46, \"sentence\": \"The U.S. House of Representatives on Wednesday gave victims of illegal alien crimes a bipartisan standing ovation on the floor of the chamber as House Minority Leader Kevin McCarthy read out the names of Americans killed by illegal aliens in a lengthy speech.\", \"id\": \"polusa_v1_4331092_-1_2_Wednesday_39_48\"}\n{\"mention\": \"Dan Crenshaw\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Dan Crenshaw (@RepDanCrenshaw) August 4, 2019\\nRed flag laws exist in California, Florida, Illinois, Maryland, Vermont, and other states where they are designed to flag individuals who are believed to be a danger to themselves or others.\", \"id\": \"polusa_v1_4331484_-1_11_Dan Crenshaw_0_12\"}\n{\"mention\": \"Christie\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Christie shocked the Republican establishment after he endorsed then-candidate Donald Trump for president in February 2016 and joined Trump’s campaign.\", \"id\": \"polusa_v1_4331667_-1_7_Chris Christie (NJ)_1_9\"}\n{\"mention\": \"Martha McSally\", \"polarity\": 0, \"from\": 9, \"to\": 23, \"sentence\": \"Appoints Martha McSally to Replace Jon Kyl in Senate\", \"id\": \"polusa_v1_4331739_-1_1_McSally_9_23\"}\n{\"mention\": \"Jeff Zucker\", \"polarity\": -1, \"from\": 39, \"to\": 50, \"sentence\": \"Fox News’ Sean Hannity Calls for CNN’s Jeff Zucker to be Fired in Wake of Fake News Scandal\", \"id\": \"polusa_v1_4331767_-1_0_Zucker_39_50\"}\n{\"mention\": \"Hannity\", \"polarity\": 0, \"from\": 44, \"to\": 51, \"sentence\": \"— Sean Hannity (@seanhannity) June 27, 2017\\nHannity’s call for Zucker’s firing comes after President Trump’s son, Donald Trump Jr., told Breitbart News that Zucker should address the scandal in an on-camera press briefing.\", \"id\": \"polusa_v1_4331767_-1_17_Hannity_44_51\"}\n{\"mention\": \"Zucker\", \"polarity\": -1, \"from\": 16, \"to\": 22, \"sentence\": \"Hannity accused Zucker of destroying the network with lies and “VERY FAKE NEWS.”\\nadvertisement\\nHey @CNN when will you fire Zucker?\", \"id\": \"polusa_v1_4331767_-1_3_Zucker_17_23\"}\n{\"mention\": \"Zinke\", \"polarity\": 1, \"from\": 19, \"to\": 24, \"sentence\": \"“I thank Secretary Zinke for traveling to Alaska this week, for meeting with stakeholders to understand the unique needs and opportunities of our state, and for moving quickly to ensure we are finally allowed to realize more of our tremendous resource potential.”\", \"id\": \"polusa_v1_4332413_-1_24_Zinke_19_24\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He added that Corker decided not to run for re-election after Trump refused to endorse him and had since become opposed to his proposals:\\nBob Corker, who helped President O give us the bad Iran Deal & couldn't get elected dog catcher in Tennessee, is now fighting Tax Cuts….\", \"id\": \"polusa_v1_4332441_-1_8_Marco Rubio_1_3\"}\n{\"mention\": \"Lee Greenwood\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"Lee Greenwood Performs 'God Bless the USA' at Inauguration Show\", \"id\": \"polusa_v1_4332496_-1_0_Lee Greenwood_0_13\"}\n{\"mention\": \"the elder Le Pen\", \"polarity\": 1, \"from\": 112, \"to\": 128, \"sentence\": \"Last November a French court upheld the FN’s decision to strip him of his membership but in a small victory for the elder Le Pen it ruled he should be allowed to remain as the party’s honorary president.\", \"id\": \"polusa_v1_4332656_-1_12_the elder Le Pen_113_129\"}\n{\"mention\": \"Cohen\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Cohen pled guilty to arranging deals for Playboy model Karen McDougal and porn star Stormy Daniels to silence their claims that they had an affair with Trump before he was president.\", \"id\": \"polusa_v1_4332672_-1_4_private lawyer Michael Cohen_0_6\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 23, \"to\": 28, \"sentence\": \"‘We Will Win’ - Donald Trump Vows to Fight Opioid Crisis\", \"id\": \"polusa_v1_4333086_-1_0_President Donald Trump_23_28\"}\n{\"mention\": \"Steve Bannon\", \"polarity\": 0, \"from\": 42, \"to\": 54, \"sentence\": \"President Donald Trump's senior counselor Steve Bannon has displayed a whiteboard in his West Wing office of all the promises that he made.\", \"id\": \"polusa_v1_4333131_-1_1_Steve Bannon_44_56\"}\n{\"mention\": \"CNN\", \"polarity\": -1, \"from\": 46, \"to\": 49, \"sentence\": \"From there, Roseanne then directed her ire at CNN, calling Daniels the cable news network’s “big star attraction.”\\nright? cnn's big star attraction — Roseanne Barr (@therealroseanne) May 3, 2018\\nDaniels, the porn actress who alleges that she had an affair with Trump, is suing the president to release her from an NDA she signed in October of 2016.\", \"id\": \"polusa_v1_4333151_-1_10_CNN_46_49\"}\n{\"mention\": \"[Sen.] Mitch McConnell\", \"polarity\": 1, \"from\": 80, \"to\": 102, \"sentence\": \"“We’re going to get a lot of Senators and a lot of Congressmen elected, a lot … [Sen.] Mitch McConnell is here, he’s smiling so big, he loves those words.”\", \"id\": \"polusa_v1_4333499_-1_17_[Sen.] Mitch McConnell_80_102\"}\n{\"mention\": \"We\", \"polarity\": 1, \"from\": 1, \"to\": 3, \"sentence\": \"“We’re going to get a lot of Senators and a lot of Congressmen elected, a lot … [Sen.] Mitch McConnell is here, he’s smiling so big, he loves those words.”\", \"id\": \"polusa_v1_4333499_-1_17_OUR_1_3\"}\n{\"mention\": \"Cunningham\", \"polarity\": 0, \"from\": 65, \"to\": 75, \"sentence\": \"In an email with the subject line “Chris Steele,” Winer wrote to Cunningham:\\nHe was in my office catching up and it occurred to me there might be value for McClarty Global knowing him and his capabilities in terms of real time and longer term analysis of developments in that part of the world.\", \"id\": \"polusa_v1_4333622_-1_61_Cunningham_66_76\"}\n{\"mention\": \"California\", \"polarity\": 0, \"from\": 17, \"to\": 27, \"sentence\": \"Jerry Brown, and California Attorney General Xavier Becerra – the elected official who, perhaps more than any other, has made protection of criminal illegal aliens and “resistance” to President Donald Trump’s immigration agenda his signature policy.\", \"id\": \"polusa_v1_4333751_-1_11_California_17_27\"}\n{\"mention\": \"NBC\", \"polarity\": 0, \"from\": 95, \"to\": 98, \"sentence\": \"Kelly is set to headline both a Sunday show and a morning news show when she begins working at NBC next month, though the morning show is not expected to premiere until later this fall.\", \"id\": \"polusa_v1_4333948_-1_6_NBC_96_99\"}\n{\"mention\": \"Somerville\", \"polarity\": -1, \"from\": 29, \"to\": 39, \"sentence\": \"Unable to mount an argument, Somerville instead descends to insults and baseless slurs, calling Bannon an “anti-Semitic Catholic” who only collaborates with Jews in order to achieve the greater good of defeating Islam.\", \"id\": \"polusa_v1_4334816_-1_20_Huffington Post writer Michele Somerville_30_40\"}\n{\"mention\": \"The Deep State\", \"polarity\": -1, \"from\": 8, \"to\": 22, \"sentence\": \"Virgil: The Deep State Strikes Back: The Permanent Campaign Against Donald Trump\", \"id\": \"polusa_v1_4334893_-1_0_The Deep State_8_22\"}\n{\"mention\": \"it\", \"polarity\": 1, \"from\": 194, \"to\": 196, \"sentence\": \"Thus Trump rallied his support; on January 12, Politico Playbook, an e-mail tipsheet for DC insiders and wannabe insiders, had to grudgingly admit, “For most people who watched Trump yesterday, it was a pretty good performance.”\", \"id\": \"polusa_v1_4334893_-1_107_it_195_197\"}\n{\"mention\": \"Shaub\", \"polarity\": -1, \"from\": 34, \"to\": 39, \"sentence\": \"Yes, he’s a federal employee, but Shaub has turned his supposedly non-partisan office into a partisan machine, advancing his anti-Trump campaign including, even, on Twitter.\", \"id\": \"polusa_v1_4334893_-1_60_Shaub_34_39\"}\n{\"mention\": \"Harris\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Harris did not give an indication on Thursday whether he would run for the Republican nomination in the special election ordered by the NCSBE.\", \"id\": \"polusa_v1_4335775_-1_17_Harris_1_7\"}\n{\"mention\": \"ICE\", \"polarity\": 0, \"from\": 82, \"to\": 85, \"sentence\": \"In a February 2018 immigration debate, Donnelly voted for an amendment which told ICE to not deport migrants who had arrived in the United States before June 30, 2018.\", \"id\": \"polusa_v1_4336150_-1_10_ICE'_83_86\"}\n{\"mention\": \"her\", \"polarity\": -1, \"from\": 7, \"to\": 10, \"sentence\": \"I gave her every break, despite the fact that she was despised by everyone, and she went for some cheap money from a book.\", \"id\": \"polusa_v1_4336439_-1_13_Westerhout_7_10\"}\n{\"mention\": \"Madeleine Westerhout\", \"polarity\": 1, \"from\": 7, \"to\": 27, \"sentence\": \"“While Madeleine Westerhout has a fully enforceable confidentiality agreement, she is a very good person and I don’t think there would ever be reason to use it,” Trump wrote Saturday morning.\", \"id\": \"polusa_v1_4336439_-1_4_Westerhout_8_28\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 73, \"to\": 88, \"sentence\": \"The inquiry forced counterintelligence investigators to evaluate whether President Trump was a potential threat to national security, and they also sought to determine whether the president was deliberately working for Russia or had unintentionally been influenced by Moscow.\", \"id\": \"polusa_v1_4336504_-1_9_President Trump_74_89\"}\n{\"mention\": \"Russia\", \"polarity\": -1, \"from\": 219, \"to\": 225, \"sentence\": \"The inquiry forced counterintelligence investigators to evaluate whether President Trump was a potential threat to national security, and they also sought to determine whether the president was deliberately working for Russia or had unintentionally been influenced by Moscow.\", \"id\": \"polusa_v1_4336504_-1_9_Russia_220_226\"}\n{\"mention\": \"California\", \"polarity\": 0, \"from\": 167, \"to\": 177, \"sentence\": \"Apparently the governor is proposing to put taxpayer money where his mouth is, following up on his bold statement last January in his State of the State speech to the California legislature: “Let me be clear: We will defend everybody — every man, woman and child — who has come here for a better life and has contributed to the well-being of our state.”\", \"id\": \"polusa_v1_4336533_-1_4_California_168_178\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 24, \"to\": 29, \"sentence\": \"Governor Abbott thanked Trump and his administration for their assistance.\", \"id\": \"polusa_v1_4336786_-1_12_Donald Trump in Texas: Hurricane Harvey a Storm of ‘Epic Proportion’_25_30\"}\n{\"mention\": \"Sarah Jeong\", \"polarity\": -1, \"from\": 8, \"to\": 19, \"sentence\": \"Today: “Sarah Jeong is a racist for trolling her harassers because Twitter never did shit to protect her.”\", \"id\": \"polusa_v1_4336900_-1_12_Sarah Jeong —_8_19\"}\n{\"mention\": \"the wall\", \"polarity\": 1, \"from\": 127, \"to\": 135, \"sentence\": \"The astonishing number of contributions that this project has received from ordinary Americans demonstrates just how important the wall is to the American people.\", \"id\": \"polusa_v1_4337162_-1_13_Border Wall_128_136\"}\n{\"mention\": \"Americans\", \"polarity\": 1, \"from\": 85, \"to\": 94, \"sentence\": \"The astonishing number of contributions that this project has received from ordinary Americans demonstrates just how important the wall is to the American people.\", \"id\": \"polusa_v1_4337162_-1_13_Americans_86_95\"}\n{\"mention\": \"Walsh\", \"polarity\": 1, \"from\": 170, \"to\": 175, \"sentence\": \"Alongside other strong women on President Donald J. Trump’s team, like director of strategic communications, Hope Hicks, or counselor to the president, KellyAnne Conway, Walsh is instrumental in making the White House function.\", \"id\": \"polusa_v1_4337825_-1_3_Walsh_170_175\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump also emphasized the importance of the repatriation of remains of soldiers missing in action in the Korean War, which would start “immediately.”\", \"id\": \"polusa_v1_4337870_-1_15_President Donald Trump_0_6\"}\n{\"mention\": \"Coleman\", \"polarity\": 1, \"from\": 37, \"to\": 44, \"sentence\": \"On Thursday, the DCCC announced that Coleman, who is described as a “DCCC veteran,” will lead an engagement effort as “the DCCC’s first-ever Director of the Cycle of Engagement.”\", \"id\": \"polusa_v1_4338042_-1_4_Coleman_38_45\"}\n{\"mention\": \"Joni Ernst\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Joni Ernst jumped into the political fray Monday evening, confirming her belief that Trump's tweets were racist in nature.\", \"id\": \"polusa_v1_4338044_-1_3_Joni Ernst_0_10\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 87, \"to\": 92, \"sentence\": \"She reiterated that view when asked on another occasion by a CNN reporter if she found Trump’s comments racist.\", \"id\": \"polusa_v1_4338044_-1_8_— Donald J. Trump (@realDonaldTrump)_87_92\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 33, \"to\": 36, \"sentence\": \"“We wish we had of gotten rid of him sooner.\", \"id\": \"polusa_v1_4338057_-1_12_Landon_34_37\"}\n{\"mention\": \"West\", \"polarity\": 1, \"from\": 435, \"to\": 439, \"sentence\": \"Constantly bringing up the past keeps you stuck there — KANYE WEST (@kanyewest) April 22, 2018\\nwe have freedom of speech but not freedom of thought — KANYE WEST (@kanyewest) April 22, 2018\\nThe thought police want to suppress freedom of thought — KANYE WEST (@kanyewest) April 22, 2018\\nself victimization is a disease — KANYE WEST (@kanyewest) April 22, 2018\\nI love the way Candace Owens thinks — KANYE WEST (@kanyewest) April 21, 2018\\nWest’s commentary on freedom of thought received 100,000 likes, while his endorsement of Owens received over 80,000.\", \"id\": \"polusa_v1_4338345_-1_10_Kanye West_436_440\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 26, \"to\": 31, \"sentence\": \"Netanyahu will likely ask Trump to inaugurate the embassy at its new location in Arnona, Jerusalem, Channel 2 news reported on Saturday night.\", \"id\": \"polusa_v1_4338440_-1_12_President Donald Trump_27_32\"}\n{\"mention\": \"Swetnick\", \"polarity\": -1, \"from\": 56, \"to\": 64, \"sentence\": \"“Based on its investigations, WebTrends determined that Swetnick had engaged in inappropriate conduct, but that no corroborating evidence existed to support Swetnick’s allegations against her coworkers,” the complaint said.\", \"id\": \"polusa_v1_4338939_-1_15_Julie Swetnick_56_64\"}\n{\"mention\": \"Warren\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Warren also spoke about “racial justice” and her proposition to build three million housing units across the country.\", \"id\": \"polusa_v1_4338989_-1_16_Elizabeth Warren (D-MA)_1_7\"}\n{\"mention\": \"MILO\", \"polarity\": 1, \"from\": 40, \"to\": 44, \"sentence\": \"The office of Chancellor Dirks defended MILO’s right to speak in their response to the professors, citing the United States Constitution as the reason why the college cannot ban MILO from appearing based on his political views.\", \"id\": \"polusa_v1_4339011_-1_13_Breitbart Senior Editor MILO_41_45\"}\n{\"mention\": \"Judith Butler\", \"polarity\": 0, \"from\": 211, \"to\": 224, \"sentence\": \"The following professors signed the letter in an attempt to stifle MILO’s right to speak:\\nElizabeth Abel, Professor, Department of English Wendy Brown, Class of 1936 First Chair, Department of Political Science Judith Butler, Maxine Elliot Professor, Department of Comparative Literature Ian Duncan, Professor, Department of English Donna Jones, Associate Professor, Department of English David Landreth, Associate Professor, Department of English Saba Mahmood, Professor, Department of Anthropology Linda Rugg, Professor, Department of Scandinavian and Associate Dean of Arts and Humanities Elena Schneider, Assistant Professor, Department of History Susan Schweik, Professor, Department of English Estelle Tarica, Associate Professor, Department of Spanish and Portuguese Katrin Wehrheim, Associate Professor, Department of Mathematics Damon Young, Assistant Professor, Departments of French and Film and Media Studies Gregory Levine, Associate Professor, Department of History of Art Lauren Williams, Professor, Department of Mathematics Jon Wilkening, Associate Professor, Vice Chair for Graduate Affairs, Mathematics Janet Sorensen, Associate Professor, English Leslie Salzinger, Associate Professor, Gender and Women’s Studies Khalid Kadir, Lecturer, International and Area Studies Tamara Roberts, Associate Professor, Music Clélia Donovan, Lecturer, Spanish and Portuguese Elisa Tamarkin, Associate Professor, English Julia Bryan-Wilson, Associate Professor, Modern and Contemporary Art Jeffrey Skoller, Associate Professor, Film & Media Déborah Blocker, Associate Professor, French, with an affiliation in Italian Studies Rachel Morello-Frosch, Professor, Department of Environmental Science, Policy and Management & School of Public health Katherine Snyder, Associate Professor, English Mark Goble, Associate Professor, English Alberto Grunbaum, Professor, Department of Mathematics Dan O’Neill, Associate Professor, East Asian Languages and Cultures Soraya Tlatli, Associate Professor, Department of French Barbara A. Barnes, Lecturer, Department of Gender and Women’s Studies Colleen Lye, Associate Professor, English Charles Hirschkind, Associate Professor, Anthropology Saba Mahmood, Professor, Anthropology Ivonne del Valle, Associate Professor, Spanish and Portuguese Daniel G. Chatman, Associate Professor, City and Regional Planning Patricia Penn Hilden, Professor, Department of Ethnic Studies Katherine Sherwood, Professor Emerita, Department of Art Practice Charis Thompson, Professor, Department of Gender and Women’s Studies Ayse Agis, Continuing Lecturer, Gender and Women’s Studies Minoo Moallem, Gender and Women’s Studies Lawrence Cohen, Sarah Kailath Professor of India Studies, Department of Anthropology Emiliano Gomez, Lecturer and Academic Coordinator, Department of Mathematics Paola Bacchetta, Associate Professor, Gender and Women’s Studies Ian Agol, Professor, Department of Mathematics Joanna Picciotto, Associate Professor, English Laura C. Nelson, Associate Professor, Gender & Women’s Studies Cori Hayden, Associate Professor, Anthropology Hung-Hsi Wu, Emeritus Professor of Mathematics Geoffrey G. O’Brien, Associate Professor, English Scott Saul, Professor, English Kevis Goodman, Associate Professor, English Mary Ann Smart, Gladyce Arata Terrill Professor, Music Katherine Snyder, Associate Professor, English Stephen A. Rosenbaum, John & Elizabeth Boalt Lecturer, School of Law Jake Kosek, Associate Professor, Geography Victoria Robinson, Ethnic Studies Celeste Langan, Associate Professor, English Hertha D. Sweet Wong, Associate Professor and Vice-Chair, Department of English Alastair Iles, Associate Professor of Environmental Policy and Societal Change Anne-Lise François, Associate Professor, English and Comparative Literature Davitt Moroney, Professor, Music; University Organist\\nJean-Paul Bourdier, Professor, Architecture Department Natalia Brizuela, Associate Professor, Spanish & Portuguese Line Mikkelsen, Associate Professor, Linguistics Darcy Grimaldo Grigsby, Professor, History of Art Shannon Steen, Associate Professor, Theater, Dance, and Performance Studies Morris W. Hirsch, Professor Emeritus, Mathematics Jenny Harrison Professor, Mathematics James Vernon, Professor, History Debarati Sanyal, Professor, French Christine Rosen, Associate Professor, Haas School of Business Waldo E. Martin, Jr., Morrison Professor of American History and Citizenship Robin Einhorn, Preston Hotchkis Professor in the History of the United States Kristin Hanson, Associate Professor, English Patricia Baquedano-Lopez, Associate Professor of Education Joseph Wolf, Professor Emeritus, Mathematics You-tien Hsing, Professor, Geography Glynda Hull, Professor, Education Richard B. Norgaard, Professor Emeritus of Energy and Resources Ellen L. Simms, Professor of Integrative Biology Katherine Snyder, Associate Professor, Department of English Kathleen Donegan, Associate Professor, Department of English and Associate Dean of Arts and Humanities Trinh T. Minh-ha, Professor of Rhetoric and of Gender & Women’s Studies Suzanne Guerlac, Professor, Department of French Mel Y. Chen, Associate Professor, Department of Gender and Women’s Studies Margaret W. Conkey, Department of Anthropology Darcy Grimaldo Grigsby, Professor, History of Art Mariane C Ferme, Professor, Department of Anthropology Lyn Hejinian, John F Hotchkis Professor of English Michael Watts, Professor Emeritus, Geography Antonio Montalban, Associate Professor, Mathematics Samera Esmeir, Associate Professor, Rhetoric Louise Fortmann, Professor Emerita, Dept of Environmental Science, Policy and Management Joseph Lavery, Assistant Professor, Dept. of English Lynn Huntsinger, Professor, Dept Environmental Science, Policy, and Management Ramona Naddaff, Associate Professor, Rhetoric Daniel Boyarin, Taubman Professor of Talmudic Culture, Near Eastern Studies and Rhetoric Gillian Hart, Professor Emerita, Geography Charles C. Pugh, Professor Emeritus, Mathematics Miryam Sas, Professor and Chair, Comparative Literature: Professor of Film & Media Mark Anderson, Professor of Architecture Darieck Scott, Associate Professor, African American Studies Dept Juana María Rodríguez, Professor, Gender and Women’s Studies Nadia Ellis, Associate Professor, English\\nCharlie Nash is a reporter for Breitbart Tech.\", \"id\": \"polusa_v1_4339011_-1_44_Judith Butler_212_225\"}\n{\"mention\": \"former convict Ray Hinton\", \"polarity\": 1, \"from\": 26, \"to\": 51, \"sentence\": \"Jones in 2015 represented former convict Ray Hinton in a successful bid that saw him freed after nearly 30 years on death row when new ballistics tests raised questions about the evidence used to convict him.\", \"id\": \"polusa_v1_4339347_-1_46_former convict Ray Hinton_26_51\"}\n{\"mention\": \"Jim Acosta\", \"polarity\": -1, \"from\": 40, \"to\": 50, \"sentence\": \"Like the hate network that employs him, Jim Acosta is a national joke and failure propped up by 89 million suckers who subsidize fake news through their cable bills.\", \"id\": \"polusa_v1_4339498_-1_18_Jim Acosta_41_51\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 35, \"to\": 38, \"sentence\": \"Like the hate network that employs him, Jim Acosta is a national joke and failure propped up by 89 million suckers who subsidize fake news through their cable bills.\", \"id\": \"polusa_v1_4339498_-1_18_’m_36_39\"}\n{\"mention\": \"Acosta\", \"polarity\": -1, \"from\": 145, \"to\": 151, \"sentence\": \"Let me offer up a little context…\\nMark Levin’s Unfreedom of the Press, a book critical of fake news, a book that serves as the exact opposite of Acosta’s little screed, currently sits at #3 on Amazon’s Top 100, and Levin’s book was released a month ago.\\nAcosta is also losing to Cozy White Cottage: 100 Ways to Love the Feeling of Being Home (#11).\", \"id\": \"polusa_v1_4339498_-1_8_Jim Acosta_146_152\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Hillary Clinton campaign spokesman Brian Fallon and communications director Nick Merrill attacked Weinstein accuser Asia Argento's boyfriend.\", \"id\": \"polusa_v1_4339560_-1_1_Hillary Clinton_2_17\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 75, \"to\": 80, \"sentence\": \"Brennan repeatedly criticized Republicans for failing to speak out against Trump’s decisions that he felt were endangering the country.\", \"id\": \"polusa_v1_4339843_-1_12_President Trump_76_81\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He was named one of the “most influential” people in news media in 2016.\", \"id\": \"polusa_v1_4340147_-1_13_Joel B. Pollak_0_2\"}\n{\"mention\": \"Estala\", \"polarity\": -1, \"from\": 35, \"to\": 41, \"sentence\": \"The neighbor also told police that Estala put his mouth over a fence post and stuck his tongue in and out through a hole in the fence.\", \"id\": \"polusa_v1_4340180_-1_6_Estala_36_42\"}\n{\"mention\": \"NBC News\", \"polarity\": 0, \"from\": 10, \"to\": 18, \"sentence\": \"But in an NBC News analysis on what Biden is weighing ahead of what would be his last shot at residing at 1600 Pennsylvania Avenue reveals the very things that have made him endearing to many Americans could keep him out of the 2020 race.\", \"id\": \"polusa_v1_4340306_-1_3_NBC News_11_19\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 4, \"to\": 6, \"sentence\": \"But he’s also a grandfather and a father trying to keep his family together.\", \"id\": \"polusa_v1_4340306_-1_9_Former Vice President Joe Biden_4_6\"}\n{\"mention\": \"Reid Hoffman\", \"polarity\": 1, \"from\": 43, \"to\": 55, \"sentence\": \"LinkedIn co-founder and venture capitalist Reid Hoffman is joining forces with a group of Obama administration officials to launch an initiative aimed at storing “all of the progressive community’s voter data,” according to a report released Monday.\", \"id\": \"polusa_v1_4340364_-1_2_Reid Hoffman_45_57\"}\n{\"mention\": \"Judge Kavanaugh\", \"polarity\": -1, \"from\": 18, \"to\": 33, \"sentence\": \"“When it comes to Judge Kavanaugh, there’s not an ounce of fairness left in Senate Democrats.\", \"id\": \"polusa_v1_4340530_-1_5_Judge Kavanaugh_19_34\"}\n{\"mention\": \"Kerrey\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Kerrey moved on to academia and now to an investment bank, but hasn’t lost the willingness to break ranks with his party.\", \"id\": \"polusa_v1_4340540_-1_4_Kerrey_0_7\"}\n{\"mention\": \"Matt Rivitz's\", \"polarity\": -1, \"from\": 75, \"to\": 88, \"sentence\": \"Far left website Salon credited Jared Holt of Right Wing Watch, along with Matt Rivitz's anti-conservative harassment campaign Sleeping Giants, for catalyzing the purge of Alex Jones and Infowars from major tech platforms earlier this week.\", \"id\": \"polusa_v1_4341391_-1_1_Matt Rivitz's_77_90\"}\n{\"mention\": \"Haley\", \"polarity\": 0, \"from\": 153, \"to\": 158, \"sentence\": \"“When the Human Rights Council treats Israel worse than North Korea, Iran and Syria, it is the council itself that is foolish and unworthy of its name,” Haley continued.\", \"id\": \"polusa_v1_4341747_-1_6_UN Envoy Nikki Haley_154_159\"}\n{\"mention\": \"Kimmel\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Kimmel has still not apologized for engaging in the only kind of bigotry still accepted by our self-appointed elites — identity-based attacks on Republicans, including Republican immigrants.\", \"id\": \"polusa_v1_4342132_-1_19_Jimmy Kimmel_1_7\"}\n{\"mention\": \"Snoop\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Snoop has never been a fan of Trump.\", \"id\": \"polusa_v1_4342345_-1_14_Snoop_1_6\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 30, \"to\": 35, \"sentence\": \"Snoop has never been a fan of Trump.\", \"id\": \"polusa_v1_4342345_-1_14_Donald Trump's_31_36\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Donald Trump Does Not Want to Watch Ryan Gosling Moon Landing Movie 'First Man'\", \"id\": \"polusa_v1_4342440_-1_0_Donald Trump_0_12\"}\n{\"mention\": \"Pelosi\", \"polarity\": 0, \"from\": 72, \"to\": 78, \"sentence\": \"Adriano Espaillat (D-NY), one of the lawmakers who signed the letter to Pelosi, told CBS News that Democrats should move “expeditiously” in January to pass legislation to shield illegal immigrants and TPS refugees from deportation, without funding a wall on America’s southern border.\", \"id\": \"polusa_v1_4342748_-1_13_Nancy Pelosi_72_78\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 134, \"to\": 137, \"sentence\": \"Standing just 155 centimetres (five foot, one inch) tall and weighing 43 kilograms (six stone, 10 pounds), her speed and agility make her a match for almost any opponent.\", \"id\": \"polusa_v1_4342847_-1_4_Diana_135_138\"}\n{\"mention\": \"Harvey Weinstein\", \"polarity\": -1, \"from\": 72, \"to\": 88, \"sentence\": \"Hillary Clinton reacted to the abuse scandal embroiling Hollywood mogul Harvey Weinstein by saying the American people elected someone guilty of sexual assault to the presidency.\", \"id\": \"polusa_v1_4342962_-1_4_Harvey Weinstein_74_90\"}\n{\"mention\": \"Seattle Mayor Ed Murray\", \"polarity\": 0, \"from\": 0, \"to\": 23, \"sentence\": \"Seattle Mayor Ed Murray responded to Trump’s immigration enforcement orders calling it the “worst days for immigrants in America since Japanese Internment.”\", \"id\": \"polusa_v1_4343071_-1_1_Seattle Mayor Ed Murray_0_25\"}\n{\"mention\": \"David Cameron\", \"polarity\": -1, \"from\": 36, \"to\": 49, \"sentence\": \"Though I’ve never had much time for David Cameron — at least not since our dope-smoking days at uni — I sat through this documentary feeling almost sorry for him.\", \"id\": \"polusa_v1_4343713_-1_16_David Cameron_37_50\"}\n{\"mention\": \"this documentary\", \"polarity\": 0, \"from\": 116, \"to\": 132, \"sentence\": \"Though I’ve never had much time for David Cameron — at least not since our dope-smoking days at uni — I sat through this documentary feeling almost sorry for him.\", \"id\": \"polusa_v1_4343713_-1_16_the BBC’s documentary Inside Europe_117_133\"}\n{\"mention\": \"Gerald Hebert\", \"polarity\": -1, \"from\": 17, \"to\": 30, \"sentence\": \"This is the same Gerald Hebert who made similar racially charged accusations against Jeff Sessions when he was nominated to be a federal district court judge, just like Tom Farr.\", \"id\": \"polusa_v1_4343810_-1_47_Gerald Hebert_18_31\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 40, \"to\": 43, \"sentence\": \"Shocking statements flow like wine from him.\", \"id\": \"polusa_v1_4343877_-1_13_Billy Bush_40_43\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 30, \"to\": 32, \"sentence\": \"“I felt that, in that moment, he was being typically Donald, which is performing and shocking,” he added.\", \"id\": \"polusa_v1_4343877_-1_15_Billy Bush_31_33\"}\n{\"mention\": \"Donald\", \"polarity\": -1, \"from\": 53, \"to\": 59, \"sentence\": \"“I felt that, in that moment, he was being typically Donald, which is performing and shocking,” he added.\", \"id\": \"polusa_v1_4343877_-1_15_Donald_54_60\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 115, \"to\": 127, \"sentence\": \"SIGN UP FOR OUR NEWSLETTER\\nFormer Today host Billy Bush has broken his silence seven months after the now-infamous Donald Trump “Access Hollywood tape” cost him his job, explaining in a tell-all interview that watching the tape left him “totally and completely gutted” but that he had ultimately become a “better man” as a result.\", \"id\": \"polusa_v1_4343877_-1_2_Donald Trump_117_129\"}\n{\"mention\": \"McSally\", \"polarity\": 1, \"from\": 64, \"to\": 71, \"sentence\": \"McSally garnered 48 percent support to Sinema’s 46, a surge for McSally from a prior poll, but still a statistical tie with a four percent margin of error.\", \"id\": \"polusa_v1_4344411_-1_3_Martha McSally_65_72\"}\n{\"mention\": \"them\", \"polarity\": 1, \"from\": 409, \"to\": 413, \"sentence\": \"Some members of the press were allowed into the building to witness the surprise, and Trump assistant Cliff Sims filmed a video of the president emerging from behind a series of panels:\\nSIGN UP FOR OUR NEWSLETTER\\nYou never know what surprises may await you on a @WhiteHouse tour! pic.twitter.com/VNLpoXRZs4 — Cliff Sims (@CSims45) March 7, 2017\\nSome in the crowd screamed with delight as President Trump gave them his signature “thumbs up” salute.\", \"id\": \"polusa_v1_4344525_-1_3_Some in the crowd_410_414\"}\n{\"mention\": \"Fischer\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Fischer went on, “My outlet is not left-wing or right-wing.\", \"id\": \"polusa_v1_4345303_-1_17_Ford Fischer_0_8\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 42, \"to\": 47, \"sentence\": \"Clinton added on Monday that she believes Trump attacked The Squad because the lawmakers “brought attention to the inhumane conditions they saw at this administration’s detention camps.”\", \"id\": \"polusa_v1_4345456_-1_13_Trump_43_48\"}\n{\"mention\": \"Epstein\", \"polarity\": 0, \"from\": 31, \"to\": 38, \"sentence\": \"Pastrana explained that he met Epstein in Ireland during the International Achievement Summit of 2002 in Dublin.\", \"id\": \"polusa_v1_4345778_-1_8_Epstein_32_39\"}\n{\"mention\": \"Li\", \"polarity\": 0, \"from\": 50, \"to\": 52, \"sentence\": \"The CUPP blasted the decision as “absurd” because Li had not delivered the offending speech yet and was merely advertised on a poster.\", \"id\": 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\"sentence\": \"A memorial fund was set up for Dixon’s family shortly after his death.\", \"id\": \"polusa_v1_4346586_-1_12_Dixon_31_36\"}\n{\"mention\": \"Farrakhan\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Farrakhan is also on record praising Adolf Hitler saying: “The Jews don’t like Farrakhan, so they call me Hitler.\", \"id\": \"polusa_v1_4347406_-1_12_Louis Farrakhan_0_9\"}\n{\"mention\": \"Adolf Hitler\", \"polarity\": -1, \"from\": 37, \"to\": 49, \"sentence\": \"Farrakhan is also on record praising Adolf Hitler saying: “The Jews don’t like Farrakhan, so they call me Hitler.\", \"id\": \"polusa_v1_4347406_-1_12_Adolf Hitler_37_49\"}\n{\"mention\": \"Sarsour\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Sarsour wrote:\\nKind, compassionate, humble, active listener — that’s Roger Waters.\", \"id\": \"polusa_v1_4347620_-1_3_Women's March leader Linda Sarsour_0_8\"}\n{\"mention\": \"Morrisey\", \"polarity\": 0, \"from\": 43, \"to\": 51, \"sentence\": 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Teddy’s fumbling has already defeated.\", \"id\": \"polusa_v1_4347896_-1_47_Teddy_184_189\"}\n{\"mention\": \"Dartmouth\", \"polarity\": -1, \"from\": 36, \"to\": 45, \"sentence\": \"Seven women filed a lawsuit against Dartmouth College in New Hampshire on Thursday for allowing professors William Kelley, Paul Whalen, and Todd Heatherton to allegedly harass female students.\", \"id\": \"polusa_v1_4348049_-1_3_Dartmouth_37_46\"}\n{\"mention\": \"Paul Whalen\", \"polarity\": -1, \"from\": 123, \"to\": 134, \"sentence\": \"Seven women filed a lawsuit against Dartmouth College in New Hampshire on Thursday for allowing professors William Kelley, Paul Whalen, and Todd Heatherton to allegedly harass female students.\", \"id\": \"polusa_v1_4348049_-1_3_Paul Whalen_124_135\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 65, \"to\": 72, \"sentence\": \"Streisand spent much of the presidential campaign working to get Clinton elected and bashing then-Republican candidate Donald Trump.\", \"id\": \"polusa_v1_4348263_-1_7_Hillary Clinton's_66_73\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Mueller said last week that the report he created for the Department of Justice, which shows that Trump or his campaign did not collude with the Russian government “speaks for itself.”\", \"id\": \"polusa_v1_4348360_-1_8_Robert Mueller_0_8\"}\n{\"mention\": \"Jones\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Jones, for his part, has already denounced the interview as “fake news” and said it was purposeful hit job on him.\", \"id\": \"polusa_v1_4348649_-1_33_Jones_1_6\"}\n{\"mention\": \"CNN\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"CNN and Andrew Kaczynski gave a misleading defense after printing that CNN may reveal a meme maker's identity if the man engages in \\\"ugly behavior.\\\"\", \"id\": \"polusa_v1_4348739_-1_1_CNN_2_5\"}\n{\"mention\": \"Ahmed\", \"polarity\": 0, \"from\": 246, \"to\": 251, \"sentence\": \"No, this absurd propaganda is by one of the Times’ resident shills for Islam, Atossa Araxia Abrahmian, coming in form of a review of Journey Into Europe: Islam, Immigration, and Identity, the latest installment in Islamic studies professor Akbar Ahmed’s series on Muslims around the world.\", \"id\": \"polusa_v1_4348858_-1_8_Ahmed_246_251\"}\n{\"mention\": \"Bajrang Dal\", \"polarity\": -1, \"from\": 30, \"to\": 41, \"sentence\": \"India’s Daily O addressed the Bajrang Dal problem in an editorial dripping with sarcasm, beginning with the observation that lonely singles have the consolation of knowing they won’t be thrashed by a gang of “sexually-frustrated, culture-spewing, self-righteous scumbags” on Valentine’s Day:\\nThese hate-loving detectives travel in packs with hockey sticks and lead pipes.\", \"id\": \"polusa_v1_4348896_-1_7_Bajrang Dal_31_42\"}\n{\"mention\": \"Jones\", \"polarity\": 1, \"from\": 28, \"to\": 33, \"sentence\": \"Brennan’s letter, signed by 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\"polusa_v1_4350197_-1_13_Salvini_1_8\"}\n{\"mention\": \"Blair\", \"polarity\": -1, \"from\": 35, \"to\": 40, \"sentence\": \"Instead of standing for something, Blair ran on the “Cool Britannia” mantra, eschewing substance for style, diverting from debate and embracing governance by charisma.\", \"id\": \"polusa_v1_4351516_-1_48_Prime Minister Tony Blair_35_40\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 290, \"to\": 293, \"sentence\": \"A report by think tank Quilliam has found that more than eight out of ten men convicted of grooming gang offences have an 'Asian' background, while victims are \\\"almost exclusively white girls\\\". https://t.co/9llGk0zVRS — Jack Montgomery ن (@JackBMontgomery) December 10, 2017\\nThe woman said she hoped Aslam would “go to prison for a long time” — but Sheriff John Rafferty handed him a sentence only one year long.\", \"id\": \"polusa_v1_4351562_-1_11_Shopkeeper Rana Aslam_291_294\"}\n{\"mention\": \"The president\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"The president pointed to the positive economic climate, citing low unemployment and an increase in jobs since the election, as signs that his administration is helping Americans achieve that sought-after American dream.\", \"id\": \"polusa_v1_4351695_-1_12_President Trump_0_13\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He is a founding member of the Breitbart Texas team.\", \"id\": \"polusa_v1_4351696_-1_41_Maryland’s Republican Governor Larry Hogan_0_2\"}\n{\"mention\": \"Israel\", \"polarity\": 0, \"from\": 158, \"to\": 164, \"sentence\": \"In fact, Omar’s bigotry just earned her a spot on the cover page of Newsweek magazine, which praises the rookie lawmaker for “changing the conversation about Israel.”\", \"id\": \"polusa_v1_4352193_-1_37_Israel_159_165\"}\n{\"mention\": \"Omar\", \"polarity\": -1, \"from\": 9, \"to\": 13, \"sentence\": \"In fact, Omar’s bigotry just earned her a spot on the cover page 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indoctrinated college students through progressive “New Civics” programs that seek to repurpose higher education away from the study of Western institutions, and even away from scholarship in general, in order to make little left-wing community organizers of our students.\", \"id\": \"polusa_v1_4354436_-1_13_Obama_73_78\"}\n{\"mention\": \"Henry Barbour\", \"polarity\": -1, \"from\": 128, \"to\": 141, \"sentence\": \"In 2014, a coalition of conservative leaders demanded that former Republican National Committee Chairman Reince Priebus censure Henry Barbour for his role in racially incendiary appeals to Democratic voters that voting for Sen.\", \"id\": \"polusa_v1_4354748_-1_40_Barbour_129_142\"}\n{\"mention\": \"the Hill\", \"polarity\": 0, \"from\": 281, \"to\": 289, \"sentence\": \"An FBI informant told three congressional committees in a written statement that Moscow routed millions to America with the expectation it would benefit Bill Clinton’s charitable efforts as then-Secretary 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\"polusa_v1_4355036_-1_0_Jerry Brown: '_0_14\"}\n{\"mention\": \"Pattison\", \"polarity\": -1, \"from\": 52, \"to\": 60, \"sentence\": \"Some black firefighters were reportedly offended by Pattison’s gesture since 90 percent of the firefighters at Engine 55 are black.\", \"id\": \"polusa_v1_4355070_-1_8_Pattison_53_61\"}\n{\"mention\": \"Engine 55\", \"polarity\": 0, \"from\": 111, \"to\": 120, \"sentence\": \"Some black firefighters were reportedly offended by Pattison’s gesture since 90 percent of the firefighters at Engine 55 are black.\", \"id\": \"polusa_v1_4355070_-1_8_Engine 55_112_121\"}\n{\"mention\": \"White House Chief Economic Advisor Gary Cohn\", \"polarity\": -1, \"from\": 51, \"to\": 95, \"sentence\": \"A source \\\"close to Trump\\\" questions the loyalty of White House Chief Economic Advisor Gary Cohn to the administration in the harshest terms.\", \"id\": \"polusa_v1_4355210_-1_1_White House Chief Economic Advisor Gary Cohn_53_97\"}\n{\"mention\": \"Conway\", 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26, \"sentence\": \"But I don’t quite have his social media firepower.\", \"id\": \"polusa_v1_4355990_-1_36_President Trump_23_26\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 50, \"to\": 55, \"sentence\": \"Asked whether Tlaib’s’s call for President Donald Trump to be impeached hurts the Democrats’ “hurts the case,” Pelosi replied: “The enthusiasm that our members have helps the case, any case….We try to build our consensus on how we go forward.\", \"id\": \"polusa_v1_4356063_-1_6_President Trump_50_55\"}\n{\"mention\": \"Sarsour\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Sarsour, who describes herself as a feminist despite being an advocate for Sharia Law, has also previously declared “jihad” against the Trump administration, and has called on Muslims in the United States to actively not assimilate into American society, but instead act “to please Allah and only Allah.”\", \"id\": \"polusa_v1_4356166_-1_18_progressive activist Linda Sarsour_1_8\"}\n{\"mention\": \"Sarsour\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Sarsour, who describes herself as a feminist despite being an advocate for Sharia Law, has also previously declared “jihad” against the Trump administration, and has called on Muslims in the United States to actively not assimilate into American society, but instead act “to please Allah and only Allah.”\", \"id\": \"polusa_v1_4356166_-1_18_Linda Sarsour_1_8\"}\n{\"mention\": \"Le Pen\", \"polarity\": 1, \"from\": 97, \"to\": 103, \"sentence\": \"Initially, Macron started out with much stronger numbers but after a week of strong campaigning, Le Pen has started to turn the tide.\", \"id\": \"polusa_v1_4356212_-1_18_Marine Le Pen_97_103\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 112, \"to\": 115, \"sentence\": \"Many have attributed the change to a poor campaign start by Macron and the incident at the Whirlpool factory in his home town of Amiens.\", \"id\": \"polusa_v1_4356212_-1_20_Marine Le Pen_113_116\"}\n{\"mention\": \"Judge Gorsuch\", \"polarity\": -1, \"from\": 20, \"to\": 33, \"sentence\": \"Schumer continued, “Judge Gorsuch, we believe, does not belong on the bench.\", \"id\": \"polusa_v1_4356408_-1_18_Gorsuch_21_34\"}\n{\"mention\": \"Jackson\", \"polarity\": -1, \"from\": 59, \"to\": 66, \"sentence\": \"Breitbart News reported in April ProPublica’s concern that Jackson “once complained that she experienced discrimination because she is white.”\", \"id\": \"polusa_v1_4356602_-1_12_Acting Assistant Secretary for Civil Rights Candice Jackson_60_67\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 24, \"to\": 29, \"sentence\": \"Obama also implied that Trump does not have “deep seriousness and focus” and is not operating “with a clear base of facts and ideas.”\", \"id\": \"polusa_v1_4356658_-1_12_President Donald Trump_25_30\"}\n{\"mention\": \"Saldana\", \"polarity\": 0, \"from\": 118, \"to\": 125, \"sentence\": \"“I’m just like, ‘People, she’s up against a man that calls women pigs on national television and she’s incompetent?'” Saldana continued.\", \"id\": \"polusa_v1_4356791_-1_6_Zoe Saldana_119_126\"}\n{\"mention\": \"Erdogan and his allies\", \"polarity\": -1, \"from\": 73, \"to\": 95, \"sentence\": \"Consistent with Celik’s remarks, Dr. Aslandogan told Breitbart News that Erdogan and his allies use association with religious minorities as a form of attack against their political opponents.\", \"id\": \"polusa_v1_4356888_-1_17_Erdogan and his allies_74_96\"}\n{\"mention\": \"them\", \"polarity\": -1, \"from\": 60, \"to\": 64, \"sentence\": \"“Erdogan, for instance, attacks his enemies by referring to them as the pawn of Israel or the pawn of the Jews or the pawn of the Catholics,” he also said.\", \"id\": \"polusa_v1_4356888_-1_21_his enemies_61_65\"}\n{\"mention\": \"Erdogan\", \"polarity\": -1, \"from\": 1, \"to\": 8, \"sentence\": \"“Erdogan, for instance, attacks his enemies by referring to them 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\"id\": \"polusa_v1_4360708_-1_8_the United States_113_130\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 49, \"to\": 54, \"sentence\": \"Several leaders of American manufacturers joined Trump for the event, highlighting the jobs they had created in the United States.\", \"id\": \"polusa_v1_4360708_-1_8_President Donald Trump_50_55\"}\n{\"mention\": \"the FBI\", \"polarity\": 0, \"from\": 106, \"to\": 113, \"sentence\": \"Republicans asked Mueller several times why Mifsud had not been prosecuted for making false statements to the FBI, when others — including Papadopoulos, former National Security Advisor Michael Flynn, and former Trump campaign manager Paul Manafort — had been.\", \"id\": \"polusa_v1_4360722_-1_22_FBI_107_114\"}\n{\"mention\": \"Murkowski\", \"polarity\": 0, \"from\": 9, \"to\": 18, \"sentence\": \"In 2015, Murkowski joined Sen.\", \"id\": \"polusa_v1_4360849_-1_15_Lisa Murkowski_10_19\"}\n{\"mention\": \"Farrow\", \"polarity\": -1, \"from\": 23, \"to\": 29, 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\"polusa_v1_4372811_-1_8_Joe Arpaio_18_28\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Wilson was reportedly charged with fleeing officers, retail theft and obstructing an officer.\", \"id\": \"polusa_v1_4373187_-1_11_John Wilson_0_7\"}\n{\"mention\": \"Scherer\", \"polarity\": 0, \"from\": 23, \"to\": 30, \"sentence\": \"Jeannine Jacobson told Scherer that Cruz can waive his half, giving the entirety to his brother.\", \"id\": \"polusa_v1_4374086_-1_22_Circuit Judge Elizabeth Scherer_23_30\"}\n{\"mention\": \"Prime Minister Malcolm Turnbull\", \"polarity\": -1, \"from\": 54, \"to\": 85, \"sentence\": \"— Donald J. Trump (@realDonaldTrump) February 2, 2017\\nPrime Minister Malcolm Turnbull was left scrambling to defend his country's allegiance to the U.S. after The Washington Post published a report on Thursday detailing a tense exchange that allegedly took place during the Australian leader's first telephone call with Trump since he became president.\", \"id\": \"polusa_v1_4374500_-1_12_Prime Minister Malcolm Turnbull_54_85\"}\n{\"mention\": \"Turnbull\", \"polarity\": -1, \"from\": 69, \"to\": 77, \"sentence\": \"The newspaper said Trump dubbed it \\\"the worst deal ever\\\" and accused Turnbull of seeking to export the \\\"next Boston bombers\\\" — a reference to Tamerlan and Dzhokhar Tsarnaev, who were born in Kyrgyzstan and set off explosives at the 2013 Boston marathon.\", \"id\": \"polusa_v1_4374500_-1_14_Prime Minister Malcolm Turnbull_70_78\"}\n{\"mention\": \"Schneiderman\", \"polarity\": -1, \"from\": 46, \"to\": 58, \"sentence\": \"According to the article, Manning Barish said Schneiderman \\\"would be 'shaking me and grabbing my face' while demanding that she repeat such things as 'I'm a little wh---.'\\\" On another occasion, Manning Barish says that Schneiderman told her \\\"If you ever left me, I'd kill you.\\\"\", \"id\": \"polusa_v1_4374681_-1_18_the powerful Democratic N.Y. Attorney General Eric Schneiderman_47_59\"}\n{\"mention\": \"Schneiderman\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Schneiderman also asked her to \\\"call him Master, and he’d slap me until I did.\\\"\", \"id\": \"polusa_v1_4374681_-1_28_Schneiderman_0_12\"}\n{\"mention\": \"Schneiderman\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Schneiderman also asked her to \\\"call him Master, and he’d slap me until I did.\\\"\", \"id\": \"polusa_v1_4374681_-1_28_the powerful Democratic N.Y. Attorney General Eric Schneiderman_0_12\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 1, \"to\": 3, \"sentence\": \"\\\"He must resign from office and be held accountable for his crimes.\\\"\", \"id\": \"polusa_v1_4374681_-1_43_Schneiderman_1_3\"}\n{\"mention\": \"Moyer\", \"polarity\": 0, \"from\": 147, \"to\": 152, \"sentence\": \"Asked whether the FBI would have been able to establish probable cause if the application “did not have the Christopher Steele information in it,” Moyer responded: \\\"So I think it's a close call, like 50/50, 51/49.\", \"id\": \"polusa_v1_4375379_-1_4_senior FBI lawyer Sally Moyer_148_153\"}\n{\"mention\": \"An 11-year-old pit bull named Sadie\", \"polarity\": 1, \"from\": 0, \"to\": 35, \"sentence\": \"An 11-year-old pit bull named Sadie has been credited for saving her family from danger after she likely sniffed out a gas leak in the basement of their Tuckahoe, New York, home.\", \"id\": \"polusa_v1_4375753_-1_1_An 11-year-old pit bull named Sadie_2_37\"}\n{\"mention\": \"Sadie\", \"polarity\": 1, \"from\": 30, \"to\": 35, \"sentence\": \"An 11-year-old pit bull named Sadie has been credited for saving her family from danger after she likely sniffed out a gas leak in the basement of their Tuckahoe, New York, home.\", \"id\": \"polusa_v1_4375753_-1_1_Sadie_32_37\"}\n{\"mention\": \"Sadie\", \"polarity\": 0, \"from\": 5, \"to\": 10, \"sentence\": \"“Did Sadie sense danger?\", \"id\": \"polusa_v1_4375753_-1_8_Sadie_6_11\"}\n{\"mention\": \"recently freed Puerto Rican nationalist Oscar López Rivera\", \"polarity\": -1, \"from\": 35, \"to\": 93, \"sentence\": \"A host of celebrations in honor of recently freed Puerto Rican nationalist Oscar López Rivera has outraged the families of those who lost relatives in a string of bombings during 1970s and 80s linked to his group, even as many Puerto Ricans hail him as a patriot and political prisoner.\", \"id\": \"polusa_v1_4376214_-1_2_recently freed Puerto Rican nationalist Oscar López Rivera_37_95\"}\n{\"mention\": \"Oscar\", \"polarity\": -1, \"from\": 75, \"to\": 80, \"sentence\": \"A host of celebrations in honor of recently freed Puerto Rican nationalist Oscar López Rivera has outraged the families of those who lost relatives in a string of bombings during 1970s and 80s linked to his group, even as many Puerto Ricans hail him as a patriot and political prisoner.\", \"id\": \"polusa_v1_4376214_-1_2_“Oscar_77_82\"}\n{\"mention\": \"Deaton\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Deaton drove away with the woman still in the car, but she managed to escape.\", \"id\": \"polusa_v1_4377357_-1_13_Deaton_0_6\"}\n{\"mention\": \"Jesus Christ\", \"polarity\": 1, \"from\": 103, \"to\": 115, \"sentence\": \"There is no one in the church who ought to be more fired up and passionate about sharing the Gospel of Jesus Christ with as many people as possible than the pastor.\", \"id\": \"polusa_v1_4377627_-1_35_Jesus_103_115\"}\n{\"mention\": \"Waas\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Waas said police arrested Alexander M. 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\\\"reckless and shows bad judgment,\\\" according to the Washington Post.\", \"id\": \"polusa_v1_4379464_-1_4_primary opponent Jennifer Wexton_29_35\"}\n{\"mention\": \"Concha\", \"polarity\": 0, \"from\": 57, \"to\": 63, \"sentence\": \"Referencing former President Bill Clinton's impeachment, Concha asserted his belief that should the same happen to Trump, it would make him a sympathetic figure and cast a vindictive light on the Democratic party.\", \"id\": \"polusa_v1_4379486_-1_7_media reporter Joe Concha_57_63\"}\n{\"mention\": \"Herrera-Dempsey\", \"polarity\": 0, \"from\": 69, \"to\": 84, \"sentence\": \"Stewart has been charged with aggravated murder for fatally shooting Herrera-Dempsey in Dublin and with murder for killing Ballard in Columbus, police said.\", \"id\": \"polusa_v1_4379580_-1_13_Herrera-Dempsey_70_85\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 1, \"from\": 200, \"to\": 212, \"sentence\": \"She added: “Whether you are talking about Pennsylvania, North Carolina, Ohio, Florida, Michigan, people are going to look at their lives in 2020 and say 'is stuff better for me now than it was before Donald Trump took office or will we give Joe Biden a chance to do nothing like we saw during the Obama years?'”\\nCLICK HERE FOR THE FOX NEWS APP\\nThe Associated Press contributed to this report.\", \"id\": \"polusa_v1_4381157_-1_23_Lara Trump_201_213\"}\n{\"mention\": \"Fico\", \"polarity\": 0, \"from\": 7, \"to\": 11, \"sentence\": \"Kiska, Fico's rival, called earlier Sunday for substantial changes in the country's coalition government or for an early election because of a \\\"huge\\\" distrust of the public in the state.\", \"id\": \"polusa_v1_4381408_-1_4_Slovak Prime Minister Robert Fico_8_12\"}\n{\"mention\": \"Turnbull\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Turnbull on Tuesday said foreign interference in politics would be outlawed under updated treason and espionage laws.\", \"id\": \"polusa_v1_4382232_-1_3_Australian 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Xi was expected to visit Pyongyang prior to Kim returning to China, showing that Kim has finally agreed to accept the role of \\\"junior partner\\\" in the relationship after a lengthy period of strained relations, said Michael Mazza of the American Enterprise Institute think tank in Washington, D.C.\\nAmid tranquil scenes of the two leaders chatting beside deep blue ocean waters and strolling through lush gardens, state media quoted Xi as telling Kim that China \\\"supports North Korea to stick to denuclearization of the Korean Peninsula and supports North Korea and the U.S. in solving the peninsula issue through dialogue and consultation.\\\"\", \"id\": \"polusa_v1_4392229_-1_8_\\\" Mazza_270_275\"}\n{\"mention\": \"Mehsud\", \"polarity\": 0, \"from\": 16, \"to\": 22, \"sentence\": \"Attorney Nazeer Mehsud says suspended police officer Rao Anwar did not appear at a hearing Saturday and the chief justice ordered his arrest.\", \"id\": 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\"polusa_v1_4502838_-1_2_Alexandria Ocasio-Cortez_0_24\"}\n{\"mention\": \"Sanford\", \"polarity\": 0, \"from\": 9, \"to\": 16, \"sentence\": \"Although Sanford was able to win a congressional seat in 2012, he lost the primary in 2018 after publicly criticizing the president.\", \"id\": \"polusa_v1_4503984_-1_14_Mark Sanford, R-S.C._10_17\"}\n{\"mention\": \"Warmbier\", \"polarity\": 1, \"from\": 116, \"to\": 124, \"sentence\": \"- Fred Warmbier, father of U.S. student held in North Korea for 15 months\\n“I beg that you see how I am only human,” Warmbier said at his trial.\", \"id\": \"polusa_v1_4505643_-1_16_Warmbier_116_124\"}\n{\"mention\": \"the president\", \"polarity\": 1, \"from\": 59, \"to\": 72, \"sentence\": \"White House press secretary Sarah Huckabee Sanders tweeted the president will “meet with those on the front lines of the national security and humanitarian crisis.”\", \"id\": \"polusa_v1_4506763_-1_22_\\\"President Trump_59_72\"}\n{\"mention\": \"Justice Kavanaugh\", \"polarity\": 0, \"from\": 29, \"to\": 46, \"sentence\": \"And I repeated that story to Justice Kavanaugh when I first greeted him here,\\\" Sotomayor said.\", \"id\": \"polusa_v1_4507651_-1_13_Brett Kavanaugh_29_46\"}\n{\"mention\": \"Engaging Trump\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Engaging Trump has rewards.\", \"id\": \"polusa_v1_4508329_-1_1_Engaging Trump_0_16\"}\n{\"mention\": \"James Devine\", \"polarity\": 0, \"from\": 74, \"to\": 86, \"sentence\": \"“We are in a war with selfish, foolish & narcissistic rich people,” wrote James Devine on Twitter.\", \"id\": \"polusa_v1_4509449_-1_3_James Devine_75_87\"}\n{\"mention\": \"former Prime Minister Alain Juppe\", \"polarity\": 0, \"from\": 71, \"to\": 104, \"sentence\": \"MACRON'S PARLIAMENTARY CANDIDATES GATHER IN PARIS\\nPhilippe is close to former Prime Minister Alain Juppe.\", \"id\": \"polusa_v1_4509668_-1_11_former Prime Minister Alain Juppe_72_105\"}\n{\"mention\": \"Philippe\", \"polarity\": 1, \"from\": 12, \"to\": 20, \"sentence\": \"Reacting to Philippe's appointment, Juppe called the new prime minister \\\"a man of great talent\\\" with \\\"all the qualities to handle the difficult job.\\\"\", \"id\": \"polusa_v1_4509668_-1_12_Edouard Philippe_12_20\"}\n{\"mention\": \"Kim\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"Kim is expected to meet President Donald Trump in May or early June.\", \"id\": \"polusa_v1_4512193_-1_12_Kim_0_4\"}\n{\"mention\": \"Levin\", \"polarity\": 0, \"from\": 45, \"to\": 50, \"sentence\": \"CLICK HERE TO GET THE FOX NEWS APP\\nFollowing Levin's rebuttal, Lee seemed to reverse course and claimed she never actually made an official diagnosis of the president, despite her book having various mental health observations about the commander-in-chief.\", \"id\": \"polusa_v1_4512856_-1_18_Mark Levin_46_51\"}\n{\"mention\": \"Sophia\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Sophia is getting older, so she wouldn’t hear it,” he said in July 2017.\", \"id\": \"polusa_v1_4513777_-1_17_Sophia_0_6\"}\n{\"mention\": \"The quartet -- George \\\"Billy\\\" Wagner III, 47; his wife, 48-year-old Angela Wagner; and George's sons, George Wagner, 27, and Edward \\\"Jake\\\" Wagner, 26 --\", \"polarity\": -1, \"from\": 0, \"to\": 152, \"sentence\": \"The quartet -- George \\\"Billy\\\" Wagner III, 47; his wife, 48-year-old Angela Wagner; and George's sons, George Wagner, 27, and Edward \\\"Jake\\\" Wagner, 26 -- spent \\\"some significant time in Alaska\\\" in the two years before their arrest, officials said.\", \"id\": \"polusa_v1_4513777_-1_4_The quartet -- George \\\"Billy\\\" Wagner III, 47; his wife, 48-year-old Angela Wagner; and George's sons, George Wagner, 27, and Edward \\\"Jake\\\" Wagner, 26 --_0_152\"}\n{\"mention\": \"Lewinsky\", \"polarity\": -1, \"from\": 165, \"to\": 173, \"sentence\": \"Hillary Clinton, who went on to be elected to the Senate and served as President Obama’s secretary of state, said 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\"polusa_v1_4544162_-1_5_De la Garza_18_29\"}\n{\"mention\": \"President Trump\", \"polarity\": 1, \"from\": 83, \"to\": 98, \"sentence\": \"Still, Conway went on: \\\"What I will tell you is that George was very supportive of President Trump, cried on election night in his MAGA hat blocks away from here at the Hilton in New York, wanted to take a job in the Trump administration and changed his mind, and was a guest of the President and First Lady months after he withdrew himself from consideration at the White House.\", \"id\": \"polusa_v1_4544269_-1_34_President Trump_84_99\"}\n{\"mention\": \"Conway\", \"polarity\": 0, \"from\": 42, \"to\": 48, \"sentence\": \"So if that’s changed, I haven’t changed,\\\" Conway continued.\", \"id\": \"polusa_v1_4544269_-1_36_George Conway '_42_48\"}\n{\"mention\": \"Alan Dershowitz\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Alan Dershowitz: Trump 'perfectly entitled to invoke executive privilege'\", \"id\": 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Francois Lecointre_139_162\"}\n{\"mention\": \"Ohio Democratic gubernatorial candidate Bill O’Neill\", \"polarity\": -1, \"from\": 0, \"to\": 52, \"sentence\": \"Ohio Democratic gubernatorial candidate Bill O’Neill apologized Saturday after boasting, unprovoked, in a viral Facebook post this week that he’s had sexual relationships with at least 50 women in his life.\", \"id\": \"polusa_v1_4567878_-1_2_Ohio Democratic gubernatorial candidate Bill O’Neill_0_54\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 104, \"to\": 106, \"sentence\": \"Nick Bailey, who has been hospitalized since helping the Skripals, released a statement Saturday saying he was \\\"merely doing his job\\\" and does not consider himself a hero.\", \"id\": \"polusa_v1_4568156_-1_24_Detective Sgt_104_106\"}\n{\"mention\": \"Lo\", \"polarity\": 1, \"from\": 10, \"to\": 12, \"sentence\": \"Katherine Lo, the founder of Eaton Workshop, told Bloomberg that the Washington location will include amenities that cater to 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to cast away their fears.\", \"id\": \"polusa_v1_4629782_-1_31_Steve Jobs_0_2\"}\n{\"mention\": \"Cook\", \"polarity\": -1, \"from\": 0, \"to\": 4, \"sentence\": \"Cook’s anti-democratic tone struck a sharp contrast with the advice that his predecessor Steve Jobs offered to graduating students at Stanford in 2005.\", \"id\": \"polusa_v1_4629782_-1_9_Tim Cook_0_5\"}\n{\"mention\": \"Buttigieg\", \"polarity\": -1, \"from\": 49, \"to\": 58, \"sentence\": \"Williams agreed with Rivera's assessment, saying Buttigieg is looking like he's \\\"small town mayor\\\" -- not presidential.\", \"id\": \"polusa_v1_4629995_-1_10_Buttigieg_50_59\"}\n{\"mention\": \"Harriet Tubman\", \"polarity\": 1, \"from\": 170, \"to\": 184, \"sentence\": \"After Democrat lawmakers and commentators spend months hammering the Trump administration for supposedly delaying the release of a $20 bill featuring famed abolishionist Harriet Tubman, several Obama-appointed officials have reportedly admitted that Treasury Secretary Steven Mnuchin had in fact followed the Obama administration's timeline for producing the new currency.\", \"id\": \"polusa_v1_4630875_-1_1_Harriet Tubman_172_186\"}\n{\"mention\": \"Harriet Tubman\", \"polarity\": 1, \"from\": 4, \"to\": 18, \"sentence\": \"\\\"So Harriet Tubman, the American hero who risked her life to free slaves, should get the $2 bill that hasn't been printed in years, and Andrew Jackson, the owner of slaves who is known for the policies that led to the deaths of countless of Native Americans, should stay on the 20?\\\"\", \"id\": \"polusa_v1_4630875_-1_23_Harriet Tubman_5_19\"}\n{\"mention\": \"Andrew Jackson\", \"polarity\": -1, \"from\": 136, \"to\": 150, \"sentence\": \"\\\"So Harriet Tubman, the American hero who risked her life to free slaves, should get the $2 bill that hasn't been printed in years, and Andrew Jackson, the owner of slaves who is known for the policies that led to the deaths of countless of Native Americans, should stay on the 20?\\\"\", \"id\": \"polusa_v1_4630875_-1_23_Andrew Jackson_137_151\"}\n{\"mention\": \"Omar\", \"polarity\": -1, \"from\": 193, \"to\": 197, \"sentence\": \"De Sousa, 61, was working in Milan as an undercover CIA officer in 2003 when U.S. and Italian intelligence agents abducted radical Egyptian cleric Osama Mustapha Hassan Nasr, also known as Abu Omar, and transported him to his native Egypt for interrogation.\", \"id\": \"polusa_v1_4631530_-1_6_Omar_194_198\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He remains jailed, and his attorney has maintained his client's innocence, according to the Associated Press.\", \"id\": \"polusa_v1_4632642_-1_33_Rodgers'_0_2\"}\n{\"mention\": \"Newsom\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Newsom, a Democrat, will travel to the capital city of San Salvador, just as President Trump and U.S. border officials are calling for tougher security measures amid a spike in Central American migrants attempting to enter the U.S. through Mexico.\", \"id\": \"polusa_v1_4632721_-1_6_Gavin Newsom_1_7\"}\n{\"mention\": \"Newsom\", \"polarity\": 1, \"from\": 244, \"to\": 250, \"sentence\": \"NEWSOM OFFERS RARE PRAISE FOR TRUMP\\n“While the Trump Administration demonizes those who are fleeing violence from Central America, California is committed to lifting up our immigrant communities and understanding the root causes of migration,” Newsom said in a statement.\", \"id\": \"polusa_v1_4632721_-1_8_Gavin Newsom_244_250\"}\n{\"mention\": \"KAMALA HARRIS\", \"polarity\": 1, \"from\": 13, \"to\": 26, \"sentence\": \"FIVE REASONS KAMALA HARRIS IS THE BRAND-NEW 2020 DEMOCRATIC PARTY FRONTRUNNER\\nIn true progressive fashion, Harris can rattle off talking points about politicians beholden to corporations, but her record reveals a special interest of her own: labor unions.\", \"id\": \"polusa_v1_4632743_-1_9_Kamala Harris_14_27\"}\n{\"mention\": \"DEMOCRATIC PARTY\", \"polarity\": 1, \"from\": 49, \"to\": 65, \"sentence\": \"FIVE REASONS KAMALA HARRIS IS THE BRAND-NEW 2020 DEMOCRATIC PARTY FRONTRUNNER\\nIn true progressive fashion, Harris can rattle off talking points about politicians beholden to corporations, but her record reveals a special interest of her own: labor unions.\", \"id\": \"polusa_v1_4632743_-1_9_Democratic Party_50_66\"}\n{\"mention\": \"Niinisto\", \"polarity\": 1, \"from\": 0, \"to\": 8, \"sentence\": \"Niinisto, a former finance minister and parliament speaker, has been a highly popular president since he took office in 2012.\", \"id\": \"polusa_v1_4632973_-1_9_President Sauli Niinisto_0_9\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 102, \"to\": 104, \"sentence\": \"Niinisto, a former finance minister and parliament speaker, has been a highly popular president since he took office in 2012.\", \"id\": \"polusa_v1_4632973_-1_9_Haavisto_103_105\"}\n{\"mention\": \"Jonathan Martin\", \"polarity\": 0, \"from\": 0, \"to\": 15, \"sentence\": \"Jonathan Martin, the national political correspondent of The New York Times, called Donald Trump a “racist” and “fascist” during two campaign conversations with a Republican National Committee staff member, according to people with direct knowledge of the exchanges.\", \"id\": \"polusa_v1_4633330_-1_1_Martin_2_17\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 157, \"to\": 164, \"sentence\": \"He was the first non-Christian candidate to win a presidential primary\\nThough he didn't publicly discuss this historic moment, many pointed out in 2016 that Sanders was the first non-Christian to win a presidential primary.\", \"id\": \"polusa_v1_4634468_-1_22_\\\" Sanders'_158_165\"}\n{\"mention\": \"Caldwell\", \"polarity\": 0, \"from\": 32, \"to\": 40, \"sentence\": \"CLICK HERE FOR THE FOX NEWS APP\\nCaldwell said the continuing violence presents a “strong opportunity to present a case to the people of Illinois to change the dynamic because people feel they have been taken for granted.”\", \"id\": \"polusa_v1_4637248_-1_10_Gianno Caldwell_33_41\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She has pleaded not guilty to aiding and abetting her husband and obstructing the investigation.\", \"id\": \"polusa_v1_4638034_-1_14_Salman_0_3\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He is highly biblical.\", \"id\": \"polusa_v1_4638082_-1_17_Donald Trump_0_2\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He said his job, and the job of his staff, was to care for whoever comes through that hospital.\", \"id\": \"polusa_v1_4639995_-1_45_Cohen_0_2\"}\n{\"mention\": \"Mr. Henry\", \"polarity\": 1, \"from\": 89, \"to\": 98, \"sentence\": \"While we most remember him for seven little words, “Give me liberty, or give me death!,” Mr. Henry only cared to be remembered for his 1765 Stamp Act Resolves that set the colonies ablaze for Independence.\", \"id\": \"polusa_v1_4640432_-1_15_Founding Father Patrick Henry_90_99\"}\n{\"mention\": \"Hillary Clinton\", \"polarity\": -1, \"from\": 193, \"to\": 208, \"sentence\": \"Democrats have lost the high ground with President Trump on Russia – the one parallel they used to separate their own bold claims of patriotism in the 2016 election – and once again, they have Hillary Clinton to thank for it.\", \"id\": \"polusa_v1_4643592_-1_24_Clinton_194_209\"}\n{\"mention\": \"Kennedy\", \"polarity\": 1, \"from\": 72, \"to\": 79, \"sentence\": \"During a rally in North Dakota on Wednesday, Trump praised the retiring Kennedy as \\\"a very special guy\\\" and \\\"a great man,\\\" telling the crowd he was \\\"very honored\\\" Kennedy chose to retire while Trump was in office because \\\"he felt confident in me to make the right choice and carry on his great legacy.\\\"\", \"id\": \"polusa_v1_4644232_-1_13_Kennedy_73_80\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 45, \"to\": 50, \"sentence\": 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Cochran's_11_18\"}\n{\"mention\": \"his\", \"polarity\": -1, \"from\": 149, \"to\": 152, \"sentence\": \"Prosecutors allege Cochran stole at least $30,000 from a charitable fund set up in part to help poor constituents and spent it at casinos and to pay his daughter's college tuition.\", \"id\": \"polusa_v1_4647196_-1_6_defense lawyer Christopher Grohman_150_153\"}\n{\"mention\": \"Cochran\", \"polarity\": -1, \"from\": 19, \"to\": 26, \"sentence\": \"Prosecutors allege Cochran stole at least $30,000 from a charitable fund set up in part to help poor constituents and spent it at casinos and to pay his daughter's college tuition.\", \"id\": \"polusa_v1_4647196_-1_6_Willie B. 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withdrawal was actually being paused, or if Graham was echoing Trump's promise for a \\\"strong, deliberate and orderly withdrawal of U.S. forces from Syria.\\\"\", \"id\": \"polusa_v1_4651581_-1_19_Graham_86_92\"}\n{\"mention\": \"Guzman\", \"polarity\": -1, \"from\": 0, \"to\": 6, \"sentence\": \"Guzman, 59, has pleaded not guilty to charges of running a massive drug trafficking operation that laundered billions of dollars and oversaw murders and kidnappings.\", \"id\": \"polusa_v1_4657506_-1_13_artist Joaquin \\\"El Chapo\\\" Guzman_0_7\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 12, \"to\": 19, \"sentence\": \"But in 2016 Sanders’ improbable Democratic primary run almost knocked off front-runner Hillary Clinton, even as socialist governments were either imploding or stagnating the world over.\", \"id\": \"polusa_v1_4658052_-1_7_Bernie Sanders_13_20\"}\n{\"mention\": \"\\\" LaHood\", \"polarity\": 0, \"from\": 110, \"to\": 118, \"sentence\": \"\\\"Our goal, my goal is that she takes her last breath from behind bars and she meets the Lord from behind bars,\\\" LaHood said Wednesday.\", \"id\": \"polusa_v1_4658202_-1_12_Bexar County District Attorney Nico LaHood_111_119\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 118, \"to\": 123, \"sentence\": \"Luntz denied the accusations at the time, saying he was focused only on conducting accurate focus groups, noting that Trump \\\"launches an attack on everyone who is even remotely critical.\\\"\", \"id\": \"polusa_v1_4658361_-1_19_Donald Trump_119_124\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 118, \"to\": 123, \"sentence\": \"Luntz denied the accusations at the time, saying he was focused only on conducting accurate focus groups, noting that Trump \\\"launches an attack on everyone who is even remotely critical.\\\"\", \"id\": \"polusa_v1_4658361_-1_19_then-candidate Trump_119_124\"}\n{\"mention\": \"Cummings\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Cummings 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\"Elizabeth\", \"polarity\": 0, \"from\": 75, \"to\": 84, \"sentence\": \"That means to prove a kidnapping took place, prosecutors will have to show Elizabeth was unlawfully removed or had her freedom restricted\\nEstranged wife speaks out\\nCummins' estranged wife, Jill Cummins, was \\\"very emotional\\\" when she learned both were found safe, her attorney, Michael Cox, said.\", \"id\": \"polusa_v1_4665269_-1_50_Elizabeth_76_85\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He loved them all,\\\" Wild said.\", \"id\": \"polusa_v1_4665721_-1_12_Kerry_0_2\"}\n{\"mention\": \"Putin\", \"polarity\": 1, \"from\": 16, \"to\": 21, \"sentence\": \"A great day for Putin, a good one for Trump\", \"id\": \"polusa_v1_4666756_-1_0_Putin_16_21\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 17, \"to\": 22, \"sentence\": \"Story highlights Trump called Scarborough \\\"crazy\\\" and Brzezinski \\\"dumb as a rock\\\"\\nRepublican and Democratic lawmakers 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Emmanuel Mensah\", \"polarity\": 1, \"from\": 1, \"to\": 24, \"sentence\": \"\\\"Private Emmanuel Mensah was a first-generation immigrant, a soldier and a New Yorker.\", \"id\": \"polusa_v1_4673744_-1_6_Private Emmanuel Mensah_2_25\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 27, \"to\": 32, \"sentence\": \"Following the meeting with Trump, Gou made a lengthy post on Facebook where he called Trump an \\\"old friend,\\\" adding that they had met for 50 minutes.\", \"id\": \"polusa_v1_4676347_-1_5_Donald Trump_28_33\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 65, \"to\": 70, \"sentence\": \"-- Meanwhile, former Secretary of State Rex Tillerson criticized Trump in another arena: foreign affairs.\", \"id\": \"polusa_v1_4676645_-1_7_US President Donald Trump_66_71\"}\n{\"mention\": \"House Minority Leader Nancy Pelosi\", \"polarity\": 1, \"from\": 23, \"to\": 57, \"sentence\": \"President Trump called House Minority Leader Nancy Pelosi tonight to congratulate her for 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leadership is not an American value\\\" https://t.co/MGeHJJixJP — The Lead CNN (@TheLeadCNN) May 1, 2017\\nAs Tapper noted, Kim is not the only \\\"brutal dictator\\\" or despot Trump reached out to over the weekend.\", \"id\": \"polusa_v1_4678786_-1_6_Kim Jong Un_20_31\"}\n{\"mention\": \"Kelly\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Kelly comes in with high expectations that his general's sense of hierarchy can bring order to a President who has long thrived on chaos and countless opinions.\", \"id\": \"polusa_v1_4679198_-1_27_Kelly_1_6\"}\n{\"mention\": \"ElZaidy\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"ElZaidy said Gadhafi had been following developments in Libya during his captivity and that he wanted to work on reconciliation and fighting terrorism in Libya.\", \"id\": \"polusa_v1_4679717_-1_21_Khaled ElZaidy_0_8\"}\n{\"mention\": \"Pompeo\", \"polarity\": 0, \"from\": 10, \"to\": 16, \"sentence\": \"\\\"Director Pompeo and has family stayed at an Agency-owned facility for three days over Christmas 2017,\\\" wrote Trapani.\", \"id\": \"polusa_v1_4680811_-1_36_Pompeo_11_17\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 68, \"to\": 73, \"sentence\": \"Muslims wary of being 'tokenized'\\nDuring his presidential campaign, Trump angered many American Muslims by making incendiary statements such as \\\"I think Islam hates us\\\" and promising to temporarily ban Muslim immigration as a counterterrorism measure.\", \"id\": \"polusa_v1_4681625_-1_37_President Trump_69_74\"}\n{\"mention\": \"Yousafzai\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"Yousafzai, the youngest recipient of the Nobel Peace Prize, is expected to meet Prime Minister Shahid Khaqan Abbasi while she is in Islamabad, where the city is on high alert for security due to her visit.\", \"id\": \"polusa_v1_4681979_-1_4_20-year-old Malala Yousafzai_1_10\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 168, \"to\": 171, \"sentence\": \"\\\"What it describes is a professional law enforcement person, who is Jim Comey, who comes up against a president who knows no limits in terms of a proper relationship,\\\" she told CNN's Dana Bash at an event for the CNN series Badass Women of Washington\\nComey took Washington by surprise earlier Wednesday when he allowed the intelligence committee to post his prepared remarks on the committee's website , one day before he's set to testify in a widely-anticipated hearing about his firing by President Donald Trump last month.\", \"id\": \"polusa_v1_4683430_-1_6_Feinstein_169_172\"}\n{\"mention\": \"Balber\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Balber said his client hasn't been interviewed yet and that special counsel Robert Mueller's investigators have not reached out about Emin and Aras Agalarov, whom he also represents.\", \"id\": \"polusa_v1_4684418_-1_6_Balber_1_7\"}\n{\"mention\": \"Anne Hidalgo\", \"polarity\": -1, \"from\": 58, \"to\": 70, \"sentence\": 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year.\", \"id\": \"polusa_v1_4689216_-1_8_Donald Trump for president_33_59\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She inspires me to join her on this journey.\", \"id\": \"polusa_v1_4691853_-1_77_Michelle_1_4\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 144, \"to\": 149, \"sentence\": \"Before Friday, Corker had been outspoken with his critiques of the President in the wake of the Charlottesville violence, saying in August that Trump has not been \\\"able to demonstrate the stability nor some of the competence that he needs to demonstrate in order to be successful.\\\"\", \"id\": \"polusa_v1_4693881_-1_11_Donald Trump_145_150\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 27, \"to\": 32, \"sentence\": \"August 17, 2017 -- Corker: Trump hasn't demonstrated the stability or competence to be successful\\nCorker slammed Trump's handling of the racially motivated protests in Charlottesville, charging that the President 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Now what for Kamala?: Harris, the California senator, was utterly impressive in Thursday's debate -- commanding a stage and looking more presidential than anyone else on it.\", \"id\": \"polusa_v1_4694303_-1_43_Harris'_26_32\"}\n{\"mention\": \"Jackman\", \"polarity\": 1, \"from\": 118, \"to\": 125, \"sentence\": \"The nation's police and defense forces are working together to ensure a safe and secure environment for the Carnival, Jackman said in video provided by CNN affiliate CNC3 Television.\", \"id\": \"polusa_v1_4695246_-1_6_Jackman_119_126\"}\n{\"mention\": \"Cohen\", \"polarity\": -1, \"from\": 194, \"to\": 199, \"sentence\": \"Stormy Daniels will be interviewed by federal prosecutors from the Southern District of New York on Monday as part of their probe into President Donald Trump's former personal attorney, Michael Cohen, according to a source familiar with the investigation.\", \"id\": \"polusa_v1_4695606_-1_1_Cohen_196_201\"}\n{\"mention\": \"Russian President Vladimir Putin\", \"polarity\": -1, \"from\": 87, \"to\": 119, \"sentence\": \"A GOP lawmaker said he is ashamed that a fellow lawmaker is a Republican after he used Russian President Vladimir Putin's \\\"talking points\\\" to dismiss President Bashar al-Assad's latest actions in the Syrian Civil War.\", \"id\": \"polusa_v1_4697694_-1_1_Russian President Vladimir Putin_89_121\"}\n{\"mention\": \"Tajani\", \"polarity\": 1, \"from\": 28, \"to\": 34, \"sentence\": \"After securing his victory, Tajani suggested that there is neither a need to press ahead with \\\"more\\\" European integration, nor to destroy this successful supranational political project to deal with the current crisis in European politics.\", \"id\": \"polusa_v1_4697739_-1_15_Tajani_29_35\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 26, \"to\": 31, \"sentence\": \"But that's not because of Trump.\", \"id\": \"polusa_v1_4698082_-1_147_President Donald Trump_26_31\"}\n{\"mention\": \"Teddy Roosevelt, the first president to travel abroad\", \"polarity\": 1, \"from\": 0, \"to\": 53, \"sentence\": \"Teddy Roosevelt, the first president to travel abroad, visited Panama City in November 1906.\", \"id\": \"polusa_v1_4698296_-1_7_Teddy Roosevelt, the first president to travel abroad_0_54\"}\n{\"mention\": \"Rodman\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Rodman also endorsed Trump for president in 2016.\", \"id\": \"polusa_v1_4699418_-1_58_former NBA star Dennis Rodman_0_6\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 57, \"to\": 60, \"sentence\": \"With her worldview forever altered by understanding that she wasn't alone, the more Stein learned, the more she felt compelled to leave the cloistered community she had been raised in, and whose religious practices she had long begun to question.\", \"id\": \"polusa_v1_4702797_-1_42_25-year-old Abby Stein_58_61\"}\n{\"mention\": \"him\", \"polarity\": 1, \"from\": 49, \"to\": 52, \"sentence\": \"\\\"We thank everyone around the world who has kept him and our family in their thoughts and prayers.\", \"id\": \"polusa_v1_4703277_-1_35_\\\"Otto Warmbier_49_52\"}\n{\"mention\": \"Mueller\", \"polarity\": -1, \"from\": 46, \"to\": 53, \"sentence\": \"Here's where things get a little trickier for Mueller.\", \"id\": \"polusa_v1_4705936_-1_20_Robert Mueller's_47_54\"}\n{\"mention\": \"Bush\", \"polarity\": -1, \"from\": 22, \"to\": 26, \"sentence\": \"Baker Kline, who said Bush told her a version of the \\\"David Cop-a-Feel\\\" joke as he groped her, had also been reluctant to share her story publicly.\", \"id\": \"polusa_v1_4706062_-1_46_he (Bush)_23_27\"}\n{\"mention\": \"Trump, himself\", \"polarity\": -1, \"from\": 80, \"to\": 94, \"sentence\": \"Story highlights The 100 days measure is linked to President Franklin Roosevelt\\nTrump, himself, talked repeatedly about his first 100 days when he was campaigning\\nWashington (CNN) President Donald Trump tweeted Friday about the \\\"ridiculous standard\\\" by which he will be judged on his accomplishments during his first 100 days in office.\", \"id\": \"polusa_v1_4706407_-1_2_Trump, himself_81_96\"}\n{\"mention\": \"him\", \"polarity\": 0, \"from\": 21, \"to\": 24, \"sentence\": \"\\\"I would've directed him to do it if I thought he wasn't doing it.\\\"\", \"id\": \"polusa_v1_4706598_-1_8_\\\"Mike_21_24\"}\n{\"mention\": \"Gianforte\", \"polarity\": -1, \"from\": 21, \"to\": 30, \"sentence\": \"JUST WATCHED Jacobs: Gianforte statement worse than assault Replay More Videos ...\", \"id\": \"polusa_v1_4706627_-1_23_Gianforte_22_31\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 0, \"to\": 22, \"sentence\": \"President Donald Trump's decision to knock London Mayor Sadiq Khan on Monday didn't come out of nowhere.\", \"id\": \"polusa_v1_4708423_-1_1_President Donald Trump_0_24\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 91, \"to\": 96, \"sentence\": \"\\\"The President is to this day the moral leader of the country,\\\" Kaufman said, warning that Trump's propensity to personally attack his opponents would lower the tone further in the wider political debate.\", \"id\": \"polusa_v1_4710514_-1_43_Donald Trump's_92_97\"}\n{\"mention\": \"She\", \"polarity\": 1, \"from\": 0, \"to\": 3, \"sentence\": \"She's regarded as the front-runner in the race to replace Gov.\", \"id\": \"polusa_v1_4713065_-1_6_South Dakota's Kristi Noem_0_3\"}\n{\"mention\": \"Adam Schiff\", \"polarity\": -1, \"from\": 9, \"to\": 20, \"sentence\": \"Now that Adam Schiff is starting to blame President Obama for Russian meddling in the election, he is probably doing so as yet another excuse that the Democrats, lead by their fearless leader, Crooked Hillary Clinton, lost the 2016 election.\", \"id\": \"polusa_v1_4713403_-1_54_Adam Schiff_10_21\"}\n{\"mention\": \"the President\", \"polarity\": -1, \"from\": 39, \"to\": 52, \"sentence\": \"Flake's prepared speech goes on to say the President's actions should be \\\"a great source of shame\\\" for the Senate and the members of the Republican Party.\", \"id\": \"polusa_v1_4713505_-1_8_President Donald Trump_40_53\"}\n{\"mention\": \"assault Wong\", \"polarity\": -1, \"from\": 109, \"to\": 121, \"sentence\": \"As they arrived, protesters at Taipei's Taoyuan International Airport also screamed insults and attempted to assault Wong.\", \"id\": \"polusa_v1_4714985_-1_11_Joshua Wong_110_122\"}\n{\"mention\": \"George W. 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Readler_244_246\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 165, \"to\": 170, \"sentence\": \"Rex Tillerson, a secretary of state not known for his eagerness to talk with the media, stepped in front of cameras earlier this month to reaffirm his commitment to Trump after multiple outlets reported that he called the President a \\\"moron\\\" after a meeting earlier this summer.\", \"id\": \"polusa_v1_4723381_-1_12_President Donald Trump_165_170\"}\n{\"mention\": \"Kelly\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Kelly brought more structure to the West Wing and cleaned house, getting rid of several Trump aides who, in his view, were working against the President or providing little benefit.\", \"id\": \"polusa_v1_4723381_-1_30_Kelly_0_5\"}\n{\"mention\": \"Michael A. Nutter\", \"polarity\": 1, \"from\": 0, \"to\": 17, \"sentence\": \"Michael A. Nutter is a CNN contributor, a Columbia University/SIPA professor of professional practice in urban and public policy and the former mayor of Philadelphia.\", \"id\": \"polusa_v1_4723840_-1_5_Michael Nutter_0_18\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump is picking the wrong battle on health care\", \"id\": \"polusa_v1_4726089_-1_0_President Trump_0_5\"}\n{\"mention\": \"Grimm\", \"polarity\": -1, \"from\": 80, \"to\": 85, \"sentence\": \"Indeed, when you compare the presidential vote patterns to the results in 2014, Grimm's performance was among the weakest among Republican incumbents.\", \"id\": \"polusa_v1_4728650_-1_82_Michael Grimm_81_86\"}\n{\"mention\": \"Comey\", \"polarity\": -1, \"from\": 78, \"to\": 83, \"sentence\": \"Story highlights Trump called the Democrats \\\"hypocrites\\\" for their outrage at Comey's dismissal\\nThe President also suggested he might cancel White House press briefings\\nTrump also denied reports that he asked Comey to pledge his loyalty to him\\n(CNN) President Donald Trump defended the timing of his firing of FBI Director James Comey in an interview Saturday night on Fox News, saying, \\\"There's really no right time to do it.\\\"\", \"id\": \"polusa_v1_4732510_-1_2_FBI Director James Comey_80_85\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 149, \"to\": 156, \"sentence\": \"He disclosed that he is cooperating with the special counsel's office and became the first person inside the Trump's administration to be charged in Mueller's probe.\", \"id\": \"polusa_v1_4732521_-1_4_Mueller_150_157\"}\n{\"mention\": \"Rex Tillerson\", \"polarity\": 1, \"from\": 13, \"to\": 26, \"sentence\": \"Thank you to Rex Tillerson for his service!\", \"id\": \"polusa_v1_4733748_-1_7_Rex Tillerson_13_26\"}\n{\"mention\": \"Barron Trump\", \"polarity\": 1, \"from\": 1, \"to\": 13, \"sentence\": \"\\\"Barron Trump deserves the chance every child does -- to be a kid,\\\" Clinton wrote on her 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Hampshire_38_51\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 54, \"to\": 76, \"sentence\": \"Those show the range of reactions in New Hampshire to President Donald Trump's characterization of the state as a \\\" drug-infested den\\\" while speaking to Mexican President Enrique Peña Nieto in January.\", \"id\": \"polusa_v1_4763424_-1_4_President Donald Trump_55_77\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 158, \"to\": 160, \"sentence\": \"Trump left the impromptu briefing room without taking questions, having delivered the first emergency foreign policy statement of his presidency,\\nBut even as he confronted one of the gravest matters of his office, Trump nonetheless found it impossible to resist dropping in on a nearby wedding reception, already underway in his treasured Grand Ballroom.\", \"id\": \"polusa_v1_4764095_-1_36_Abe_159_161\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump left the impromptu briefing room without taking questions, having delivered the first emergency foreign policy statement of his presidency,\\nBut even as he confronted one of the gravest matters of his office, Trump nonetheless found it impossible to resist dropping in on a nearby wedding reception, already underway in his treasured Grand Ballroom.\", \"id\": \"polusa_v1_4764095_-1_36_Trump_0_6\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 36, \"to\": 41, \"sentence\": \"Doug Mills/The New York Times/Redux\\nTrump received a heaping of praise from Republican leaders Wednesday following the passage of the GOP tax bill, and some of the strongest praise came from Vice President Mike Pence.\", \"id\": \"polusa_v1_4766164_-1_16_President Donald Trump_37_42\"}\n{\"mention\": \"James Comey\", \"polarity\": -1, \"from\": 69, \"to\": 80, \"sentence\": \"When will people start saying, \\\"thank you, Mr. President, for firing James Comey?\\\"\", \"id\": \"polusa_v1_4772500_-1_16_James 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operatives claim to have compromising personal and financial information about Trump, multiple US officials with direct knowledge of the briefings.\", \"id\": \"polusa_v1_4785748_-1_11_President-elect Donald Trump_1_6\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 29, \"to\": 32, \"sentence\": \"To prove how deeply personal she thinks it is, the Wisconsin politician provided her own story: \\\"For me, I was a child who had a very serious illness and then was labeled as a kid with a pre-existing condition.\", \"id\": \"polusa_v1_4787991_-1_5_Democratic Senator Tammy Baldwin_30_33\"}\n{\"mention\": \"the Pentagon\", \"polarity\": 0, \"from\": 396, \"to\": 408, \"sentence\": \"Story highlights Defense Secretary James Mattis announced an advisory panel would make recommendations on implementation of Trump's directive\\nTransgender troops have been openly serving in the military since June 2016\\nWashington (CNN) Transgender members of the military will be able to re-enlist for service while President Donald Trump's directive barring transgender recruits is under review, the Pentagon has confirmed.\", \"id\": \"polusa_v1_4793314_-1_2_Pentagon_398_410\"}\n{\"mention\": \"Ted Cruz\", \"polarity\": -1, \"from\": 81, \"to\": 89, \"sentence\": \"BASH: I can't believe I'm going to ask you this, but so you're officially saying Ted Cruz is OK with people buying sex toys?\", \"id\": \"polusa_v1_4793563_-1_125_CRUZ: One of those laws was a law restricting the sale of sex toys_82_90\"}\n{\"mention\": \"Vladimir Putin\", \"polarity\": 0, \"from\": 38, \"to\": 52, \"sentence\": \"Hide Caption 7 of 14\\nPhotos: The 2017 Vladimir Putin calendar July -- \\\"Mankind will be interested to know that we have such riches!\", \"id\": \"polusa_v1_4803134_-1_13_Putin_38_52\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 55, \"to\": 62, \"sentence\": \"Among Democrats and independents, approval ratings for Mueller have not changed significantly.\", \"id\": 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\"polarity\": 0, \"from\": 289, \"to\": 300, \"sentence\": \"Noting that North Korea has a history of playing out talks while it pockets concessions -- a hallmark of talks in 1994, 2005 and 2012 -- Harris said he thinks Trump is \\\"spot on when he says he's not going to wait that long\\\" and that he'll know within a year ... the seriousness with which Kim Jong Un approaches this deal.\\\"\", \"id\": \"polusa_v1_4812658_-1_40_Kim Jong Un_290_301\"}\n{\"mention\": \"McConnell\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"McConnell, who has led the Senate Republicans for a decade, may be one of the most disciplined politicians in America and therefore uniquely suited for the task.\", \"id\": \"polusa_v1_4813667_-1_10_McConnell_0_10\"}\n{\"mention\": \"Senate\", \"polarity\": 1, \"from\": 27, \"to\": 33, \"sentence\": \"McConnell, who has led the Senate Republicans for a decade, may be one of the most disciplined politicians in America and therefore uniquely suited for the 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\"from\": 117, \"to\": 125, \"sentence\": \"It has been well documented that Trump stretches the truth in making his case to the American people; in this sense, Giuliani fits right into the team.\", \"id\": \"polusa_v1_55255444_-1_9_Giuliani_117_125\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 33, \"to\": 38, \"sentence\": \"It has been well documented that Trump stretches the truth in making his case to the American people; in this sense, Giuliani fits right into the team.\", \"id\": \"polusa_v1_55255444_-1_9_Trump_33_38\"}\n{\"mention\": \"William Aitcheson\", \"polarity\": 0, \"from\": 0, \"to\": 17, \"sentence\": \"William Aitcheson, a priest in the Roman Catholic Diocese of Arlington, Virginia.\", \"id\": \"polusa_v1_55257673_-1_7_Father William Aitcheson_0_17\"}\n{\"mention\": \"\\\" Lycoming County Coroner Charles Kiessling\", \"polarity\": 0, \"from\": 241, \"to\": 284, \"sentence\": \"Facebook\\nJill Greninger, 35, was standing on stairs next to an industrial-size meat grinder while working at Economy Locker Storage Co., Inc. in Pennsdale when she \\\"tragically either fell or was drawn into the machine resulting in her death,\\\" Lycoming County Coroner Charles Kiessling said in a statement.\", \"id\": \"polusa_v1_55258295_-1_6_\\\" Lycoming County Coroner Charles Kiessling_241_284\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 82, \"to\": 97, \"sentence\": \"Mark Takano, D-Calif., tweeted: \\\"I did not attend the inauguration because I felt President Trump lacked 'moral legitimacy.'\", \"id\": \"polusa_v1_55259716_-1_68_Donald Trump's_82_97\"}\n{\"mention\": \"the inauguration\", \"polarity\": -1, \"from\": 50, \"to\": 66, \"sentence\": \"Mark Takano, D-Calif., tweeted: \\\"I did not attend the inauguration because I felt President Trump lacked 'moral legitimacy.'\", \"id\": \"polusa_v1_55259716_-1_68_the inauguration_50_66\"}\n{\"mention\": \"Franken\", \"polarity\": 0, \"from\": 162, \"to\": 169, \"sentence\": \"Related: Sex harassment cases redraw election map next year\\n\\\"We still have a lot of work to do together on issues ranging from net neutrality to climate change,\\\" Franken said.\", \"id\": \"polusa_v1_55262498_-1_14_Al Franken_163_170\"}\n{\"mention\": \"her\", \"polarity\": 1, \"from\": 25, \"to\": 28, \"sentence\": \"\\\"While I can never thank her enough for her love and support, I am willing to spend the rest of my life trying, honey.\\\"\", \"id\": \"polusa_v1_55262498_-1_19_Al Franken_25_28\"}\n{\"mention\": \"Donald Trump's\", \"polarity\": -1, \"from\": 155, \"to\": 169, \"sentence\": \"Fintiklis, who manages the Miami-based private equity fund Ithaca Capital, has alleged financial misconduct by Trump Hotels dating back years and has said Donald Trump's statements on immigration have destroyed his brand in Latin America.\", \"id\": \"polusa_v1_55263179_-1_16_Donald Trump's_156_170\"}\n{\"mention\": \"Kudlow\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Kudlow is a 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thanked him for \\\"fairy godmother-ing\\\" her gender transition in the early aughts (rumors of Wachowski's transition hit the press in 2003, nearly 10 years before she made an official public appearance).\", \"id\": \"polusa_v1_55264817_-1_14_Arianna Huffington_209_212\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": 1, \"from\": 178, \"to\": 200, \"sentence\": \"TRUMP AGENDA: What the tax deal might mean for 2020\\nNBC’s Jonathan Allen, on what the tax deal means now and in 2020: “By securing his first major legislative victory Wednesday, President Donald Trump demonstrated he's capable of working with his own party in Congress and added another plank to his re-election platform.\", \"id\": \"polusa_v1_55264892_-1_2_President Donald Trump_180_202\"}\n{\"mention\": \"President Trump\", \"polarity\": 1, \"from\": 119, \"to\": 134, \"sentence\": \"“Republicans in Congress celebrated the passage of the biggest rewrite of the U.S. tax code in decades Wednesday, with President 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their honeymoon and a month later \\\"physically prevented me from leaving the house.\\\"\", \"id\": \"polusa_v1_55307379_-1_17_Rob Porter_32_38\"}\n{\"mention\": \"Willoughby\", \"polarity\": 0, \"from\": 137, \"to\": 147, \"sentence\": \"The allegations surfaced Tuesday against Rob Porter, an influential senior aide in the Trump administration, from two ex-wives: Jennifer Willoughby and Colbie Holderness.\", \"id\": \"polusa_v1_55307379_-1_3_Willoughby_138_148\"}\n{\"mention\": \"his\", \"polarity\": 1, \"from\": 46, \"to\": 49, \"sentence\": \"Some in the White House were quick to jump to his defense.\", \"id\": \"polusa_v1_55307379_-1_8_Rob Porter_46_49\"}\n{\"mention\": \"Josue\", \"polarity\": 0, \"from\": 72, \"to\": 77, \"sentence\": \"There was no DNA from Jackson found on Josue's clothing and no DNA from Josue on Jackson's clothing, he said.\", \"id\": \"polusa_v1_55307876_-1_10_Josue_72_77\"}\n{\"mention\": \"Sanders\", \"polarity\": 1, \"from\": 31, \"to\": 38, \"sentence\": \"\\\"I worked as hard as I could,\\\" Sanders said Sunday.\", \"id\": \"polusa_v1_55308047_-1_10_Bernie Sanders_32_39\"}\n{\"mention\": \"Japanese\", \"polarity\": 0, \"from\": 60, \"to\": 68, \"sentence\": \"Trump awards sumo trophy as Tokyo charm offensive continues\\nJapanese Prime Minister Shinzo Abe is courting Trump with three things close to his heart: wrestling matches, burgers and golf.\", \"id\": \"polusa_v1_55314060_-1_2_Japanese_62_70\"}\n{\"mention\": \"Shinzo Abe\", \"polarity\": 1, \"from\": 84, \"to\": 94, \"sentence\": \"Trump awards sumo trophy as Tokyo charm offensive continues\\nJapanese Prime Minister Shinzo Abe is courting Trump with three things close to his heart: wrestling matches, burgers and golf.\", \"id\": \"polusa_v1_55314060_-1_2_Shinzo Abe_86_96\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 48, \"to\": 56, \"sentence\": \"But, three different sources told NBC News that Smollett’s brief experience with the criminal justice system hardly qualifies as a diverted case.\", \"id\": \"polusa_v1_55315159_-1_21_actor Jussie Smollett_49_57\"}\n{\"mention\": \"NBC News\", \"polarity\": 0, \"from\": 34, \"to\": 42, \"sentence\": \"But, three different sources told NBC News that Smollett’s brief experience with the criminal justice system hardly qualifies as a diverted case.\", \"id\": \"polusa_v1_55315159_-1_21_NBC News_35_43\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Smollett also declared himself exonerated — though he was not — and as a victim of both a hate crime and a system with a poor track record of treating people of color with fairness.\", \"id\": \"polusa_v1_55315159_-1_7_Smollett_0_8\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 0, \"to\": 8, \"sentence\": \"Smollett also declared himself exonerated — though he was not — and as a victim of both a hate crime and a system with a poor track record of treating people of color with fairness.\", \"id\": \"polusa_v1_55315159_-1_7_actor Jussie Smollett_0_8\"}\n{\"mention\": \"Wolf\", \"polarity\": -1, \"from\": 101, \"to\": 105, \"sentence\": \"After peppering her speech with several swear words as well as references to sex acts and genitalia, Wolf was criticized by an uneasy alliance of both supposedly free-speech obsessed conservatives and supposedly free-speech obsessed journalists.\", \"id\": \"polusa_v1_55315791_-1_12_comedian Michelle Wolf_101_105\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 5, \"to\": 10, \"sentence\": \"That Trump is ineffective and only out to enrich himself and his wealthy friends.\", \"id\": \"polusa_v1_55318659_-1_53_President Trump_5_10\"}\n{\"mention\": \"Zhang\", \"polarity\": -1, \"from\": 7, \"to\": 12, \"sentence\": \"Yujing Zhang, the Chinese citizen arrested at Mar-a-Lago while President Trump was visiting Florida in March, was indicted Friday on two counts.\", \"id\": \"polusa_v1_55319200_-1_1_Zhang_9_14\"}\n{\"mention\": \"she\", \"polarity\": -1, \"from\": 48, \"to\": 51, \"sentence\": \"Federal authorities told a judge on Monday that she lied repeatedly to Secret Service agents while carrying computer malware unlike anything a government analyst had ever seen.\", \"id\": \"polusa_v1_55319200_-1_7_Zhang_48_51\"}\n{\"mention\": \"Secret Service\", \"polarity\": 0, \"from\": 71, \"to\": 85, \"sentence\": \"Federal authorities told a judge on Monday that she lied repeatedly to Secret Service agents while carrying computer malware unlike anything a government analyst had ever seen.\", \"id\": \"polusa_v1_55319200_-1_7_Secret Service_71_85\"}\n{\"mention\": \"Flynn\", \"polarity\": -1, \"from\": 88, \"to\": 93, \"sentence\": \"Shortly after Trump took office in January, Yates informed the White House she believed Flynn had misled senior administration officials about his communications with the Russian ambassador to the U.S., and warned that Flynn was potentially vulnerable to Russian blackmail, current and former U.S. officials told the Washington Post.\", \"id\": \"polusa_v1_55320007_-1_7_Michael Flynn_89_94\"}\n{\"mention\": \"her\", \"polarity\": 0, \"from\": 89, \"to\": 92, \"sentence\": \"Gerald Herbert / AP file\\nThursday's hearing is Kraninger's first public appearance since her nomination.\", \"id\": \"polusa_v1_55323155_-1_17_Deputy Assistant Secretary for Policy Kathy Kraninger_89_92\"}\n{\"mention\": \"Foxx\", \"polarity\": -1, \"from\": 25, \"to\": 29, \"sentence\": \"Almost immediately after Foxx's office dismissed the charges, Chicago Mayor Rahm Emanuel blasted prosecutors saying it was a \\\"whitewash of justice.\\\"\", \"id\": \"polusa_v1_55323316_-1_16_Foxx_26_30\"}\n{\"mention\": \"Putin\", \"polarity\": -1, \"from\": 50, \"to\": 55, \"sentence\": \"Asked what she makes of criticism leveled against Putin, she responded: “I wouldn't draw him if I had even a hint of negativity toward him.\", \"id\": \"polusa_v1_55323916_-1_40_Putin_51_56\"}\n{\"mention\": 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\"polusa_v1_55325778_-1_32_Karpowitz_164_173\"}\n{\"mention\": \"Chaffetz\", \"polarity\": 1, \"from\": 21, \"to\": 29, \"sentence\": \"\\\"For nearly a decade Chaffetz has been a mainstay of Utah political life,\\\" the conservative Deseret News wrote in an editorial last month thanking him for his service.\", \"id\": \"polusa_v1_55325778_-1_8_Chaffetz_22_30\"}\n{\"mention\": \"Biden\", \"polarity\": 1, \"from\": 25, \"to\": 30, \"sentence\": \"ANALYSIS: At the debate, Biden revived his long-ago support for local school control.\", \"id\": \"polusa_v1_55328243_-1_1_Biden_27_32\"}\n{\"mention\": \"Kamala Harris\", \"polarity\": 0, \"from\": 4, \"to\": 17, \"sentence\": \"For Kamala Harris and Joe Biden, integration's painful past becomes the present\\nAnalysis: In the debate, Biden revived his long-ago support for local school control.\", \"id\": \"polusa_v1_55328243_-1_3_Kamala Harris_6_19\"}\n{\"mention\": \"Gianforte\", \"polarity\": -1, \"from\": 200, \"to\": 209, \"sentence\": 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\"sentence\": \"CHRIS HAYES: Totally, yeah.\", \"id\": \"polusa_v1_55332357_-1_454_CHRIS HAYES_0_12\"}\n{\"mention\": \"Hotez\", \"polarity\": -1, \"from\": 52, \"to\": 57, \"sentence\": \"It’s not difficult to find personal attacks against Hotez on the internet, including blogs that outright call him a liar.\", \"id\": \"polusa_v1_55333427_-1_48_Hotez_53_58\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 101, \"to\": 104, \"sentence\": \"Montgomery County Sheriff's Office\\nIvey, 72, will be the second woman to be governor of Alabama when she is sworn in Monday evening, the sources said.\", \"id\": \"polusa_v1_55336076_-1_20_Robert Bentley_101_104\"}\n{\"mention\": \"Bob Menendez\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Bob Menendez has been dragged down by sky-high disapproval ratings after escaping a guilty verdict when his federal corruption trial ended in a mistrial last year.\", \"id\": \"polusa_v1_55336268_-1_5_Bob Menendez_0_12\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He had changed his story several times following Wall's disappearance.\", \"id\": \"polusa_v1_55339000_-1_16_Danish submarine inventor Peter Madsen_0_2\"}\n{\"mention\": \"King\", \"polarity\": -1, \"from\": 49, \"to\": 53, \"sentence\": \"Tuesday brought the latest spate of bad news for King—National Republican Congressional Committee chairman Steve Stivers disavowing him by declaring he must \\\"stand up against white supremacy and hate.\\\"\", \"id\": \"polusa_v1_55339755_-1_5_Steve King_50_54\"}\n{\"mention\": \"President Trump\", \"polarity\": -1, \"from\": 56, \"to\": 71, \"sentence\": \"Bob Corker, R-Tenn., and Jeff Flake, R-Ariz., denounced President Trump, calling him unfit and devoid of moral leadership.\", \"id\": \"polusa_v1_55341496_-1_6_President Trump_56_71\"}\n{\"mention\": \"Corker\", \"polarity\": 0, \"from\": 80, \"to\": 86, \"sentence\": \"\\\"His governing model is to divide and to attempt to bully and to use untruths,” Corker said.\", \"id\": \"polusa_v1_55341496_-1_7_Corker_81_87\"}\n{\"mention\": \"Jim Acosta\", \"polarity\": 0, \"from\": 52, \"to\": 62, \"sentence\": \"CNN files lawsuit against Trump administration over Jim Acosta's press credentials\", \"id\": \"polusa_v1_55344385_-1_0_correspondent Jim Acosta_52_62\"}\n{\"mention\": \"Sanders\", \"polarity\": 0, \"from\": 12, \"to\": 19, \"sentence\": \"On Tuesday, Sanders responded to the suit, saying that CNN has nearly 50 other pass holders and that \\\"Acosta is no more or less special than any other media outlet or reporter with respect to the First Amendment.\\\"\", \"id\": \"polusa_v1_55344385_-1_8_Sanders_13_20\"}\n{\"mention\": \"the president\", \"polarity\": -1, \"from\": 42, \"to\": 55, \"sentence\": \"Citing North Korea's blistering rhetoric, the president pulled out of the planned June 12 talks and also threatened military action.\", \"id\": \"polusa_v1_55345929_-1_8_Vice President Mike Pence_42_55\"}\n{\"mention\": \"North Korea's\", \"polarity\": -1, \"from\": 7, \"to\": 20, \"sentence\": \"Citing North Korea's blistering rhetoric, the president pulled out of the planned June 12 talks and also threatened military action.\", \"id\": \"polusa_v1_55345929_-1_8_North Korea_7_20\"}\n{\"mention\": \"Edwards\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Edwards used abuse and threats to force 39-year-old John Christopher Smith to work as a J&J Cafeteria cook from 2009 until 2014, authorities said.\", \"id\": \"polusa_v1_55346059_-1_5_Edwards_1_8\"}\n{\"mention\": \"McConnell\", \"polarity\": 0, \"from\": 23, \"to\": 32, \"sentence\": \"The bottom line: While McConnell and his allies aim to reduce Bannon's influence with Trump and with base Republican voters, he has no intention of backing down.\", \"id\": \"polusa_v1_55346170_-1_26_McConnell_24_33\"}\n{\"mention\": \"Chris\", \"polarity\": -1, \"from\": 26, \"to\": 31, \"sentence\": \"Because of this incident, Chris was arraigned on July 7 on one count of interfering with electronic communications, a felony, and one count of malicious destruction of a building under $200, a misdemeanor.\", \"id\": \"polusa_v1_55348041_-1_35_Chris_26_31\"}\n{\"mention\": \"Chris\", \"polarity\": -1, \"from\": 26, \"to\": 31, \"sentence\": \"Because of this incident, Chris was arraigned on July 7 on one count of interfering with electronic communications, a felony, and one count of malicious destruction of a building under $200, a misdemeanor.\", \"id\": \"polusa_v1_55348041_-1_35_Theresa Lockhart_26_31\"}\n{\"mention\": \"Theresa\", \"polarity\": 0, \"from\": 37, \"to\": 44, \"sentence\": \"Senior Deputy Police Chief Blue said Theresa’s case is open, ongoing and active.\", \"id\": \"polusa_v1_55348041_-1_61_Theresa_38_45\"}\n{\"mention\": \"Donald Trump\", \"polarity\": -1, \"from\": 75, \"to\": 87, \"sentence\": \"Play Facebook\\nTwitter\\nGoogle Plus\\nEmbed Michael Moore explains how to stop Donald Trump 11:17 autoplay autoplay Copy this code to your website or blog\\nSeveral Republican congress members have faced raucous town halls during the last week.\", \"id\": \"polusa_v1_55349981_-1_6_Donald Trump's_76_88\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 52, \"to\": 54, \"sentence\": \"“The DOJ wanted to make this case about bathrooms,” he explained.\", \"id\": \"polusa_v1_55350100_-1_28_Nevins_53_55\"}\n{\"mention\": \"Steinfeld\", \"polarity\": 0, \"from\": 53, \"to\": 62, \"sentence\": \"Vrba told investigators he initially tried to poison Steinfeld, then described how he stabbed Steinfeld in the living room of Calderas' mobile home, Deputy Rowdy Douglas wrote in a probable cause statement.\", \"id\": \"polusa_v1_55350780_-1_29_Lee Steinfeld_54_63\"}\n{\"mention\": \"Freeman\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Freeman, a former mixed martial arts fighter from Florida, is now responsible for burying Manson's body, which has remained at 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107, \"sentence\": \"His brother \\\"will be the most dynamic 70-something-year-old you've ever met in your entire life,\\\" should he run, he said.\", \"id\": \"polusa_v1_55362630_-1_46_Frank Biden_105_107\"}\n{\"mention\": \"Gorsuch\", \"polarity\": -1, \"from\": 29, \"to\": 36, \"sentence\": \"Latino Legal Groups React to Gorsuch Nomination with Wariness, Concerns\", \"id\": \"polusa_v1_55363300_-1_0_Gorsuch_29_36\"}\n{\"mention\": \"Gorsuch\", \"polarity\": -1, \"from\": 29, \"to\": 36, \"sentence\": \"Latino Legal Groups React to Gorsuch Nomination with Wariness, Concerns\", \"id\": \"polusa_v1_55363300_-1_0_Supreme Court Nominee Neil Gorsuch_29_36\"}\n{\"mention\": \"Jan Jordan's\", \"polarity\": -1, \"from\": 54, \"to\": 66, \"sentence\": \"Pinellas County Sheriff Bob Gualtieri said that Capt. 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\"polusa_v1_55406066_-1_6_Apple Chief Executive Officer Tim Cook_199_203\"}\n{\"mention\": \"Irvin\", \"polarity\": -1, \"from\": 36, \"to\": 41, \"sentence\": \"Greenlee was sentenced to life, and Irvin and Shepherd to death.\", \"id\": \"polusa_v1_55406198_-1_33_Irvin_36_41\"}\n{\"mention\": \"Tyndall\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Tyndall very much took up Faraday’s mantle as a prominent public advocate of science.\", \"id\": \"polusa_v1_55413273_-1_24_John Tyndall_1_8\"}\n{\"mention\": \"Roland Jackson\", \"polarity\": 1, \"from\": 14, \"to\": 28, \"sentence\": \"In many ways, Roland Jackson has done a great service in his detailed and careful presentation of John Tyndall’s life at a time when science is under attack, neglected and misunderstood, especially by those in government.\", \"id\": \"polusa_v1_55413273_-1_44_Mr. Jackson_15_29\"}\n{\"mention\": \"She\", \"polarity\": -1, \"from\": 0, \"to\": 3, \"sentence\": \"She now seems uninterested in even 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influence.\", \"id\": \"polusa_v1_55463877_-1_1_Chinese President Xi Jinping_32_60\"}\n{\"mention\": \"the Asia-Pacific\", \"polarity\": 0, \"from\": 115, \"to\": 131, \"sentence\": \"Vice President Mike Pence and Chinese President Xi Jinping presented conflicting visions for trade and security in the Asia-Pacific, as the U.S. and China vie for global influence.\", \"id\": \"polusa_v1_55463877_-1_1_the Asia-Pacific_117_133\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": 0, \"from\": 0, \"to\": 22, \"sentence\": \"President Donald Trump will soon make one of the most consequential appointments of his administration when he nominates the next...\", \"id\": \"polusa_v1_55466354_-1_3_President Donald Trump_1_23\"}\n{\"mention\": \"Treasury Secretary\", \"polarity\": 0, \"from\": 130, \"to\": 148, \"sentence\": \"Now, the couple are big supporters of President-elect Donald Trump and have no hard feelings against Mr. Mnuchin, his nominee for Treasury Secretary.\", \"id\": 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election.\", \"id\": \"polusa_v1_59515694_-1_5_Randy Hultgren_0_14\"}\n{\"mention\": \"Hultgren\", \"polarity\": 1, \"from\": 6, \"to\": 14, \"sentence\": \"Randy Hultgren of Plano: a solid conservative who defeated his Democratic opponent by more than 18 percentage points in the 2016 election.\", \"id\": \"polusa_v1_59515694_-1_5_Hultgren_6_14\"}\n{\"mention\": \"Glover\", \"polarity\": 0, \"from\": 58, \"to\": 64, \"sentence\": \"The men confessed, but DNA tests in 2011 matched DNA from Glover’s body to Johnny \\\"Maniac\\\" Douglas, a murderer and sex offender shot to death in 2008.\", \"id\": \"polusa_v1_59517596_-1_5_Nina Glover_59_65\"}\n{\"mention\": \"Schakowsky\", \"polarity\": -1, \"from\": 24, \"to\": 34, \"sentence\": \"\\\"When I talk to voters, Schakowsky seems to be a very polarizing figure, and after more than 20 years in office, some people feel like she's no longer listening to local concerns, but stuck on federal issues,\\\" Rice said.\", \"id\": \"polusa_v1_59518072_-1_17_Schakowsky_25_35\"}\n{\"mention\": \"Kalinich\", \"polarity\": 0, \"from\": 12, \"to\": 20, \"sentence\": \"Gail Chaney Kalinich, a lawyer and official of the League of Women Voters of Glen Ellyn, said Roskam had agreed to the Thursday meeting as long as no recording devices were used and no members of the news media were on hand.\", \"id\": \"polusa_v1_59518665_-1_13_Kalinich_13_21\"}\n{\"mention\": \"Brown\", \"polarity\": 1, \"from\": 7, \"to\": 12, \"sentence\": \"Ernest Brown, a former high ranking Chicago Police official has died after suffering an apparent heart attack at a South Loop restaurant Saturday, officials said.\", \"id\": \"polusa_v1_59518965_-1_1_Brown_9_14\"}\n{\"mention\": \"These\", \"polarity\": 1, \"from\": 1, \"to\": 6, \"sentence\": \"\\\"These are young people who are dedicating their lives,\\\" Cuomo said.\", \"id\": \"polusa_v1_59520490_-1_10_These_2_7\"}\n{\"mention\": \"Emanuel\", \"polarity\": 1, \"from\": 0, \"to\": 7, \"sentence\": \"Emanuel is leveling the focus of his argument at automatic cost-of-living increases built into many state and city pension plans.\", \"id\": \"polusa_v1_59520971_-1_27_Emanuel_0_8\"}\n{\"mention\": \"Akorn\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Akorn, valued at more than $4 billion, develops, manufactures and markets generic and branded prescription drugs, over-the-counter consumer health products and animal health pharmaceuticals.\", \"id\": \"polusa_v1_59524116_-1_10_Akorn_1_6\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said Sroka, who he called “an extraordinary fisherman and an even better person,” had been a member of the harbor association for 38 years.\", \"id\": \"polusa_v1_59524327_-1_7_Wilmette Harbor Association President Matthew Bevenour_1_3\"}\n{\"mention\": \"Kim\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"Kim said Wednesday that Abernathy's comment was troublesome.\", \"id\": \"polusa_v1_59524515_-1_21_mayoral candidate Holly Kim_1_4\"}\n{\"mention\": \"Kelly\", \"polarity\": -1, \"from\": 58, \"to\": 63, \"sentence\": \"There were 21 bullets fired at Hernandez, 11 of them from Kelly’s gun, according to police records.\", \"id\": \"polusa_v1_59526771_-1_29_Chicago police officer Patrick Kelly_59_64\"}\n{\"mention\": \"His\", \"polarity\": 0, \"from\": 0, \"to\": 3, \"sentence\": \"His lawsuit against the city and four arresting officers cites false arrest and excessive force.\", \"id\": \"polusa_v1_59528492_-1_6_Lawrence Crosby_0_3\"}\n{\"mention\": \"Vekselberg\", \"polarity\": 1, \"from\": 276, \"to\": 286, \"sentence\": \"Columbus Nova's attorney Richard Owens said in a statement that, after Trump's inauguration, the firm hired Cohen as a business consultant \\\"regarding potential sources of capital and potential investments in real estate and other ventures,\\\" but that it had nothing to do with Vekselberg.\", \"id\": \"polusa_v1_59529921_-1_11_Russian billionaire Victor Vekselberg_277_287\"}\n{\"mention\": \"Walker\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Walker credited an improved economy as allowing him to propose spending more money on education and other areas he had previously targeted for cuts.\", \"id\": \"polusa_v1_59531959_-1_21_Walker_0_6\"}\n{\"mention\": \"Halfman\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Halfman described Tyma as “a lovely little guy.”\", \"id\": \"polusa_v1_59532842_-1_18_Halfman_0_7\"}\n{\"mention\": \"Tyma\", \"polarity\": 1, \"from\": 18, \"to\": 22, \"sentence\": \"Halfman described Tyma as “a lovely little guy.”\", \"id\": \"polusa_v1_59532842_-1_18_Tyma_18_22\"}\n{\"mention\": \"The good Lord\", \"polarity\": 1, \"from\": 0, \"to\": 13, \"sentence\": \"The good Lord put us on Earth.\", \"id\": \"polusa_v1_59534066_-1_40_God_0_13\"}\n{\"mention\": \"Matthews\", \"polarity\": 0, \"from\": 74, \"to\": 82, \"sentence\": \"\\\"I can't describe how sorry I am for the death of Staff Sergeant Melgar,\\\" Matthews told the court.\", \"id\": \"polusa_v1_59534449_-1_5_Adam Matthews_75_83\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 94, \"to\": 102, \"sentence\": \"Then Foxx’s office dropped the charges without warning or explanation to the public, allowing Smollett to claim innocence.\", \"id\": \"polusa_v1_59537417_-1_33_Smollett_94_102\"}\n{\"mention\": \"Hunt\", \"polarity\": 0, \"from\": 13, \"to\": 17, \"sentence\": \"It's a lot,\\\" Hunt said.\", \"id\": \"polusa_v1_59537634_-1_14_Hunt_13_17\"}\n{\"mention\": \"Justus Howell\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"Justus Howell rally Frank Abderholden / Lake County News-Sun Yolands McNair of Detroit, Mich., lost her daughter Adaisha Miller, 24 after she was shot and killed by an off duty police officer who was holding a party at his house.\", \"id\": \"polusa_v1_59538120_-1_18_Latoya Howell_1_14\"}\n{\"mention\": \"Latoya Howell\", \"polarity\": 1, \"from\": 99, \"to\": 112, \"sentence\": \"She and other mothers who have lost children to officer involved shootings were in Zion to support Latoya Howell on the second anniversary of her son, Justus's, shooting by police.\", \"id\": \"polusa_v1_59538120_-1_19_Latoya Howell_99_112\"}\n{\"mention\": \"David\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"David's doesn't expect the process to materially impact its business or interfere with day-to-day operations or its relationships with vendors and customers, according to the company.\", \"id\": \"polusa_v1_59538289_-1_10_David_0_5\"}\n{\"mention\": \"Kelly\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Kelly’s eagerness to defend the president’s unconscionable behavior and Kelly’s own lack of respect for civilian politicians simply feed Trump’s demons.\", \"id\": \"polusa_v1_59538308_-1_35_White House Chief of Staff John Kelly_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 137, \"to\": 142, \"sentence\": \"Kelly’s eagerness to defend the president’s unconscionable behavior and Kelly’s own lack of respect for civilian politicians simply feed Trump’s demons.\", \"id\": \"polusa_v1_59538308_-1_35_Trump_137_142\"}\n{\"mention\": \"Dominguez\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Dominguez recently left her position after more than five years in the city legal department to take a job with the Illinois Attorney General's office in Chicago.\", \"id\": \"polusa_v1_59538701_-1_3_Dominguez_1_10\"}\n{\"mention\": \"the governor\", \"polarity\": -1, \"from\": 14, \"to\": 26, \"sentence\": \"Democrats say the governor has continually shifted his requirements for an agreement to avoid being put in the position of having to decide whether to sign a budget that will require unpopular tax hikes just as he's about to ask voters for a second term.\", \"id\": \"polusa_v1_59539001_-1_16_the governor_14_26\"}\n{\"mention\": \"Blagojevich\", \"polarity\": -1, \"from\": 125, \"to\": 136, \"sentence\": \"In June 2008, a few months before the phone calls between Pritzker and the governor, Antoin \\\"Tony\\\" Rezko, who had been a key Blagojevich fundraiser and adviser, was convicted by a federal jury of corruption charges after a headline-grabbing trial that lasted weeks.\", \"id\": \"polusa_v1_59540821_-1_40_Blagojevich_125_136\"}\n{\"mention\": \"Pritzker\", \"polarity\": -1, \"from\": 58, \"to\": 66, \"sentence\": \"In June 2008, a few months before the phone calls between Pritzker and the governor, Antoin \\\"Tony\\\" Rezko, who had been a key Blagojevich fundraiser and adviser, was convicted by a federal jury of corruption charges after a headline-grabbing trial that lasted weeks.\", \"id\": \"polusa_v1_59540821_-1_40_J.B. Pritzker_58_66\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He also ran for president last year.\", \"id\": \"polusa_v1_59541586_-1_14_Jansa_0_2\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He has made friends (\\\"Krispy\\\" and \\\"D-Block\\\"), cares for prison cats and continues to wield significant power over Phoenixus, a privately-held Swiss pharmaceutical company.\", \"id\": \"polusa_v1_59541929_-1_13_Martin Shkreli_0_2\"}\n{\"mention\": \"Novack\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Novack said commission members ultimately will review the results and share them with city officials and the community at large.\", \"id\": \"polusa_v1_59543133_-1_15_Novack_0_7\"}\n{\"mention\": \"Bass\", \"polarity\": 1, \"from\": 13, \"to\": 17, \"sentence\": \"Beyond that, Bass urged students to think about running for office, even as students.\", \"id\": \"polusa_v1_59543239_-1_30_Bass_14_18\"}\n{\"mention\": \"Wolf\", \"polarity\": 0, \"from\": 103, \"to\": 107, \"sentence\": \"And while an official \\\"We Can Help\\\" program is new to the department, it is not new to Elgin officers, Wolf said.\", \"id\": \"polusa_v1_59543812_-1_30_Elgin Deputy Chief Bill Wolf Janelle Walker / The Courier-News Elgin Deputy Chief Bill Wolf_103_107\"}\n{\"mention\": \"Sustrich, Reinking's former boss\", \"polarity\": 0, \"from\": 0, \"to\": 32, \"sentence\": \"Sustrich, Reinking's former boss, described him as appearing paranoid and delusional at times.\", \"id\": \"polusa_v1_59544078_-1_28_Sustrich, Reinking's former boss_0_33\"}\n{\"mention\": \"Sanders\", \"polarity\": -1, \"from\": 41, \"to\": 48, \"sentence\": \"Because of his political influence, what Sanders said to and about Vought in their contentious exchange is frightening and depressing to people of faith.\", \"id\": \"polusa_v1_59544166_-1_21_Bernie Sanders_42_49\"}\n{\"mention\": \"Vought\", \"polarity\": -1, \"from\": 67, \"to\": 73, \"sentence\": \"Because of his political influence, what Sanders said to and about Vought in their contentious exchange is frightening and depressing to people of faith.\", \"id\": \"polusa_v1_59544166_-1_21_Vought_68_74\"}\n{\"mention\": \"the Hardest Hit Fund\", \"polarity\": 1, \"from\": 71, \"to\": 91, \"sentence\": \"Dan Kildee, a Democrat from Flint, Mich., about his efforts to finance the Hardest Hit Fund, which funds cities, like Gary, struggling with blight issues.\", \"id\": \"polusa_v1_59544405_-1_15_the Hardest Hit Fund_71_91\"}\n{\"mention\": \"The Washington Post's Joe Heim\", \"polarity\": 0, \"from\": 241, \"to\": 271, \"sentence\": \"The woman, identified as Kashiya Nwanguma, who at the time was a 21-year-old public health major at the University of Louisville, joined two others in suing Trump in Jefferson County Circuit Court for allegedly inciting a riot, according to The Washington Post's Joe Heim.\", \"id\": 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Trump steps down!!”\", \"id\": \"polusa_v1_59548365_-1_16_Franken_8_15\"}\n{\"mention\": \"Julka\", \"polarity\": 0, \"from\": 65, \"to\": 70, \"sentence\": \"Their federal lawsuit states the resulting punishment caused the Julka boys to lose friends, bear the brunt of insults and lose \\\"overall social interaction.\\\"\", \"id\": \"polusa_v1_59548450_-1_18_Rahul Julka_66_71\"}\n{\"mention\": \"Biandudi\", \"polarity\": 1, \"from\": 11, \"to\": 19, \"sentence\": \"Meanwhile, Biandudi said she is glad her cellphone video may have helped capture what transpired.\", \"id\": \"polusa_v1_59548459_-1_49_Biandudi_12_20\"}\n{\"mention\": \"Smollett\", \"polarity\": -1, \"from\": 50, \"to\": 58, \"sentence\": \"The Cook County state’s attorney’s office charged Smollett with felony disorderly conduct for allegedly filing a false report that described an attack with racist and homophobic elements.\", \"id\": \"polusa_v1_59548626_-1_4_Jussie Smollett_50_58\"}\n{\"mention\": \"Mallott\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Mallott, in a resignation letter, apologized for \\\"inappropriate comments I made that placed a person whom I respect and revere in a position of vulnerability.\\\"\", \"id\": \"polusa_v1_59548944_-1_13_Mallott_1_8\"}\n{\"mention\": \"Mallott\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Mallott, in a resignation letter, apologized for \\\"inappropriate comments I made that placed a person whom I respect and revere in a position of vulnerability.\\\"\", \"id\": \"polusa_v1_59548944_-1_13_Mallott_0_8\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 45, \"to\": 48, \"sentence\": \"\\\"We're not towing cars to be mean-spirited,\\\" she said.\", \"id\": \"polusa_v1_59549056_-1_11_Mayor Karen Freeman-Wilson_46_49\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 63, \"to\": 68, \"sentence\": \"Moon Seong Mook, a former South Korean military official, said Trump's comments on the drills confirmed what many in South Korea had feared all along — that North Korea would attempt to drive a wedge between Washington and Seoul and gain substantial concessions from an unconventional U.S. president who thinks much less of the traditional alliance than his predecessors.\", \"id\": \"polusa_v1_59549202_-1_26_President Donald Trump_64_69\"}\n{\"mention\": \"Ezra Galston\", \"polarity\": 1, \"from\": 445, \"to\": 457, \"sentence\": \"Signature deal: SpotHero\\nMentor: Stuart Larkins (Chicago Ventures), Roy Bahat (Bloomberg Beta), Dan Levitan (Maveron), his parents\\nEducation: Bachelor's degree in happiness from New York University's Gallatin School of Individualized Study; MBA from the University of Chicago Booth School of Business\\nSocial media: @ezramogee on Twitter; blog at Breaking VC\\nAs a professional poker player turned startup employee turned business school student, Ezra Galston was looking for a way to stand out when he entered venture capital in 2012.\", \"id\": \"polusa_v1_59549832_-1_7_Ezra Galston_446_458\"}\n{\"mention\": \"Chicago\", \"polarity\": 0, \"from\": 49, \"to\": 56, \"sentence\": \"Signature deal: SpotHero\\nMentor: Stuart Larkins (Chicago Ventures), Roy Bahat (Bloomberg Beta), Dan Levitan (Maveron), his parents\\nEducation: Bachelor's degree in happiness from New York University's Gallatin School of Individualized Study; MBA from the University of Chicago Booth School of Business\\nSocial media: @ezramogee on Twitter; blog at Breaking VC\\nAs a professional poker player turned startup employee turned business school student, Ezra Galston was looking for a way to stand out when he entered venture capital in 2012.\", \"id\": \"polusa_v1_59549832_-1_7_Chicago_50_57\"}\n{\"mention\": \"Harris\", \"polarity\": 1, \"from\": 74, \"to\": 80, \"sentence\": \"At one point, Glenbrook South High School special education teacher Terry Harris would have to stand close to the student who was speaking to make sure he could understand them.\", 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the officers’ care for his son was all part of a “test case” for a new community policing study, statements the inspector general’s office labeled as disingenuous and implausible.\", \"id\": \"polusa_v1_59556386_-1_31_Escamilla_34_43\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 0, \"to\": 7, \"sentence\": \"Clinton later in the interview admitted he had not personally apologized to Lewinsky, the intern with whom he had an affair while president.\", \"id\": \"polusa_v1_59556466_-1_13_Clinton_0_7\"}\n{\"mention\": \"Emanuel\", \"polarity\": 1, \"from\": 146, \"to\": 153, \"sentence\": \"And I think that it would be a tremendous investment and job creator, an economic engine for the city that will pay dividends for decades ahead,\\\" Emanuel added.\", \"id\": \"polusa_v1_59557190_-1_11_Mayor Rahm Emanuel_146_153\"}\n{\"mention\": \"Acosta\", \"polarity\": -1, \"from\": 53, \"to\": 59, \"sentence\": \"Sanders initially explained the decision by accusing Acosta of making 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/ RedEye\", \"polarity\": 0, \"from\": 304, \"to\": 336, \"sentence\": \"Hannah Steinkopf-Frank / RedEye Growing Home volunteer Teresa Mittons, front, tours one of the greenhouses with Kristin Miodonski, the director of community engagement Growing Home volunteer Teresa Mittons, front, tours one of the greenhouses with Kristin Miodonski, the director of community engagement (Hannah Steinkopf-Frank / RedEye)\\nDuring an eight-week paid program, these production assistants develop communication, responsibility and networking skills while learning the ins and outs of organic farming.\", \"id\": \"polusa_v1_59560348_-1_43_(Hannah Steinkopf-Frank / RedEye_305_337\"}\n{\"mention\": \"Lightfoot\", \"polarity\": 1, \"from\": 0, \"to\": 9, \"sentence\": \"Lightfoot has vowed to push for the elimination of aldermanic privilege, which allows aldermen to tightly control development in their wards.\", \"id\": \"polusa_v1_59560876_-1_30_Lightfoot_0_9\"}\n{\"mention\": \"Lightfoot\", \"polarity\": 1, 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on TV, print and digital ads — but is also participating in a nationwide “Rise up for Roe” tour barnstorming the country and says a coalition of liberal groups will have done around 500 anti-Kavanaugh events by the end of the August.\", \"id\": \"polusa_v1_79076846_-1_53_NARAL_0_5\"}\n{\"mention\": \"Kavanaugh\", \"polarity\": -1, \"from\": 249, \"to\": 258, \"sentence\": \"NARAL, for example, plans to spend about $1 million total on TV, print and digital ads — but is also participating in a nationwide “Rise up for Roe” tour barnstorming the country and says a coalition of liberal groups will have done around 500 anti-Kavanaugh events by the end of the August.\", \"id\": \"polusa_v1_79076846_-1_53_Brett Kavanaugh_249_258\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He also plans to tell senators, “If confirmed to the Court, I would be part of a Team of Nine, committed to deciding cases according to the Constitution and laws of the United States.\", 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\"id\": \"polusa_v1_79077766_-1_12_Graham_41_44\"}\n{\"mention\": \"South Carolina\", \"polarity\": 0, \"from\": 4, \"to\": 18, \"sentence\": \"The South Carolina senator also through his support for a new system his ally Sen.\", \"id\": \"polusa_v1_79077766_-1_12_South Carolina_5_19\"}\n{\"mention\": \"George Papadopoulos\", \"polarity\": -1, \"from\": 0, \"to\": 19, \"sentence\": \"George Papadopoulos, derided as a mere coffee boy by his detractors in the Trump campaign, was caught gossiping in Europe about dirt on Hillary Clinton the Russians had allegedly procured.\", \"id\": \"polusa_v1_79077769_-1_29_George Papadopoulos_0_19\"}\n{\"mention\": \"McCain\", \"polarity\": 1, \"from\": 12, \"to\": 18, \"sentence\": \"-- OBAMA on McCain defending his citizenship in 2008: “He saw himself as defending America’s character, not just mine … I was grateful but I wasn’t surprised.\", \"id\": \"polusa_v1_79077972_-1_55_McCain_13_19\"}\n{\"mention\": \"Baker\", \"polarity\": -1, \"from\": 42, \"to\": 47, \"sentence\": \"Wall Street Journal editor-in-chief Gerry Baker has faced criticism in the past for softening coverage of President Donald Trump.\", \"id\": \"polusa_v1_79078021_-1_2_Baker_44_49\"}\n{\"mention\": \"Warren\", \"polarity\": 1, \"from\": 51, \"to\": 57, \"sentence\": \"Carlson praised the lack of \\\"identity politics\\\" in Warren's latest plan, and listed off her proposals including more workplace apprenticeship programs, and encouraging the government to buy American products when it can.\", \"id\": \"polusa_v1_79078070_-1_13_WARREN_51_57\"}\n{\"mention\": \"| Getty Warren\", \"polarity\": 1, \"from\": 0, \"to\": 14, \"sentence\": \"| Getty Warren delivers strong fundraising haul\\nBOSTON — Sen.\", \"id\": \"polusa_v1_79078077_-1_4_Warren_0_14\"}\n{\"mention\": \"Putin\", \"polarity\": -1, \"from\": 47, \"to\": 52, \"sentence\": \"• \\\"The president's refusal to acknowledge that Putin interfered in our elections should alarm us all,\\\" Sen.\", \"id\": 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Trump_18_23\"}\n{\"mention\": \"Rose\", \"polarity\": -1, \"from\": 0, \"to\": 4, \"sentence\": \"Rose was pressed the most on policies boosted by Ocasio-Cortez and his response to comments made by Omar that were widely considered anti-Semitic.\", \"id\": \"polusa_v1_79078865_-1_50_Rose_0_5\"}\n{\"mention\": \"DeSantis\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"DeSantis’ net favorability rating: 2 points, with 45 percent viewing him favorable and 43 percent negatively.\", \"id\": \"polusa_v1_79079037_-1_18_Ron DeSantis_0_8\"}\n{\"mention\": \"Gillum\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Gillum’s 50-47 percent advantage over DeSantis is buoyed by solid backing among independents and overwhelming African-American support for the first-ever black nominee for governor, according to the Quinnipiac University poll of 785 likely Florida voters.\", \"id\": \"polusa_v1_79079037_-1_4_MIAMI — Democrat Andrew Gillum_1_7\"}\n{\"mention\": \"Trump\", 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King\", \"polarity\": 0, \"from\": 108, \"to\": 145, \"sentence\": \"King takes the hot seat\\nWith help from Lauren Gardner, Brianna Gurciullo and Tanya Snyder\\nKING ON THE HILL: NHTSA Deputy Administrator Heidi King will be in the hot seat today as the Senate Commerce Committee considers her nomination for administrator, a position vacant since President Donald Trump’s inauguration.\", \"id\": \"polusa_v1_79084943_-1_2_NHTSA Deputy Administrator Heidi King_110_147\"}\n{\"mention\": \"Stephen Miller\", \"polarity\": -1, \"from\": 19, \"to\": 33, \"sentence\": \"Graham tees off on Stephen Miller over immigration\", \"id\": \"polusa_v1_79085332_-1_0_Stephen Miller_19_33\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 80, \"to\": 102, \"sentence\": \"| Getty Trump: Blumenthal lied about Vietnam, 'misrepresents' what Gorsuch said\\nPresident Donald Trump attacked the military record of Sen.\", \"id\": \"polusa_v1_79085363_-1_7_Trump_80_102\"}\n{\"mention\": \"Blumenthal\", \"polarity\": -1, \"from\": 15, \"to\": 25, \"sentence\": \"| Getty Trump: Blumenthal lied about Vietnam, 'misrepresents' what Gorsuch said\\nPresident Donald Trump attacked the military record of Sen.\", \"id\": \"polusa_v1_79085363_-1_7_Chris Cuomo_15_25\"}\n{\"mention\": \"The FRA\", \"polarity\": 1, \"from\": 18, \"to\": 25, \"sentence\": \"Rail\\nMONEY TRAIN: The FRA is offering more than $244 million in grant funding for capital rail projects under its Consolidated Rail Infrastructure and Safety Improvements program, the agency announced Wednesday.\", \"id\": \"polusa_v1_79085845_-1_25_The FRA_19_26\"}\n{\"mention\": \"Wednesday\", \"polarity\": 0, \"from\": 201, \"to\": 210, \"sentence\": \"Rail\\nMONEY TRAIN: The FRA is offering more than $244 million in grant funding for capital rail projects under its Consolidated Rail Infrastructure and Safety Improvements program, the agency announced Wednesday.\", \"id\": \"polusa_v1_79085845_-1_25_Wednesday_202_211\"}\n{\"mention\": \"Rosenstein\", \"polarity\": 0, \"from\": 0, \"to\": 10, \"sentence\": \"Rosenstein doubts foreign ads would sway American voters\", \"id\": \"polusa_v1_79085850_-1_0_Deputy Attorney General Rod Rosenstein_0_10\"}\n{\"mention\": \"Fitzgerald\", \"polarity\": -1, \"from\": 85, \"to\": 95, \"sentence\": \"Story Continued Below\\nBuying shares of tobacco companies raises even more flags than Fitzgerald’s trading in drug and food companies because it stands in such stark contrast to the CDC’s mission to persuade smokers to quit and keep children from becoming addicted.\", \"id\": \"polusa_v1_79085879_-1_5_CDC Director Brenda Fitzgerald_86_96\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump previously referred to Mueller as Comey’s “best friend” in a September interview with The Daily Caller , and claimed to have “100 pictures of him and Comey hugging and kissing each other.”\", 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and claimed she is routinely attacked for giving “honest answers” in interviews.\", \"id\": \"polusa_v1_79086322_-1_13_Grisham_1_8\"}\n{\"mention\": \"poster=\\\"http://v.politico.com/images/1155968404/201812/3318/1155968404_5978154035001_5978149579001-vs.jpg?pubId=1155968404\\\" true Women Rule Summit Freshman Dem Spanberger\", \"polarity\": 0, \"from\": 0, \"to\": 170, \"sentence\": \"poster=\\\"http://v.politico.com/images/1155968404/201812/3318/1155968404_5978154035001_5978149579001-vs.jpg?pubId=1155968404\\\" true Women Rule Summit Freshman Dem Spanberger says she won’t break vow to oppose Pelosi\\nRep.-Elect Abigail Spanberger is sticking to her vow to oppose Nancy Pelosi’s speaker bid, even as the California Democrat moves closer to securing the gavel.\", \"id\": \"polusa_v1_79086395_-1_2_Freshman Dem Spanberger_0_172\"}\n{\"mention\": \"President Barack Obama\", \"polarity\": 0, \"from\": 254, \"to\": 276, \"sentence\": \"“He executed the well-practiced maneuver once again on 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questioning Jackie’s story, said he was glad the gang rape never actually happened.\", \"id\": \"allsides_3849_1594_8_Merlan_56_62\"}\n{\"mention\": \"Clark\", \"polarity\": 0, \"from\": 109, \"to\": 114, \"sentence\": \"“This isn’t Nazi Germany — we are not asking people to carry their papers around on them at all times,” said Clark, the vice chairman of the House Public Safety and Homeland Security Committee.\", \"id\": \"polusa_v1_4290621_-1_6_Heath Clark_110_115\"}\n{\"mention\": \"Beau Biden\", \"polarity\": 1, \"from\": 90, \"to\": 100, \"sentence\": \"With heavy hearts, the Biden family—and their closest friends and loved ones—laid to rest Beau Biden, 46, on Saturday.\", \"id\": \"allsides_3156_1295_1_Biden's_92_102\"}\n{\"mention\": \"Feinstein\", \"polarity\": 0, \"from\": 24, \"to\": 33, \"sentence\": \"\\\"This is a big report,\\\" Feinstein said.\", \"id\": \"polusa_v1_4261174_-1_9_Dianne Feinstein_25_34\"}\n{\"mention\": \"Syrian President Bashar Assad\", \"polarity\": 0, 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31, \"to\": 36, \"sentence\": \"One briefing note reveals that Truss was keen to hear “what we can learn from ‘Reaganomics’ on things like regulation and red tape”.\", \"id\": \"polusa_v1_39062438_-1_8_New trade minister Liz Truss_32_37\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mr. Trump also struggled to answer if he had ever sought forgiveness from God, before reluctantly acknowledging that he had not.\", \"id\": \"allsides_3030_1239_44_Donald Trump_0_9\"}\n{\"mention\": \"\\\" Meek\", \"polarity\": 0, \"from\": 18, \"to\": 24, \"sentence\": \"I KNEW it was him,\\\" Meek told The Associated Press after being interviewed by investigators.\", \"id\": \"allsides_3115_1277_8_Joey Meek_18_24\"}\n{\"mention\": \"Mr. Obama\", \"polarity\": 1, \"from\": 127, \"to\": 136, \"sentence\": \"“Because I believe that is a growth agenda — not just an equity agenda, not just a fairness agenda — that is a growth agenda,” Mr. Obama said.\", \"id\": \"allsides_5737_2458_83_Ron Haskins, a senior fellow in economic studies at the left-leaning Brookings Institution_127_136\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 14, \"to\": 16, \"sentence\": \"I really do,\\\" he said.\", \"id\": \"polusa_v1_59520739_-1_4_President Trump_14_16\"}\n{\"mention\": \"Nora\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Nora Anne Quoirin, 15, disappeared Aug. 4 at an eco-resort in southern Negeri Sembilan state.\", \"id\": \"polusa_v1_55194278_-1_1_Nora_2_6\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 82, \"to\": 87, \"sentence\": \"Vice President Mike Pence said Sunday that the federal judge who halted President Trump’s temporary immigration ban “made the wrong decision” and vowed to use “all legal means at our disposal” to protect Americans.\", \"id\": \"allsides_1386_557_1_Trump_84_89\"}\n{\"mention\": \"Scaramucci\", \"polarity\": 1, \"from\": 107, \"to\": 117, \"sentence\": \"Story highlights The hedge fund 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campaign has tried to tamp down the controversy since it emerged this week in previews of the book “Clinton Cash: The Untold Story of How and Why Foreign Governments and Businesses Helped Make Bill and Hillary Rich.”\", \"id\": \"allsides_3315_1366_23_Clinton_4_11\"}\n{\"mention\": \"Luisa Ortega\", \"polarity\": -1, \"from\": 0, \"to\": 12, \"sentence\": \"Luisa Ortega arrived in Colombia on Friday with her husband German Ferrer after Venezuelan authorities ordered his arrest for allegedly running an extortion ring out of the prosecutor's office.\", \"id\": \"polusa_v1_4641689_-1_3_Luisa Ortega_0_13\"}\n{\"mention\": \"Davis\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Davis said about 10 first responders from the police, fire and medical response departments were also taken to the hospital as a precautionary measure, but none had shown symptoms of illness.\", \"id\": \"polusa_v1_4386725_-1_12_Larry Davis_0_6\"}\n{\"mention\": \"Priebus\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Priebus, is a Washington veteran with deep ties to Republican leadership, particularly House Speaker Paul Ryan, The Associated Press reports.\", \"id\": \"allsides_1643_664_5_Republican National Committee chairman Reince Priebus his new chief of staff_0_7\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He was supported by Deputy Solicitor Gen. 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statement.“I look forward to learning more about her, how she will interact with Congress, and how she proposes to lead the department.”\", \"id\": \"allsides_3940_1637_32_\\\"Ms. Lynch_79_88\"}\n{\"mention\": \"Priebus\", \"polarity\": 1, \"from\": 12, \"to\": 19, \"sentence\": \"\\\"Bannon and Priebus will continue the effective leadership team they formed during the campaign, working as equal partners to transform the federal government, making it much more efficient, effective and productive,\\\" it said.\", \"id\": \"allsides_1643_664_14_Republican National Committee chairman Reince Priebus his new chief of staff_12_19\"}\n{\"mention\": \"Ginsburg\", \"polarity\": 0, \"from\": 29, \"to\": 37, \"sentence\": \"A February 6 event featuring Ginsburg and private equity titan and philanthropist David Rubenstein in New York City was also canceled.\", \"id\": \"polusa_v1_4300546_-1_4_Ruth Bader Ginsburg_29_37\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He also has a financial past that ranges from misguided to high-flying depending on who is doing the describing.\", \"id\": \"allsides_3137_1287_11_Marco Rubio_0_2\"}\n{\"mention\": \"Mr. Obama and Mr. Cameron\", \"polarity\": 1, \"from\": 0, \"to\": 25, \"sentence\": \"Mr. Obama and Mr. Cameron argued that NATO must transition to a “more effective security network that fosters stability around the world,” urging member nations to bolster military spending.\", \"id\": \"allsides_4186_1744_15_Mr. Obama and Mr. Cameron_0_25\"}\n{\"mention\": \"Joe Biden\", \"polarity\": 0, \"from\": 0, \"to\": 9, \"sentence\": \"Joe Biden really wants to run for president\", \"id\": \"allsides_4585_1919_0_Joe Biden_0_9\"}\n{\"mention\": \"Rauner\", \"polarity\": 1, \"from\": 6, \"to\": 12, \"sentence\": \"Later Rauner said he preferred raising the national minimum (because raising the state minimum might give an advantage to neighboring states with lower minimums) but that he would support raising the state minimum if certain conditions were met.\", \"id\": \"allsides_3993_1659_26_Rauner_6_12\"}\n{\"mention\": \"Osama Bin Laden\", \"polarity\": -1, \"from\": 113, \"to\": 128, \"sentence\": \"On Monday morning, however, Trump doubled down on his remarks, tweeting that, \\\"Of course we should have captured Osama Bin Laden long before we did.\\\"\", \"id\": \"polusa_v1_55355520_-1_26_Osama Bin Laden_114_129\"}\n{\"mention\": \"Simpson\", \"polarity\": -1, \"from\": 9, \"to\": 16, \"sentence\": \"In 2010, Simpson was arrested one day before he was scheduled to fly to South Africa to undertake what he claimed were religious studies at a madrassa.\", \"id\": \"allsides_3275_1348_21_Elton Simpson_9_16\"}\n{\"mention\": \"Flynn\", \"polarity\": 0, \"from\": 18, \"to\": 23, \"sentence\": \"Around this time, Flynn spoke with Kislyak and urged him not to retaliate.\\n... while it's not clear what Sessions talked about\\nSessions spokeswoman Sarah Isgur Flores said that the then-senator met with Kislyak because of his position on the Senate Armed Services Committee.\", \"id\": \"polusa_v1_4255128_-1_12_Michael Flynn_18_23\"}\n{\"mention\": \"Nancy Pelosi\", \"polarity\": -1, \"from\": 10, \"to\": 22, \"sentence\": \"SEE ALSO: Nancy Pelosi sounds pessimistic note about Dems’ chances to take House The Secret Service is reeling from a new scandal after an intruder last month jumped the White House fence and made it into the executive mansion before he was apprehended.\", \"id\": \"allsides_4091_1700_7_Minority Leader Nancy Pelosi_10_22\"}\n{\"mention\": \"Riehl\", \"polarity\": -1, \"from\": 15, \"to\": 20, \"sentence\": \"At this point, Riehl is aware he has shot Deputy Parrish.\", \"id\": \"polusa_v1_113842673_-1_29_Matthew Riehl_16_21\"}\n{\"mention\": \"Deputy Parrish\", \"polarity\": 0, \"from\": 42, \"to\": 56, \"sentence\": \"At this point, Riehl is aware he has shot Deputy Parrish.\", \"id\": \"polusa_v1_113842673_-1_29_Deputy 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\"sentence\": \"The RNC has been silent on the matter of Wynn’s donations since the WSJ report was published ― opening itself to charges of hypocrisy given that the party called on Democrats to return money that Harvey Weinstein donated to their campaigns over his years of activity in fundraising circles.\", \"id\": \"polusa_v1_3926717_-1_8_casino mogul Steve Wynn_42_46\"}\n{\"mention\": \"Tom Clancy’s\", \"polarity\": 0, \"from\": 124, \"to\": 136, \"sentence\": \"SIGN UP FOR OUR NEWSLETTER\\nTake on the Santa Blanca Cartel as elite special forces operators in the Wildlands of Bolivia in Tom Clancy’s Ghost Recon Wildlands.\", \"id\": \"polusa_v1_4287432_-1_2_Tom Clancy’s_126_138\"}\n{\"mention\": \"Kemp\", \"polarity\": 1, \"from\": 0, \"to\": 4, \"sentence\": \"Kemp \\\"ran a great race in Georgia – he won,\\\" Trump wrote \\\"It is time to move on!\\\"\", \"id\": \"polusa_v1_4180752_-1_19_Brian Kemp_1_5\"}\n{\"mention\": \"Ms. Mikulski\", \"polarity\": 1, \"from\": 0, \"to\": 12, 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reinstate Trump's ban.\", \"id\": \"allsides_1385_557_49_President Trump_69_74\"}\n{\"mention\": \"Benjamin Netanyahu\", \"polarity\": -1, \"from\": 9, \"to\": 27, \"sentence\": \"Israel’s Benjamin Netanyahu faces corruption indictments\", \"id\": \"polusa_v1_55055245_-1_0_Benjamin Netanyahu_9_27\"}\n{\"mention\": \"Harry\", \"polarity\": 0, \"from\": 27, \"to\": 32, \"sentence\": \"“I don’t know about that,” Harry said.\", \"id\": \"allsides_149_62_14_Harry_27_32\"}\n{\"mention\": \"Mr. Trump “\", \"polarity\": -1, \"from\": 46, \"to\": 57, \"sentence\": \"Representative Barbara Lee of California said Mr. Trump “has demeaned and insulted the African-American community, and we are going to have to really raise our voices and resist this if these views are going to be reflected in his policies.”\", \"id\": \"allsides_1445_583_30_Mr. Trump “_46_57\"}\n{\"mention\": \"Condoleezza Rice's\", \"polarity\": 1, \"from\": 61, \"to\": 79, \"sentence\": \"Graham and his allies denounced this 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the Trump family.\\\"\", \"id\": \"polusa_v1_4802670_-1_5_Melania Trump's_55_60\"}\n{\"mention\": \"Roy Moore\", \"polarity\": -1, \"from\": 73, \"to\": 82, \"sentence\": \"“This is revolting and the Republican Party and everybody’s who endorsed Roy Moore needs to disavow his candidacy right now and ask him to withdraw,” said Senator Chris Van Hollen of Maryland, who leads the Senate Democratic campaign arm.\", \"id\": \"allsides_348_139_67_Mr. Moore_73_82\"}\n{\"mention\": \"Johnson\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Johnson said officials should “assume\\\" that \\\"the Russians will be back, and possibly other state actors, and possibly other bad cyber actors\\\"\\nJohnson told the House Intelligence Committee it is “a fact” Russian President Vladimir Putin directed cyberattacks aimed at influencing the election.\", \"id\": \"polusa_v1_55239936_-1_3_Former DHS secretary Jeh Johnson_0_8\"}\n{\"mention\": \"Steve Emsley\", \"polarity\": 0, \"from\": 0, \"to\": 12, \"sentence\": \"Steve Emsley\\nNewcastle upon Tyne\\n• My Renault Zoe has a battery capacity of 40 kilowatt hours, enough to run a one-bar electric fire for 40 hours.\", \"id\": \"polusa_v1_39007077_-1_16_Steve Emsley_1_13\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 55, \"to\": 57, \"sentence\": \"“I shall work, within the limits of judicial decency,” he wrote, “to put off decision on miscegenation as long as I can.”\", \"id\": \"allsides_5953_2552_43_Justice Felix Frankfurter_55_57\"}\n{\"mention\": \"Donald Trump\", \"polarity\": 0, \"from\": 33, \"to\": 45, \"sentence\": \"\\\"First of all, I’ve come to know Donald Trump over the last few years.\", \"id\": \"allsides_2417_981_15_Donald Trump_33_45\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 69, \"to\": 74, \"sentence\": \"Maybe there are even some callous enough to thrill to another of Mr. Trump’s careless assertions, that the N.F.L. had become too concerned with protecting players from head injuries in the 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\"from\": 50, \"to\": 55, \"sentence\": \"Related: Alabama’s women wrote the verdict on Roy Moore\\nMoore, a Republican, lost the race to Doug Jones, the first Alabama Democrat elected to the U.S. Senate in 25 years.\", \"id\": \"polusa_v1_55253529_-1_19_Roy Moore_51_56\"}\n{\"mention\": \"Scott\", \"polarity\": -1, \"from\": 32, \"to\": 37, \"sentence\": \"A bystander’s video begins with Scott and Slager both standing and locked in some type of struggle.\", \"id\": \"allsides_225_91_7_Scott_32_37\"}\n{\"mention\": \"Breyer\", \"polarity\": 0, \"from\": 83, \"to\": 89, \"sentence\": \"“I believe it highly likely that the death penalty violates the Eighth Amendment,” Breyer said.\", \"id\": \"allsides_3084_1264_10_Justice Stephen Breyer_83_89\"}\n{\"mention\": \"Flake\", \"polarity\": -1, \"from\": 6, \"to\": 11, \"sentence\": \"While Flake will be able to slow down the pace of Trump’s judicial nominations, he won’t be able to block all of them by himself.\", \"id\": 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55, \"to\": 57, \"sentence\": \"“Up at Camp David, we do skeet shooting all the time,” he told The New Republic in the interview, conducted Jan. 16, just after he unveiled his gun proposals.\", \"id\": \"allsides_5795_2482_4_Obama_55_57\"}\n{\"mention\": \"Holly Williams\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Holly Williams: Has America already ceded leadership in this industry--\\nMichael Dunne: No.\", \"id\": \"polusa_v1_113885769_-1_156_Holly Williams_0_15\"}\n{\"mention\": \"Mr. Trump\", \"polarity\": 1, \"from\": 40, \"to\": 49, \"sentence\": \"Surveys from Quinnipiac University show Mr. Trump more than doubling up Senator Marco Rubio of Florida in his home state.\", \"id\": \"allsides_2410_977_2_Donald J. 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Luis Alberto Rodríguez López-Callejas, Raul Castro's son-in-law.\", \"id\": \"polusa_v1_4699437_-1_46_Trump_0_11\"}\n{\"mention\": \"his\", \"polarity\": 0, \"from\": 46, \"to\": 49, \"sentence\": \"The opinions expressed in this commentary are his.\", \"id\": \"polusa_v1_4758038_-1_4_President Trump_46_49\"}\n{\"mention\": \"Robert Durst\", \"polarity\": -1, \"from\": 1, \"to\": 13, \"sentence\": \"“Robert Durst, Subject of HBO Documentary on Unsolved Killings, Is Arrested” (via @nytimes): http://t.co/0QIgyXtRai #TheJinx — HBO (@HBO) March 15, 2015 Catch up on the series everyone is talking about before the shocking finale.\", \"id\": \"allsides_3471_1432_77_Robert Durst_1_13\"}\n{\"mention\": \"Mnangagwa\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Mnangagwa first took office in November after Mugabe resigned under military pressure, and narrowly won a July 30 election that the opposition alleged was rigged.\", \"id\": \"polusa_v1_4430084_-1_8_President Emmerson Mnangagwa_0_10\"}\n{\"mention\": \"Mugabe\", \"polarity\": -1, \"from\": 46, \"to\": 52, \"sentence\": \"Mnangagwa first took office in November after Mugabe resigned under military pressure, and narrowly won a July 30 election that the opposition alleged was rigged.\", \"id\": \"polusa_v1_4430084_-1_8_Robert Mugabe's_47_53\"}\n{\"mention\": \"Conway\", \"polarity\": 0, \"from\": 32, \"to\": 38, \"sentence\": \"White House counselor Kellyanne Conway’s husband took to the president’s favored social media platform to make the argument that the San Francisco-based court sees so many cases overturned because of the sheer volume of cases they oversee.\", \"id\": \"polusa_v1_4284566_-1_3_Attorney George Conway_33_39\"}\n{\"mention\": \"the president\", \"polarity\": 0, \"from\": 50, \"to\": 63, \"sentence\": \"I don't think it is more dangerous than alcohol,\\\" the president said.\", \"id\": \"allsides_4650_1948_3_President Obama_50_63\"}\n{\"mention\": \"Loa-Nunez\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Loa-Nunez posted a $250 cash bond on May 10 and then disappeared, according to reports.\", \"id\": \"polusa_v1_4304820_-1_16_Juana Loa-Nunez_0_10\"}\n{\"mention\": \"Todd Akin's\", \"polarity\": -1, \"from\": 71, \"to\": 82, \"sentence\": \"Romney released a statement late Tuesday saying: \\\"As I said yesterday, Todd Akin's comments were offensive and wrong and he should very seriously consider what course would be in the best interest of our country.\", \"id\": \"allsides_6341_2728_27_Akin_71_82\"}\n{\"mention\": \"Dolan\", \"polarity\": 0, \"from\": 9, \"to\": 14, \"sentence\": \"Cardinal Dolan Battles Andrew Cuomo over Abortion Law\", \"id\": \"polusa_v1_4325162_-1_0_New York Cardinal Timothy Dolan_9_14\"}\n{\"mention\": \"Baron\", \"polarity\": 1, \"from\": 4, \"to\": 9, \"sentence\": \"But Baron got a prize of his own in the Post.\", \"id\": \"polusa_v1_79087698_-1_91_Baron_4_9\"}\n{\"mention\": \"President Donald Trump\", \"polarity\": -1, \"from\": 13, \"to\": 35, \"sentence\": \"On Thursday, President Donald Trump blocked the release of hundreds of records on the 1963 assassination of President John F. 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\"sentence\": \"The truth is that we would probably have never heard Vikki’s story if she hadn’t died in prison, but Britain is full of Vikki Thompsons – thousands of young trans people up and down the country missing out on fulfilling their potential because of prejudice, ignorance and discrimination.\", \"id\": \"polusa_v1_38938696_-1_36_Vikki_54_59\"}\n{\"mention\": \"Raja Pervez Ashraf\", \"polarity\": 0, \"from\": 444, \"to\": 462, \"sentence\": \"__Aug. 18 2008: Musharraf resigns from his post as president under pressure;\\n__Sept. 6, 2008: Bhutto's husband Asif Ali Zardari becomes president;\\n__May 2, 2011: Osama bin Laden is killed in a U.S. Navy SEALs raid in the army garrison town of Abbottabad;\\n__June 19, 2012: Supreme Court disqualifies Gilani as prime minister for not complying with a court order to request a Swiss court reopen corruption cases against Zardari;\\n__June 22, 2012: Raja Pervez Ashraf becomes prime minister, completes his term on March 16, 2013;\\n__May 11, 2013: Sharif's party, the Pakistan Muslim League, overwhelmingly wins in general elections, he becomes prime minister for third time;\\n__ July 28, 2017: Sharif is disqualified from office by the Supreme Court on corruption charges stemming from so-called leaked Panama papers;\\n__Aug. 1, 2017 Sharif's confidant Shahid Khaqan Abbasi is sworn in as prime minister;\\n__May 31: Abbasi's government completes its term in office and elections are scheduled for July 25;\\n__July 6: Anti-graft tribunal convicts Sharif in absentia and sentences him to 10 years in prison, his daughter and son in-law are sentenced to lesser term;\\n__July 13: Sharif returns home from London where his ailing wife is in hospital; he and his daughter are arrested after landing and taken to a jail in Rawalpindi;\\n__July 25: Voting takes place for Pakistan's third straight civilian government.\", \"id\": \"polusa_v1_4537616_-1_6_Raja Pervez Ashraf_445_463\"}\n{\"mention\": \"Emanuel\", \"polarity\": -1, \"from\": 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\"id\": \"polusa_v1_18207549_-1_2_Mohammed bin Salman_95_133\"}\n{\"mention\": \"The Russian president\", \"polarity\": 0, \"from\": 6, \"to\": 27, \"sentence\": \"Video\\nThe Russian president was due to discuss the murder of journalist Jamal Khashoggi with Saudi Crown Prince Mohammed bin Salman.\", \"id\": \"polusa_v1_18207549_-1_2_Putin_8_29\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 9, \"to\": 11, \"sentence\": \"What did he say there?\", \"id\": \"polusa_v1_52924931_-1_20_Bowers_9_11\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 9, \"to\": 12, \"sentence\": \"Instead, she is retiring because she wants to focus on the job she was elected to do: Serving her constituents.\", \"id\": \"allsides_3523_1455_15_Barbara Mikulski (D-MD) – who has served in Congress longer than any other woman in American history_9_12\"}\n{\"mention\": \"Cory Booker and Kirsten Gillibrand\", \"polarity\": 1, \"from\": 0, \"to\": 34, \"sentence\": \"Cory Booker and Kirsten Gillibrand to end the federal ban on medical marijuana, now legalized in 23 states.\", \"id\": \"allsides_3487_1440_3_Cory Booker and Kirsten Gillibrand_0_34\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 49, \"to\": 54, \"sentence\": \"\\\"Dreamers' lives were thrown into chaos when the Trump Administration tried to terminate the DACA program without obeying the law,\\\" said California Attorney General Xavier Becerra.\", \"id\": \"allsides_98_40_5_President Trump_49_54\"}\n{\"mention\": \"Cramer\", \"polarity\": 0, \"from\": 68, \"to\": 74, \"sentence\": \"“Her trying to cozy up to Donald Trump has resulted in good votes,” Cramer said.\", \"id\": \"polusa_v1_79074579_-1_71_Kevin Cramer_69_75\"}\n{\"mention\": \"his\", \"polarity\": 0, \"from\": 27, \"to\": 30, \"sentence\": \"Now she has agreed to join his administration.\", \"id\": \"allsides_1617_652_1_Donald Trump_27_30\"}\n{\"mention\": \"she\", \"polarity\": 0, \"from\": 4, \"to\": 7, \"sentence\": \"Now she has agreed to join his administration.\", \"id\": \"allsides_1617_652_1_Nikki Haley_4_7\"}\n{\"mention\": \"Husari\", \"polarity\": 0, \"from\": 13, \"to\": 19, \"sentence\": \"“Artillery,” Husari says, before swiftly continuing to speak, almost as if nothing had happened.\", \"id\": \"polusa_v1_3913336_-1_48_Husari_13_19\"}\n{\"mention\": \"Mrs. Clinton\", \"polarity\": -1, \"from\": 44, \"to\": 56, \"sentence\": \"Moreover, a majority of respondents believe Mrs. Clinton doesn’t care about voters’ “needs and problems” — which, you might recall, was the exact same problem Mitt Romney faced in 2012 and we all know how that turned out.\", \"id\": \"allsides_3023_1236_18_Clinton_44_56\"}\n{\"mention\": \"He\", \"polarity\": 1, \"from\": 0, \"to\": 2, \"sentence\": \"He has played the role of adjudicator for Congressional Republicans before, during last year’s fight over a payroll tax extension and the battle between Democrats and Republicans over how, or if, to pay for an emergency disaster financing bill.\", \"id\": \"allsides_5889_2525_27_Mr. Boehner_0_2\"}\n{\"mention\": \"Irma\", \"polarity\": 0, \"from\": 63, \"to\": 67, \"sentence\": \"The agency is just beginning to sort through claims related to Irma, and doesn't have a dollar figure for Irma flood payouts yet.\", \"id\": \"polusa_v1_116916665_-1_16_Harvey_63_67\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He then added: “I’m an African-American.\", \"id\": \"allsides_1783_726_7_Cam Newton_0_2\"}\n{\"mention\": \"The president\", \"polarity\": 0, \"from\": 0, \"to\": 13, \"sentence\": \"The president has no further comment.\\\"\", \"id\": \"allsides_1164_465_8_President Trump_0_13\"}\n{\"mention\": \"Duncan\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Duncan, who arrived in the U.S. from Liberia Sept. 20, first sought medical care for fever and abdominal pain Sept. 25.\", \"id\": \"allsides_4051_1683_13_Duncan_0_6\"}\n{\"mention\": \"Romney\", \"polarity\": 0, \"from\": 30, \"to\": 36, \"sentence\": \"Before the GST Steel closure, Romney left Bain in 1999 to work on the 2002 Winter Olympics in Utah.\", \"id\": \"allsides_6386_2751_22_Mitt Romney_30_36\"}\n{\"mention\": \"Delgado\", \"polarity\": 0, \"from\": 66, \"to\": 73, \"sentence\": \"Without other options, an acquaintance set up a GoFundMe page for Delgado in July 2016.\", \"id\": \"polusa_v1_3960158_-1_123_police Officer Omar Delgado_67_74\"}\n{\"mention\": \"Elizabeth Warren\", \"polarity\": 1, \"from\": 0, \"to\": 16, \"sentence\": \"Elizabeth Warren represents that hope and it's the only thing worth hoping for.\", \"id\": \"allsides_3814_1579_54_Elizabeth Warren_0_16\"}\n{\"mention\": \"Inhofe\", \"polarity\": 0, \"from\": 57, \"to\": 63, \"sentence\": \"When Humphries questioned the likelihood of impeachment, Inhofe said it wouldn’t be immediate.\", \"id\": \"allsides_5418_2307_8_James Inhofe (R-Okla.)_57_63\"}\n{\"mention\": \"he\", \"polarity\": 1, \"from\": 85, \"to\": 87, \"sentence\": \"After meetings with gun-safety and victims groups Wednesday, the vice president said he is \\\"determined\\\" to take \\\"urgent action\\\" to address gun violence.\", \"id\": \"allsides_5849_2506_3_Biden_85_87\"}\n{\"mention\": \"Aranda\", \"polarity\": -1, \"from\": 34, \"to\": 40, \"sentence\": \"Police said the suspect, Emmanuel Aranda, told them he went to the mall \\\"looking for someone to kill\\\" and chose the boy at random.\", \"id\": \"polusa_v1_113897170_-1_3_Aranda_34_40\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said he didn’t know if any friends or colleagues had received similar messages, but is hoping that law enforcement officials can track down the sender.\", \"id\": \"polusa_v1_3953594_-1_33_Gilliard_1_3\"}\n{\"mention\": \"him\", \"polarity\": 0, \"from\": 29, \"to\": 32, \"sentence\": \"Wikileaks started contacting him in late September of 2016.\", \"id\": \"allsides_326_131_16_Jr._29_32\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 92, \"to\": 94, \"sentence\": \"“Due to my position, I am not allowed to participate in any activity of private companies,” he wrote in 2010, according to court records.\", \"id\": \"polusa_v1_55029374_-1_13_Chi_93_95\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 3, \"to\": 8, \"sentence\": \"At Trump's request, Pompeo gives the president his daily intelligence briefings instead of sending other briefers from CIA headquarters.\", \"id\": \"polusa_v1_116009017_-1_21_President Trump_3_8\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 12, \"to\": 17, \"sentence\": \"— Donald J. Trump (@realDonaldTrump) August 1, 2016\", \"id\": \"allsides_1941_788_11_Republican presidential nominee Donald Trump_12_17\"}\n{\"mention\": \"Newton Falls\", \"polarity\": 0, \"from\": 71, \"to\": 83, \"sentence\": \"The Vindicator reported that Zuckerberg dined with the Moore family in Newton Falls, about 55 miles south-east of Cleveland.\", \"id\": \"polusa_v1_39026681_-1_5_Newton Falls_72_84\"}\n{\"mention\": \"Obama\", \"polarity\": -1, \"from\": 21, \"to\": 26, \"sentence\": \"Top GOP Senator Says Obama Could Be Impeached Over ‘Most Egregious Cover-Up in American History’\", \"id\": \"allsides_5418_2307_0_Obama_21_26\"}\n{\"mention\": \"Sara\", \"polarity\": 1, \"from\": 15, \"to\": 19, \"sentence\": \"\\\"This evening, Sara is getting a full medical evaluation to ensure that it’s safe for her travel to New York to be with her family and get the long-term care she needs,” said Eric Ferrero, spokesman for Amnesty International USA.\", \"id\": \"polusa_v1_4199632_-1_15_Beltran Hernandez_16_20\"}\n{\"mention\": \"Boehner\", \"polarity\": -1, \"from\": 82, \"to\": 89, \"sentence\": \"Ted Cruz (R-Texas) skipped over the pleasantries and went straight to criticizing Boehner -- without naming him -- and McConnell for making promises to conservatives and not keeping them.\", \"id\": \"allsides_2867_1170_28_John Boehner_82_89\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 11, \"to\": 13, \"sentence\": \"Each time, he was met with a bipartisan filibuster from senators angered at the legislation itself and at the process being used.\", \"id\": \"allsides_5764_2470_12_Mr. Reid_11_13\"}\n{\"mention\": \"gu.com/letters\", \"polarity\": 0, \"from\": 138, \"to\": 152, \"sentence\": \"Rosemary Chamberlin\\nBristol\\n• Join the debate – email guardian.letters@theguardian.com\\n• Read more Guardian letters – click here to visit gu.com/letters\\n• Do you have a photo you’d like to share with other Guardian readers?\", \"id\": \"polusa_v1_38983522_-1_8_gu.com/letters_139_154\"}\n{\"mention\": \"Ernst\", \"polarity\": 1, \"from\": 107, \"to\": 112, \"sentence\": \"Those named were the first-term Iowa senator Joni Ernst, the first-term Arkansas senator Tom Cotton – like Ernst a military veteran – and the governor of Indiana, Mike Pence.\", \"id\": \"allsides_2024_824_2_Ernst_107_112\"}\n{\"mention\": \"Pence\", \"polarity\": 0, \"from\": 168, \"to\": 173, \"sentence\": \"Those named were the first-term Iowa senator Joni Ernst, the first-term Arkansas senator Tom Cotton – like Ernst a military veteran – and the governor of Indiana, Mike Pence.\", \"id\": \"allsides_2024_824_2_Pence_168_173\"}\n{\"mention\": \"Robertson\", \"polarity\": -1, \"from\": 46, \"to\": 55, \"sentence\": \"These outraged messages have largely defended Robertson’s anti-gay comments as an expression of his religious beliefs without acknowledging his remarks that African Americans were better off without full civil rights.\", \"id\": \"allsides_4739_1993_24_Duck Dynasty patriarch Phil Robertson_46_55\"}\n{\"mention\": \"he\", \"polarity\": -1, \"from\": 4, \"to\": 6, \"sentence\": \"And he constantly sips from a glass of water before storming out of the room.\", \"id\": \"polusa_v1_59499078_-1_22_Actor Matt Walsh of ‘Veep’_4_6\"}\n{\"mention\": \"she\", \"polarity\": 1, \"from\": 49, \"to\": 52, \"sentence\": \"And as the election approached in recent months, she ordered a review committee to determine if Chicago’s fines, fees and collection practices should be changed to help struggling residents get out from under debts accrued from unpaid parking tickets and city sticker fines.\", \"id\": \"polusa_v1_59621831_-1_16_Antonio Perez/Chicago Tribune City clerk candidate Patricia Horton_49_52\"}\n{\"mention\": \"Roy Moore\", \"polarity\": -1, \"from\": 0, \"to\": 9, \"sentence\": \"Roy Moore is denying the allegations in The Washington Post.\", \"id\": \"allsides_343_138_25_Roy Moore_0_9\"}\n{\"mention\": \"Farage\", \"polarity\": 1, \"from\": 0, \"to\": 6, \"sentence\": \"Farage invited scrutiny of the Remainer funding and urged Brexiteers to be \\\"happy warriors\\\" in the last days of the election campaign.\", \"id\": \"polusa_v1_4317609_-1_1_Mr Farage_2_8\"}\n{\"mention\": \"Neil Armstrong\", \"polarity\": 0, \"from\": 0, \"to\": 14, \"sentence\": \"Neil Armstrong passed away in 2012 at the age of 82.\", \"id\": \"polusa_v1_113859719_-1_422_Armstrong_0_15\"}\n{\"mention\": \"Fox\", \"polarity\": 0, \"from\": 149, \"to\": 152, \"sentence\": \"“Hilario Yanez, who goes by Eli, said Trump showed courage to tackle the illegal immigration issue comprehensively during his first year in office,” Fox reported.\", \"id\": \"polusa_v1_4318520_-1_6_Hilario Yanez_150_153\"}\n{\"mention\": \"Rudy Giuliani\", \"polarity\": -1, \"from\": 0, \"to\": 13, \"sentence\": \"Rudy Giuliani made not one - but two giant unforced errors\", \"id\": \"polusa_v1_55380890_-1_0_Rudy Giuliani_0_13\"}\n{\"mention\": \"Wolff\", \"polarity\": 0, \"from\": 55, \"to\": 60, \"sentence\": \"He compared questions of his mental fitness, raised by Wolff's book, to that of President Ronald Reagan, who had suffered from Alzheimer's disease toward the end of his presidency.\", \"id\": \"polusa_v1_113833129_-1_16_Wolff_56_61\"}\n{\"mention\": \"Dzurenda\", \"polarity\": 0, \"from\": 23, \"to\": 31, \"sentence\": \"\\\"Once it goes public,\\\" Dzurenda said, \\\"just like when you produce and publicize people's names, those companies and people get harassed, or could get harassed, or letters.\\\"\", \"id\": \"polusa_v1_115997943_-1_16_Department of Corrections Director James Dzurenda_24_32\"}\n{\"mention\": \"Obama\", \"polarity\": 1, \"from\": 137, \"to\": 142, \"sentence\": \"What has truly upset the cycle is that Republicans have finally learned -- after a couple of failed extortion attempts -- that President Obama and Democrats are serious about de-weaponizing the debt limit.\", \"id\": \"allsides_4570_1913_7_Obama_137_142\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 0, \"to\": 5, \"sentence\": \"Trump's corrupt media awards: Why some pundits are angling to win\", \"id\": \"polusa_v1_4434271_-1_0_Donald Trump_0_5\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 105, \"to\": 110, \"sentence\": \"- Pollster Frank Luntz, reacting to the president's State of the Union address\\nThe pollster’s praise for Trump did not stop there.\", \"id\": \"polusa_v1_4658361_-1_12_Donald Trump_105_110\"}\n{\"mention\": \"Trump Jr.'s\", \"polarity\": -1, \"from\": 0, \"to\": 11, \"sentence\": \"Trump Jr.'s push to eliminate his 24-hour protection comes at a time when the extended Trump family has faced steady criticism for straining the resources of the Secret Service.\", \"id\": \"polusa_v1_59552612_-1_13_Donald Trump Jr._1_12\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 35, \"to\": 42, \"sentence\": \"The FBI, led at the time by Robert Mueller, required the confidential witness to sign a non-disclosure agreement.\", \"id\": \"allsides_372_150_13_Mueller_35_42\"}\n{\"mention\": \"Abe\", \"polarity\": 1, \"from\": 10, \"to\": 13, \"sentence\": \"Pence and Abe also agreed to deepen cooperation in promoting energy, infrastructure and providing loans to nations in the region.\", \"id\": \"polusa_v1_4431694_-1_3_Abe_11_14\"}\n{\"mention\": \"Pence\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Pence and Abe also agreed to deepen cooperation in promoting energy, infrastructure and providing loans to nations in the region.\", \"id\": \"polusa_v1_4431694_-1_3_Pence_1_6\"}\n{\"mention\": \"Wilson\", \"polarity\": -1, \"from\": 147, \"to\": 153, \"sentence\": \"The report said: \\\"Although there are several individuals who have stated that Brown held his hands up in an unambiguous sign of surrender prior to Wilson shooting him dead, their accounts do not support a prosecution of Wilson.‎ As detailed throughout this report, some of those accounts are inaccurate because they are inconsistent with the physical and forensic evidence; some of those accounts are materially inconsistent with that witness's own prior statements with no explanation, credible or otherwise, as to why those accounts changed over time.\\\"\", \"id\": \"allsides_3510_1449_4_former Ferguson police officer Darren Wilson_147_153\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 6, \"to\": 13, \"sentence\": \"Poll: Clinton's Lead Over Trump Slips After Florida Shooting\", \"id\": \"allsides_2075_845_0_Clinton_6_13\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 38, \"to\": 43, \"sentence\": \"With 63% of Americans disapproving of Trump's response to the Russia investigation, the President's handling of the matter has gotten lower marks than his handling of other issues, including the economy and terrorism\\nMost people in both parties -- 56% -- believe that Special Counsel Robert Mueller's investigation will be impartial and that Trump should not attempt to stop it.\", \"id\": \"polusa_v1_4720617_-1_6_President Donald Trump_38_43\"}\n{\"mention\": \"Japan's Prime Minister Shinzo Abe\", \"polarity\": 0, \"from\": 63, \"to\": 96, \"sentence\": \"At a joint news conference at the Akasaka Palace in Tokyo with Japan's Prime Minister Shinzo Abe, the two leaders spoke of trade and security issues and offered condolences over the mass shooting at a church in Texas on Sunday that killed at least 26 people.\", \"id\": \"polusa_v1_52877448_-1_3_Japan's Prime Minister Shinzo Abe_64_97\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 110, \"to\": 115, \"sentence\": \"A majority of 51 percent of blue collar workers said the United States is headed in the right direction under Trump.\", \"id\": \"polusa_v1_4323252_-1_5_President Trump_110_115\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 50, \"to\": 55, \"sentence\": \"\\\"Now is the moment,\\\" The Telegraph quoted Bannon, Trump’s former strategist and a key player in his 2016 election campaign, as saying.\", \"id\": \"polusa_v1_55270154_-1_33_President Donald Trump_51_56\"}\n{\"mention\": \"Mary Fallin, a Republican\", \"polarity\": 0, \"from\": 0, \"to\": 25, \"sentence\": \"Mary Fallin, a Republican.\", \"id\": \"allsides_3552_1465_5_Mary Fallin, a Republican_0_25\"}\n{\"mention\": \"Cruz\", \"polarity\": 0, \"from\": 0, \"to\": 4, \"sentence\": \"Cruz, however, has vowed to continue his campaign even if he doesn’t win Indiana. .@tedcruz vows to continue his campaign even if he loses Indiana: https://t.co/Ol7bV9niPp pic.twitter.com/4t5YCgW2Xf — MSNBC (@MSNBC) May 2, 2016 This post has been updated.\", \"id\": \"allsides_2239_911_13_Ted Cruz (Texas)_0_4\"}\n{\"mention\": \"the future Hillary Clinton\", \"polarity\": 1, \"from\": 22, \"to\": 48, \"sentence\": \"Her speech introduced the future Hillary Clinton to the national stage.\", \"id\": \"polusa_v1_39078865_-1_6_Hillary Clinton_22_48\"}\n{\"mention\": \"Morsi\", \"polarity\": 1, \"from\": 0, \"to\": 5, \"sentence\": \"Morsi became the first democratically elected president of Egypt in the aftermath of the Islamist Arab Spring protests of 2011 that toppled longtime dictator Hosni Mubarak.\", \"id\": \"polusa_v1_4297466_-1_8_Morsi_1_6\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He reverted to the tough talk he was unable to muster on foreign soil just hours earlier about Mexico paying for the wall.\", \"id\": \"allsides_1850_753_13_Donald Trump_0_2\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 111, \"to\": 116, \"sentence\": \"Though Turnbull declined to confirm the report, he also didn't deny it, apart from rejecting one detail — that Trump had hung up on him.\", \"id\": \"polusa_v1_4374500_-1_15_President Trump_112_117\"}\n{\"mention\": \"Turnbull\", \"polarity\": -1, \"from\": 7, \"to\": 15, \"sentence\": \"Though Turnbull declined to confirm the report, he also didn't deny it, apart from rejecting one detail — that Trump had hung up on him.\", \"id\": \"polusa_v1_4374500_-1_15_Prime Minister Malcolm Turnbull_8_16\"}\n{\"mention\": \"Akin\", \"polarity\": -1, \"from\": 0, \"to\": 4, \"sentence\": \"Akin has since backed off the comment, saying he \\\"misspoke.\\\"\", \"id\": \"allsides_6349_2732_16_Missouri Republican Senate candidate Todd Akin_0_4\"}\n{\"mention\": \"Denbighshire\", \"polarity\": 0, \"from\": 58, \"to\": 70, \"sentence\": \"Shelter Cymru said it had worked with 13 people living on Denbighshire's streets and that the method involved \\\"a single one-night count in November\\\".\", \"id\": \"polusa_v1_18147358_-1_4_Denbighshire_59_71\"}\n{\"mention\": \"Powell\", \"polarity\": 1, \"from\": 59, \"to\": 65, \"sentence\": \"In a brief statement, Press Secretary Sarah Sanders called Powell a \\\"trusted adviser,\\\" claiming she always planned to serve only one year before returning to New York.\", \"id\": \"polusa_v1_4399050_-1_3_Deputy National Security Adviser Dina Powell_60_66\"}\n{\"mention\": \"He\", \"polarity\": 0, \"from\": 0, \"to\": 2, \"sentence\": \"He said when deputies arrived on scene that the gunman was taken into custody “without incident” but declined to elaborate.\", \"id\": \"allsides_1470_592_15_Broward County Sheriff Scott Israel_0_2\"}\n{\"mention\": \"Heller\", \"polarity\": 0, \"from\": 0, \"to\": 6, \"sentence\": \"Heller next to the door to his office when they responded to a call from a burglar-alarm company just after 9 a.m. Sunday morning.\", \"id\": \"polusa_v1_4406155_-1_4_Heller_0_6\"}\n{\"mention\": \"Schumer\", \"polarity\": -1, \"from\": 10, \"to\": 17, \"sentence\": \"He called Schumer’s withdrawal of the offer “a step backward.”\", \"id\": \"allsides_51_20_17_Chuck Schumer_10_17\"}\n{\"mention\": \"President Barack Obama\", \"polarity\": 1, \"from\": 0, \"to\": 22, \"sentence\": \"President Barack Obama spoke out on the crisis in Egypt on Thursday, saying he's \\\"concerned\\\" by recent events.\", \"id\": \"allsides_5141_2174_1_Obama_0_24\"}\n{\"mention\": \"Trump\", \"polarity\": 1, \"from\": 7, \"to\": 12, \"sentence\": \"Donald Trump: ‘Get Smart America!’\", \"id\": \"polusa_v1_4306732_-1_0_President Donald Trump_7_12\"}\n{\"mention\": \"Mueller\", \"polarity\": 0, \"from\": 167, \"to\": 174, \"sentence\": \"Trump blames Sessions for the creation of the special counsel, though even his allies have pointed out that it was Trump’s own actions that precipitated the naming of Mueller.\", \"id\": \"allsides_309_124_8_Mueller_167_174\"}\n{\"mention\": \"he\", \"polarity\": 0, \"from\": 19, \"to\": 21, \"sentence\": \"Earlier this year, he predicted prison sentences for Trump insiders over Mueller’s Russia investigation.\", \"id\": \"polusa_v1_3933900_-1_23_— Richard W. Painter (@RWPUSA) December 13, 2018_20_22\"}\n{\"mention\": \"Trump\", \"polarity\": -1, \"from\": 80, \"to\": 85, \"sentence\": \"Widely mocked for honking the horn of a truck on the White House lawn in March, Trump faced potential ridicule again on Monday as he surrounded himself with vehicles and products from all 50 states to launch his “made in America” week.\", \"id\": \"polusa_v1_39166443_-1_7_Donald Trump_81_86\"}\n{\"mention\": \"Kasich\", \"polarity\": 0, \"from\": 125, \"to\": 131, \"sentence\": \"\\\"Keeping Trump from winning a plurality in Indiana is critical to keeping him under 1,237 bound delegates before Cleveland,\\\" Kasich's campaign said Sunday.\", \"id\": \"allsides_2278_926_30_Kasich_125_131\"}\n{\"mention\": \"Pagliano\", \"polarity\": 0, \"from\": 0, \"to\": 8, \"sentence\": \"Pagliano became a key player during the investigation into Clinton's email practices as secretary of state.\", \"id\": \"polusa_v1_4987298_-1_6_former Clinton IT aide Bryan Pagliano_0_8\"}\n{\"mention\": \"Haspel\", \"polarity\": -1, \"from\": 4, \"to\": 10, \"sentence\": \"Yet Haspel’s defenders are loathe to admit that the practice she participated in was concerning, much less illegal.\", \"id\": \"polusa_v1_39016662_-1_10_Gina Haspel_5_11\"}\n{\"mention\": \"White House press secretary Sarah Huckabee Sanders\", \"polarity\": -1, \"from\": 14, \"to\": 64, \"sentence\": \"A week later, White House press secretary Sarah Huckabee Sanders was asked to leave the Red Hen, a restaurant in Lexington, Virginia.\", \"id\": \"polusa_v1_113886456_-1_18_White House press secretary Sarah Huckabee Sanders_15_65\"}\n{\"mention\": \"Clinton\", \"polarity\": -1, \"from\": 18, \"to\": 25, \"sentence\": \"Surprise: Hillary Clinton Went Around Federal Law, Used Her Personal Email Account For Official Business as Secretary of State\", \"id\": \"allsides_3522_1454_0_Clinton_18_25\"}\n{\"mention\": \"Giovanni\", \"polarity\": 0, \"from\": 27, \"to\": 35, \"sentence\": \"The Kaczmareks agreed, and Giovanni became only the third child in the U.S. to undergo the procedure.\", \"id\": \"polusa_v1_113872189_-1_11_Giovanni_28_36\"}\n{\"mention\": \"Blythe\", \"polarity\": 0, \"from\": 112, \"to\": 118, \"sentence\": \"Four hours east of Los Angeles, in a drought-stricken area of a drought-afflicted state, is a small town called Blythe where alfalfa is king.\", \"id\": \"polusa_v1_38921371_-1_3_Blythe_114_120\"}\n{\"mention\": \"Frieden\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Frieden has launched an investigation as to how the Dallas nurse became infected.\", \"id\": \"allsides_4053_1683_15_Thomas Frieden_0_7\"}\n{\"mention\": \"him\", \"polarity\": -1, \"from\": 60, \"to\": 63, \"sentence\": \"It was a recurring theme: Mr. Romney’s supporters had taken him at his word when he had said repeatedly after 2012 that he would not run again.\", \"id\": \"allsides_3645_1504_32_Jeb Bush_60_63\"}\n{\"mention\": \"Jerry Brown\", \"polarity\": 1, \"from\": 0, \"to\": 11, \"sentence\": \"Jerry Brown seeks to build support for a gas take increase to pay for infrastructure items like road repair.\", \"id\": \"polusa_v1_55025977_-1_69_Jerry Brown's_0_11\"}\n{\"mention\": \"Acosta\", \"polarity\": -1, \"from\": 14, \"to\": 20, \"sentence\": \"In announcing Acosta's suspension, Sanders said, \\\"The fact that CNN is proud of the way their employee behaved is not only disgusting, it is an example of their outrageous disregard for everyone, including young women, who work in this administration.\\\"\", \"id\": \"polusa_v1_59576418_-1_41_CNN correspondent Jim Acosta_15_21\"}\n{\"mention\": \"Cassidy\", \"polarity\": 0, \"from\": 0, \"to\": 7, \"sentence\": \"Cassidy has sought to defend the provision.\", \"id\": \"allsides_569_226_44_Graham-Cassidy_0_7\"}\n{\"mention\": \"Trump\", \"polarity\": 0, \"from\": 0, \"to\": 5, \"sentence\": \"Trump returned to the United States on Tuesday night.\", \"id\": \"polusa_v1_4359001_-1_13_Donald Trump_1_6\"}\n{\"mention\": \"Clinton\", \"polarity\": 1, \"from\": 104, \"to\": 111, \"sentence\": \"A Wall Street Journal/NBC poll taken after the “Access Hollywood” flap—but before Sunday’s debate—gives Clinton a 46-35 lead over Trump.\", \"id\": \"allsides_1732_705_20_Hillary Clinton_104_111\"}\n{\"mention\": \"He\", \"polarity\": -1, \"from\": 0, \"to\": 2, \"sentence\": \"He also deleted and “otherwise did not produce” emails sought by the Special Counsel’s Office and Law Firm A, including the September email between him and Person A in September 2016.\", \"id\": \"polusa_v1_4354039_-1_7_Alex Van Der Zwaan_1_3\"}\n"
  },
  {
    "path": "NewsSentiment/fxlogger.py",
    "content": "import logging\n\nlogger = None\n\n\ndef get_logger():\n    global logger\n\n    if not logger:\n        formatter = logging.Formatter(fmt='%(asctime)s %(levelname)s %(module)s(%(lineno)d):%(funcName)s|: %(message)s',\n                                      datefmt='%H:%M:%S')\n\n        handler = logging.StreamHandler()\n        handler.setFormatter(formatter)\n\n        logger = logging.getLogger(\"NewsSentiment\")\n        if logger.level == logging.NOTSET:\n            logger.setLevel(logging.ERROR)\n\n        if len(logger.handlers) == 0:\n            logger.addHandler(handler)\n\n    return logger\n"
  },
  {
    "path": "NewsSentiment/infer.py",
    "content": "import argparse\n\nimport torch\nimport torch.nn.functional as F\nfrom math import ceil\nfrom jsonlines import jsonlines\nfrom tqdm import tqdm\nfrom typing import overload, Any, List, Dict, Union, Sequence, Tuple, Optional\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\nfrom NewsSentiment.dataset import FXEasyTokenizer\nfrom NewsSentiment.download import Download\nfrom NewsSentiment.fxlogger import get_logger\nfrom NewsSentiment.models.singletarget.grutscsingle import GRUTSCSingle\nfrom NewsSentiment.train import (\n    parse_arguments as parse_arguments_from_train,\n    prepare_and_start_instructor,\n)\n\n\nclass TargetSentimentClassifier:\n    def __init__(\n        self,\n        opts_from_infer=None,\n        single_targets=True,\n        logging_level=\"ERROR\",\n        state_dict=None,\n    ):\n        self.logger = get_logger()\n\n        # reset NUM_CATEGORIES_OF_SELECTED_KNOWLEDGE_SOURCES\n        FXEasyTokenizer.NUM_CATEGORIES_OF_SELECTED_KNOWLEDGE_SOURCES = 0\n\n        # get the default parameters from train.py\n        final_opts = parse_arguments_from_train(\n            override_args=True, overwrite_logging_level=logging_level\n        )\n        # if no arguments have been passed, get the defaults of infer.py (and since\n        # override_args=True, not the arguments passed by the console (in args) will be\n        # used but just the defaults defined in parse_arguments\n        if not opts_from_infer:\n            opts_from_infer = parse_arguments(override_args=True)\n\n        for key, val in vars(opts_from_infer).items():\n            if val is not None:\n                previous_val = getattr(final_opts, key)\n                self.logger.info(\"overwriting: %s=%s to %s\", key, previous_val, val)\n                setattr(final_opts, key, val)\n\n        # set custom variables\n        final_opts.single_targets = single_targets\n        final_opts.multi_targets = not single_targets\n        if state_dict:\n            final_opts.state_dict = state_dict\n\n        # set training_mode to False so that we get the Instructor object\n        final_opts.training_mode = False\n\n        # prepare and initialize instructor\n        instructor = prepare_and_start_instructor(final_opts)\n\n        # get stuff that we need from the instructor\n        self.model = instructor.own_model\n        self.tokenizer = instructor.own_tokenizer\n        self.opt = instructor.opt\n        self.instructor = instructor\n        self.polarities_inverse = SentimentClasses.get_polarity_associations_inverse()\n\n        # set model to evaluation mode (disable gradient / learning)\n        self.model.eval()\n        torch.autograd.set_grad_enabled(False)\n\n    def infer_from_text(self, left, target, right):\n        \"\"\"\n        Calculates the targeted mention of the sentence defined by left + target + right.\n        :param left: The text from the beginning of the sentence to the mention of the\n        target (will be empty if the sentence starts with the mention of the target).\n        Make sure to include a space if there is one between the left phrase and the\n        target mention, e.g., \"I like Peter.\" -> left=\"I like \", target=\"Peter\", right=\".\".\n        :param target: The mention of the target.\n        :param right: The text from the end of the target to the end of the sentence.\n        Make sure to include a space if there is one between the target and the next word\n        of the sentence.\n        :return:\n        \"\"\"\n        return self.infer(text_left=left, target_mention=target, text_right=right)\n\n    @overload\n    def infer(\n        self,\n        text_left: str = ...,\n        target_mention: str = ...,\n        text_right: str = ...,\n        text: None = None,\n        target_mention_from: None = None,\n        target_mention_to: None = None,\n        targets: None = None,\n        batch_size: int = ...,\n        disable_tqdm: bool = ...,\n    ) -> Tuple[Dict[str, Any], ...]:\n        ...\n\n    @overload\n    def infer(\n        self,\n        text_left: None = None,\n        target_mention: None = None,\n        text_right: None = None,\n        text: str = ...,\n        target_mention_from: int = ...,\n        target_mention_to: int = ...,\n        targets: None = None,\n        batch_size: int = ...,\n        disable_tqdm: bool = ...,\n    ) -> Tuple[Dict[str, Any], ...]:\n        ...\n\n    @overload\n    def infer(\n        self,\n        text_left: None = None,\n        target_mention: None = None,\n        text_right: None = None,\n        text: None = None,\n        target_mention_from: None = None,\n        target_mention_to: None = None,\n        targets: Sequence[Union[Tuple[str, str, str], Tuple[str, int, int]]] = ...,\n        batch_size: int = ...,\n        disable_tqdm: bool = ...,\n    ) -> List[Tuple[Dict[str, Any], ...]]:\n        ...\n\n    def infer(\n        self,\n        text_left: Optional[str] = None,\n        target_mention: Optional[str] = None,\n        text_right: Optional[str] = None,\n        text: Optional[str] = None,\n        target_mention_from: Optional[int] = None,\n        target_mention_to: Optional[int] = None,\n        targets: Optional[\n            Sequence[Union[Tuple[str, str, str], Tuple[str, int, int]]]\n        ] = None,\n        batch_size: int = 1,\n        disable_tqdm: bool = False,\n    ) -> Union[Tuple[Dict[str, Any], ...], List[Tuple[Dict[str, Any], ...]]]:\n        \"\"\"Computes sentiment for one or more targets. Additionally splits multiple\n        targets into batches of batch_size and processes them in a vectorized fashion.\n\n        Note that the text before and after the target should end with a space\n        (or comma, etc.)), or begin with a space, respectively.\n\n        Args:\n            text_left (str | None, optional): Text before the target mention.\n                Defaults to None.\n            target_mention (str | None, optional): Target mention. Defaults to None.\n            text_right (str | None, optional): Text after the target mention.\n                Defaults to None.\n            text (str | None, optional): Text containing the target mention.\n                Defaults to None.\n            target_mention_from (str | None, optional): Start index of the\n                target mention. Defaults to None.\n            target_mention_to (str | None, optional): End index of the target mention.\n                Defaults to None.\n            targets (Sequence[Tuple[str, str, str] | Tuple[str, int, int]] | None,\n                optional): Tuples containing (text_left,target_mention,text_right)\n                or (text,target_mention_from,target_mention_to) for multiple targets\n                (mixed style is possible). Defaults to None.\n            batch_size (int, optional): Preferred size of each batch if using multiple\n                targets. Defaults to 1.\n            disable_tqdm (bool, optional): Disables the tqdm progress bar that shows\n                progress in batch processing. Defaults to False.\n\n        Returns:\n            Tuple[Dict[str, Any], ...] | List[Tuple[Dict[str, Any], ...]: Tuple (or\n                list of tuples for multiple targets with order preserved) containing\n                class probabilities as dictionaries with keys \"class_id\", \"class_label\"\n                and \"class_prob\".\n        \"\"\"\n        component_base = (text_left, target_mention, text_right)\n        is_component_based = all(isinstance(i, str) for i in component_base)\n\n        index_base = (text, target_mention_from, target_mention_to)\n        is_index_based = all(\n            isinstance(arg, typ) for arg, typ in zip(index_base, (str, int, int))\n        )\n\n        is_targets_based = targets is not None\n\n        # verify input\n        assert (\n            sum((is_component_based, is_index_based, is_targets_based)) == 1\n        ), \"\"\"Wrong input types or too many inputs!\n            Must be either one single or multiple component or index based targets.\"\"\"\n\n        targets = (\n            (component_base if is_component_based else index_base,)\n            if not is_targets_based\n            else targets\n        )\n\n        num_targets = len(targets)\n        num_batches = ceil(num_targets / batch_size)\n\n        out = []\n\n        for batch_start, batch_end in tqdm(\n            zip(\n                range(0, num_targets, batch_size),\n                (*range(batch_size, num_targets, batch_size), None),\n            ),\n            total=num_batches,\n            desc=\"Processing batches\",\n            unit=\"batch\",\n            disable=disable_tqdm,\n        ):\n            out.extend(self.batch_infer(targets[batch_start:batch_end]))\n\n        return out[0] if not is_targets_based else out\n\n    def batch_infer(\n        self,\n        targets: Sequence[Union[Tuple[str, str, str], Tuple[str, int, int]]],\n    ) -> List[Tuple[Dict[str, Any], ...]]:\n        \"\"\"Computes sentiment for a batch of targets.\n        Targets are tuples of text before target, target mention, and text after target.\n\n        Args:\n            targets (Sequence[Tuple[str,str,str] | Tuple[str,int,int]]): Batch of\n                targets to compute sentiment for. Tuples contain\n                (text before, target mention, text after) or\n                (text,target mention start index, target mention end index).\n                Texts before and after the target mention should end with a space\n                (or comma, etc.)), or begin with a space, respectively.\n\n        Returns:\n            List[Tuple[Dict[str,Any], ...]]: List of target classification tuples,\n                containing class probabilities as dictionaries with keys\n                \"class_id\", \"class_label\" and \"class_prob\".\n                The order of tuples matches the order of input targets.\n        \"\"\"\n        targets_prepared = []\n\n        for target in targets:\n            assert (\n                len(target) == 3\n            ), f\"{target} is missing {3-len(target)} component(s).\"\n\n            if all(isinstance(component, str) for component in target):\n                text_left, target_mention, text_right = target\n            elif all(\n                isinstance(component, typ)\n                for component, typ in zip(target, (str, int, int))\n            ):\n                text = target[0]\n                target_mention_from = target[1]\n                target_mention_to = target[2]\n                text_left = text[:target_mention_from]\n                target_mention = text[target_mention_from:target_mention_to]\n                text_right = text[target_mention_to:]\n            else:\n                raise TypeError(f\"Wrong input types in {target}.\")\n\n            # assert text_left.endswith(' ') # we cannot handle commas, if we have this\n            # check\n            assert not any(\n                (target_mention.startswith(\" \"), target_mention.endswith(\" \"))\n            ), f\"target_mention={target_mention}; text={text}\"\n            # assert text_right.startswith(' ')\n\n            targets_prepared.append(\n                (\n                    FXEasyTokenizer.prepare_left_segment(text_left),\n                    FXEasyTokenizer.prepare_target_mention(target_mention),\n                    FXEasyTokenizer.prepare_right_segment(text_right),\n                )\n            )\n\n        indexed_examples = self.tokenizer.batch_create_model_input_seqs(\n            targets=targets_prepared,\n            coreferential_targets_for_target_mask=None,\n        )\n\n        inputs = self.instructor.select_inputs(indexed_examples, is_single_item=False)\n\n        outputs = self.model(inputs)\n\n        class_probabilities_per_target = F.softmax(outputs, dim=-1).cpu().tolist()\n\n        return [\n            tuple(\n                sorted(\n                    (\n                        {\n                            \"class_id\": class_id,\n                            \"class_label\": self.polarities_inverse[class_id],\n                            \"class_prob\": class_prob,\n                        }\n                        for class_id, class_prob in enumerate(class_probabilities)\n                    ),\n                    key=lambda x: x[\"class_prob\"],\n                    reverse=True,\n                )\n            )\n            for class_probabilities in class_probabilities_per_target\n        ]\n\n    def get_info_for_label(self, classification_result, label):\n        for r in classification_result:\n            if r[\"class_label\"] == label:\n                return r\n        raise ValueError(label)\n\n\ndef parse_arguments(override_args=False):\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--own_model_name\", default=\"grutsc\", type=str)\n    parser.add_argument(\n        \"--pretrained_model_name\",\n        type=str,\n        help=\"has to be placed in folder pretrained_models\",\n    )\n    parser.add_argument(\"--default_lm\", default=\"roberta-base\", type=str)\n    parser.add_argument(\n        \"--state_dict\", type=str, default=Download.model_path(GRUTSCSingle)\n    )\n    parser.add_argument(\n        \"--knowledgesources\", default=\"nrc_emotions mpqa_subjectivity bingliu_opinion\"\n    )\n    parser.add_argument(\n        \"--device\",\n        default=None,\n        type=str,\n        help=\"e.g., cuda:0; if None: any CUDA device will be used if available, else \"\n        \"CPU\",\n    )\n    parser.add_argument(\n        \"--logging\",\n        type=str,\n        default=\"ERROR\",\n    )\n\n    # if own_args == None -> parse_args will use sys.argv\n    # if own_args == [] -> parse_args will use this empty list instead\n    own_args = None\n    if override_args:\n        own_args = []\n\n    # create arguments\n    opt = parser.parse_args(args=own_args)\n\n    return opt\n"
  },
  {
    "path": "NewsSentiment/inferrest.py",
    "content": "from flask import Flask, request\n\nfrom NewsSentiment import TargetSentimentClassifier\n\napp = Flask(__name__)\n\ntsc = TargetSentimentClassifier()\n\n\n@app.route(\"/infer\", methods=[\"POST\"])\ndef index():\n    text_left = request.form[\"left\"]\n    target_mention = request.form[\"target\"]\n    text_right = request.form[\"right\"]\n    return {\n        \"result\": tsc.infer(\n            text_left=text_left, target_mention=target_mention, text_right=text_right\n        )\n    }\n\n\ndef start_rest_server(port=13273):\n    print(\"starting server...\")\n    app.run(host=\"0.0.0.0\", port=port)\n    print(\"done\")\n\n\nif __name__ == \"__main__\":\n    start_rest_server()\n"
  },
  {
    "path": "NewsSentiment/knowledge/__init__.py",
    "content": ""
  },
  {
    "path": "NewsSentiment/knowledge/bingliuopinion/bingliuopinion.py",
    "content": "import torch\n\nfrom NewsSentiment.diskdict import DiskDict\nfrom NewsSentiment.knowledge.bingliuopinion.converter import PATH_DICT_BING_LIU_OPINION_POLARITY, POLARITY2INDEX\nfrom NewsSentiment.knowledge.knowledgeutils import find_key_original_or_lc\n\n__ddict_emolex = DiskDict(PATH_DICT_BING_LIU_OPINION_POLARITY)\n__ddict_emolex_keys_lower = {k.lower(): v for k, v in __ddict_emolex.items()}\n__num_emotions = 2\nassert len(__ddict_emolex) == 6726\nassert len(POLARITY2INDEX) == __num_emotions\n\n\ndef get_num_bingliu_polarities():\n    return __num_emotions\n\n\ndef get_bingliu_polarities_as_tensor(term: str):\n    emotions = find_key_original_or_lc(__ddict_emolex, __ddict_emolex_keys_lower, term)\n    tensor_emotions = torch.zeros(__num_emotions, dtype=torch.long)\n    for emotion_index in emotions:\n        tensor_emotions[emotion_index] = 1\n    return tensor_emotions\n"
  },
  {
    "path": "NewsSentiment/knowledge/bingliuopinion/converter.py",
    "content": "from collections import defaultdict, Counter\nfrom pathlib import Path\nimport csv\nimport os\n\nfrom tqdm import tqdm\n\nfrom NewsSentiment.fxlogger import get_logger\nfrom NewsSentiment.diskdict import DiskDict\n\nPOLARITY2INDEX = {\n    \"positive\": 1,\n    \"negative\": 0,\n}\nTHIS_DIR = Path(os.path.dirname(os.path.realpath(__file__)))\nPATH_DICT_BING_LIU_OPINION_POLARITY = THIS_DIR / \"opinion_polarity.ddict\"\n\nlogger = get_logger()\n\n\ndef convert_single_txt_to_dict(path: Path):\n    terms = set()\n    with open(path, \"r\") as file:\n        line_count = 0\n        for line in file:\n            if line_count > 29:\n                terms.add(line.strip())\n            line_count += 1\n    return terms\n\n\ndef convert_txt_to_dict():\n    path_pos = THIS_DIR / \"positive-words.txt\"\n    path_neg = THIS_DIR / \"negative-words.txt\"\n\n    term2polarity = defaultdict(set)\n    polarity_counter = Counter()\n\n    positive_terms = convert_single_txt_to_dict(path_pos)\n    negative_terms = convert_single_txt_to_dict(path_neg)\n    all_terms = positive_terms.union(negative_terms)\n\n    for term in all_terms:\n        if term in positive_terms:\n            term2polarity[term].add(POLARITY2INDEX[\"positive\"])\n            polarity_counter[\"positive\"] += 1\n        if term in negative_terms:\n            term2polarity[term].add(POLARITY2INDEX[\"negative\"])\n            polarity_counter[\"negative\"] += 1\n\n    logger.info(\"read %s terms\", len(term2polarity))\n    logger.info(\"polarity count:\\n%s\", polarity_counter.most_common())\n\n    logger.info(\"saving to %s...\", PATH_DICT_BING_LIU_OPINION_POLARITY)\n    ddict_emolex = DiskDict(PATH_DICT_BING_LIU_OPINION_POLARITY)\n    ddict_emolex.update(term2polarity)\n    ddict_emolex.sync_to_disk()\n    logger.info(\"done\")\n\n\nif __name__ == \"__main__\":\n    convert_txt_to_dict()\n"
  },
  {
    "path": "NewsSentiment/knowledge/bingliuopinion/license.txt",
    "content": ";;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;\n;\n; Both files (negative- and positive-words.txt) and the papers can all be downloaded from\n;    http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html\n;\n; If you use this list, please cite the following paper:\n;\n;   Minqing Hu and Bing Liu. \"Mining and Summarizing Customer Reviews.\"\n;       Proceedings of the ACM SIGKDD International Conference on Knowledge\n;       Discovery and Data Mining (KDD-2004), Aug 22-25, 2004, Seattle,\n;       Washington, USA,\n; Notes:\n;    1. The appearance of an opinion word in a sentence does not necessarily\n;       mean that the sentence expresses a positive or negative opinion.\n;       See the paper below:\n;\n;       Bing Liu. \"Sentiment Analysis and Subjectivity.\" An chapter in\n;          Handbook of Natural Language Processing, Second Edition,\n;          (editors: N. Indurkhya and F. J. Damerau), 2010.\n;\n;    2. You will notice many misspelled words in the list. They are not\n;       mistakes. They are included as these misspelled words appear\n;       frequently in social media content.\n;\n;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;\n"
  },
  {
    "path": "NewsSentiment/knowledge/bingliuopinion/negative-words.txt",
    "content": "2-faced\n2-faces\nabnormal\nabolish\nabominable\nabominably\nabominate\nabomination\nabort\naborted\naborts\nabrade\nabrasive\nabrupt\nabruptly\nabscond\nabsence\nabsent-minded\nabsentee\nabsurd\nabsurdity\nabsurdly\nabsurdness\nabuse\nabused\nabuses\nabusive\nabysmal\nabysmally\nabyss\naccidental\naccost\naccursed\naccusation\naccusations\naccuse\naccuses\naccusing\naccusingly\nacerbate\nacerbic\nacerbically\nache\nached\naches\nachey\naching\nacrid\nacridly\nacridness\nacrimonious\nacrimoniously\nacrimony\nadamant\nadamantly\naddict\naddicted\naddicting\naddicts\nadmonish\nadmonisher\nadmonishingly\nadmonishment\nadmonition\nadulterate\nadulterated\nadulteration\nadulterier\nadversarial\nadversary\nadverse\nadversity\nafflict\naffliction\nafflictive\naffront\nafraid\naggravate\naggravating\naggravation\naggression\naggressive\naggressiveness\naggressor\naggrieve\naggrieved\naggrivation\naghast\nagonies\nagonize\nagonizing\nagonizingly\nagony\naground\nail\nailing\nailment\naimless\nalarm\nalarmed\nalarming\nalarmingly\nalienate\nalienated\nalienation\nallegation\nallegations\nallege\nallergic\nallergies\nallergy\naloof\naltercation\nambiguity\nambiguous\nambivalence\nambivalent\nambush\namiss\namputate\nanarchism\nanarchist\nanarchistic\nanarchy\nanemic\nanger\nangrily\nangriness\nangry\nanguish\nanimosity\nannihilate\nannihilation\nannoy\nannoyance\nannoyances\nannoyed\nannoying\nannoyingly\nannoys\nanomalous\nanomaly\nantagonism\nantagonist\nantagonistic\nantagonize\nanti-\nanti-american\nanti-israeli\nanti-occupation\nanti-proliferation\nanti-semites\nanti-social\nanti-us\nanti-white\nantipathy\nantiquated\nantithetical\nanxieties\nanxiety\nanxious\nanxiously\nanxiousness\napathetic\napathetically\napathy\napocalypse\napocalyptic\napologist\napologists\nappal\nappall\nappalled\nappalling\nappallingly\napprehension\napprehensions\napprehensive\napprehensively\narbitrary\narcane\narchaic\narduous\narduously\nargumentative\narrogance\narrogant\narrogantly\nashamed\nasinine\nasininely\nasinininity\naskance\nasperse\naspersion\naspersions\nassail\nassassin\nassassinate\nassault\nassult\nastray\nasunder\natrocious\natrocities\natrocity\natrophy\nattack\nattacks\naudacious\naudaciously\naudaciousness\naudacity\naudiciously\naustere\nauthoritarian\nautocrat\nautocratic\navalanche\navarice\navaricious\navariciously\navenge\naverse\naversion\naweful\nawful\nawfully\nawfulness\nawkward\nawkwardness\nax\nbabble\nback-logged\nback-wood\nback-woods\nbackache\nbackaches\nbackaching\nbackbite\nbackbiting\nbackward\nbackwardness\nbackwood\nbackwoods\nbad\nbadly\nbaffle\nbaffled\nbafflement\nbaffling\nbait\nbalk\nbanal\nbanalize\nbane\nbanish\nbanishment\nbankrupt\nbarbarian\nbarbaric\nbarbarically\nbarbarity\nbarbarous\nbarbarously\nbarren\nbaseless\nbash\nbashed\nbashful\nbashing\nbastard\nbastards\nbattered\nbattering\nbatty\nbearish\nbeastly\nbedlam\nbedlamite\nbefoul\nbeg\nbeggar\nbeggarly\nbegging\nbeguile\nbelabor\nbelated\nbeleaguer\nbelie\nbelittle\nbelittled\nbelittling\nbellicose\nbelligerence\nbelligerent\nbelligerently\nbemoan\nbemoaning\nbemused\nbent\nberate\nbereave\nbereavement\nbereft\nberserk\nbeseech\nbeset\nbesiege\nbesmirch\nbestial\nbetray\nbetrayal\nbetrayals\nbetrayer\nbetraying\nbetrays\nbewail\nbeware\nbewilder\nbewildered\nbewildering\nbewilderingly\nbewilderment\nbewitch\nbias\nbiased\nbiases\nbicker\nbickering\nbid-rigging\nbigotries\nbigotry\nbitch\nbitchy\nbiting\nbitingly\nbitter\nbitterly\nbitterness\nbizarre\nblab\nblabber\nblackmail\nblah\nblame\nblameworthy\nbland\nblandish\nblaspheme\nblasphemous\nblasphemy\nblasted\nblatant\nblatantly\nblather\nbleak\nbleakly\nbleakness\nbleed\nbleeding\nbleeds\nblemish\nblind\nblinding\nblindingly\nblindside\nblister\nblistering\nbloated\nblockage\nblockhead\nbloodshed\nbloodthirsty\nbloody\nblotchy\nblow\nblunder\nblundering\nblunders\nblunt\nblur\nbluring\nblurred\nblurring\nblurry\nblurs\nblurt\nboastful\nboggle\nbogus\nboil\nboiling\nboisterous\nbomb\nbombard\nbombardment\nbombastic\nbondage\nbonkers\nbore\nbored\nboredom\nbores\nboring\nbotch\nbother\nbothered\nbothering\nbothers\nbothersome\nbowdlerize\nboycott\nbraggart\nbragger\nbrainless\nbrainwash\nbrash\nbrashly\nbrashness\nbrat\nbravado\nbrazen\nbrazenly\nbrazenness\nbreach\nbreak\nbreak-up\nbreak-ups\nbreakdown\nbreaking\nbreaks\nbreakup\nbreakups\nbribery\nbrimstone\nbristle\nbrittle\nbroke\nbroken\nbroken-hearted\nbrood\nbrowbeat\nbruise\nbruised\nbruises\nbruising\nbrusque\nbrutal\nbrutalising\nbrutalities\nbrutality\nbrutalize\nbrutalizing\nbrutally\nbrute\nbrutish\nbs\nbuckle\nbug\nbugging\nbuggy\nbugs\nbulkier\nbulkiness\nbulky\nbulkyness\nbull****\nbull----\nbullies\nbullshit\nbullshyt\nbully\nbullying\nbullyingly\nbum\nbump\nbumped\nbumping\nbumpping\nbumps\nbumpy\nbungle\nbungler\nbungling\nbunk\nburden\nburdensome\nburdensomely\nburn\nburned\nburning\nburns\nbust\nbusts\nbusybody\nbutcher\nbutchery\nbuzzing\nbyzantine\ncackle\ncalamities\ncalamitous\ncalamitously\ncalamity\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ected\ninfection\ninfections\ninferior\ninferiority\ninfernal\ninfest\ninfested\ninfidel\ninfidels\ninfiltrator\ninfiltrators\ninfirm\ninflame\ninflammation\ninflammatory\ninflammed\ninflated\ninflationary\ninflexible\ninflict\ninfraction\ninfringe\ninfringement\ninfringements\ninfuriate\ninfuriated\ninfuriating\ninfuriatingly\ninglorious\ningrate\ningratitude\ninhibit\ninhibition\ninhospitable\ninhospitality\ninhuman\ninhumane\ninhumanity\ninimical\ninimically\niniquitous\niniquity\ninjudicious\ninjure\ninjurious\ninjury\ninjustice\ninjustices\ninnuendo\ninoperable\ninopportune\ninordinate\ninordinately\ninsane\ninsanely\ninsanity\ninsatiable\ninsecure\ninsecurity\ninsensible\ninsensitive\ninsensitively\ninsensitivity\ninsidious\ninsidiously\ninsignificance\ninsignificant\ninsignificantly\ninsincere\ninsincerely\ninsincerity\ninsinuate\ninsinuating\ninsinuation\ninsociable\ninsolence\ninsolent\ninsolently\ninsolvent\ninsouciance\ninstability\ninstable\ninstigate\ninstigator\ninstigators\ninsubordinate\ninsubstantial\ninsubstantially\ninsufferable\ninsufferably\ninsufficiency\ninsufficient\ninsufficiently\ninsular\ninsult\ninsulted\ninsulting\ninsultingly\ninsults\ninsupportable\ninsupportably\ninsurmountable\ninsurmountably\ninsurrection\nintefere\ninteferes\nintense\ninterfere\ninterference\ninterferes\nintermittent\ninterrupt\ninterruption\ninterruptions\nintimidate\nintimidating\nintimidatingly\nintimidation\nintolerable\nintolerablely\nintolerance\nintoxicate\nintractable\nintransigence\nintransigent\nintrude\nintrusion\nintrusive\ninundate\ninundated\ninvader\ninvalid\ninvalidate\ninvalidity\ninvasive\ninvective\ninveigle\ninvidious\ninvidiously\ninvidiousness\ninvisible\ninvoluntarily\ninvoluntary\nirascible\nirate\nirately\nire\nirk\nirked\nirking\nirks\nirksome\nirksomely\nirksomeness\nirksomenesses\nironic\nironical\nironically\nironies\nirony\nirragularity\nirrational\nirrationalities\nirrationality\nirrationally\nirrationals\nirreconcilable\nirrecoverable\nirrecoverableness\nirrecoverablenesses\nirrecoverably\nirredeemable\nirredeemably\nirreformable\nirregular\nirregularity\nirrelevance\nirrelevant\nirreparable\nirreplacible\nirrepressible\nirresolute\nirresolvable\nirresponsible\nirresponsibly\nirretating\nirretrievable\nirreversible\nirritable\nirritably\nirritant\nirritate\nirritated\nirritating\nirritation\nirritations\nisolate\nisolated\nisolation\nissue\nissues\nitch\nitching\nitchy\njabber\njaded\njagged\njam\njarring\njaundiced\njealous\njealously\njealousness\njealousy\njeer\njeering\njeeringly\njeers\njeopardize\njeopardy\njerk\njerky\njitter\njitters\njittery\njob-killing\njobless\njoke\njoker\njolt\njudder\njuddering\njudders\njumpy\njunk\njunky\njunkyard\njutter\njutters\nkaput\nkill\nkilled\nkiller\nkilling\nkilljoy\nkills\nknave\nknife\nknock\nknotted\nkook\nkooky\nlack\nlackadaisical\nlacked\nlackey\nlackeys\nlacking\nlackluster\nlacks\nlaconic\nlag\nlagged\nlagging\nlaggy\nlags\nlaid-off\nlambast\nlambaste\nlame\nlame-duck\nlament\nlamentable\nlamentably\nlanguid\nlanguish\nlanguor\nlanguorous\nlanguorously\nlanky\nlapse\nlapsed\nlapses\nlascivious\nlast-ditch\nlatency\nlaughable\nlaughably\nlaughingstock\nlawbreaker\nlawbreaking\nlawless\nlawlessness\nlayoff\nlayoff-happy\nlazy\nleak\nleakage\nleakages\nleaking\nleaks\nleaky\nlech\nlecher\nlecherous\nlechery\nleech\nleer\nleery\nleft-leaning\nlemon\nlengthy\nless-developed\nlesser-known\nletch\nlethal\nlethargic\nlethargy\nlewd\nlewdly\nlewdness\nliability\nliable\nliar\nliars\nlicentious\nlicentiously\nlicentiousness\nlie\nlied\nlier\nlies\nlife-threatening\nlifeless\nlimit\nlimitation\nlimitations\nlimited\nlimits\nlimp\nlistless\nlitigious\nlittle-known\nlivid\nlividly\nloath\nloathe\nloathing\nloathly\nloathsome\nloathsomely\nlone\nloneliness\nlonely\nloner\nlonesome\nlong-time\nlong-winded\nlonging\nlongingly\nloophole\nloopholes\nloose\nloot\nlorn\nlose\nloser\nlosers\nloses\nlosing\nloss\nlosses\nlost\nloud\nlouder\nlousy\nloveless\nlovelorn\nlow-rated\nlowly\nludicrous\nludicrously\nlugubrious\nlukewarm\nlull\nlumpy\nlunatic\nlunaticism\nlurch\nlure\nlurid\nlurk\nlurking\nlying\nmacabre\nmad\nmadden\nmaddening\nmaddeningly\nmadder\nmadly\nmadman\nmadness\nmaladjusted\nmaladjustment\nmalady\nmalaise\nmalcontent\nmalcontented\nmaledict\nmalevolence\nmalevolent\nmalevolently\nmalice\nmalicious\nmaliciously\nmaliciousness\nmalign\nmalignant\nmalodorous\nmaltreatment\nmangle\nmangled\nmangles\nmangling\nmania\nmaniac\nmaniacal\nmanic\nmanipulate\nmanipulation\nmanipulative\nmanipulators\nmar\nmarginal\nmarginally\nmartyrdom\nmartyrdom-seeking\nmashed\nmassacre\nmassacres\nmatte\nmawkish\nmawkishly\nmawkishness\nmeager\nmeaningless\nmeanness\nmeasly\nmeddle\nmeddlesome\nmediocre\nmediocrity\nmelancholy\nmelodramatic\nmelodramatically\nmeltdown\nmenace\nmenacing\nmenacingly\nmendacious\nmendacity\nmenial\nmerciless\nmercilessly\nmess\nmessed\nmesses\nmessing\nmessy\nmidget\nmiff\nmilitancy\nmindless\nmindlessly\nmirage\nmire\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  },
  {
    "path": "NewsSentiment/knowledge/bingliuopinion/positive-words.txt",
    "content": "a+\nabound\nabounds\nabundance\nabundant\naccessable\naccessible\nacclaim\nacclaimed\nacclamation\naccolade\naccolades\naccommodative\naccomodative\naccomplish\naccomplished\naccomplishment\naccomplishments\naccurate\naccurately\nachievable\nachievement\nachievements\nachievible\nacumen\nadaptable\nadaptive\nadequate\nadjustable\nadmirable\nadmirably\nadmiration\nadmire\nadmirer\nadmiring\nadmiringly\nadorable\nadore\nadored\nadorer\nadoring\nadoringly\nadroit\nadroitly\nadulate\nadulation\nadulatory\nadvanced\nadvantage\nadvantageous\nadvantageously\nadvantages\nadventuresome\nadventurous\nadvocate\nadvocated\nadvocates\naffability\naffable\naffably\naffectation\naffection\naffectionate\naffinity\naffirm\naffirmation\naffirmative\naffluence\naffluent\nafford\naffordable\naffordably\nafordable\nagile\nagilely\nagility\nagreeable\nagreeableness\nagreeably\nall-around\nalluring\nalluringly\naltruistic\naltruistically\namaze\namazed\namazement\namazes\namazing\namazingly\nambitious\nambitiously\nameliorate\namenable\namenity\namiability\namiabily\namiable\namicability\namicable\namicably\namity\nample\namply\namuse\namusing\namusingly\nangel\nangelic\napotheosis\nappeal\nappealing\napplaud\nappreciable\nappreciate\nappreciated\nappreciates\nappreciative\nappreciatively\nappropriate\napproval\napprove\nardent\nardently\nardor\narticulate\naspiration\naspirations\naspire\nassurance\nassurances\nassure\nassuredly\nassuring\nastonish\nastonished\nastonishing\nastonishingly\nastonishment\nastound\nastounded\nastounding\nastoundingly\nastutely\nattentive\nattraction\nattractive\nattractively\nattune\naudible\naudibly\nauspicious\nauthentic\nauthoritative\nautonomous\navailable\naver\navid\navidly\naward\nawarded\nawards\nawe\nawed\nawesome\nawesomely\nawesomeness\nawestruck\nawsome\nbackbone\nbalanced\nbargain\nbeauteous\nbeautiful\nbeautifullly\nbeautifully\nbeautify\nbeauty\nbeckon\nbeckoned\nbeckoning\nbeckons\nbelievable\nbelieveable\nbeloved\nbenefactor\nbeneficent\nbeneficial\nbeneficially\nbeneficiary\nbenefit\nbenefits\nbenevolence\nbenevolent\nbenifits\nbest\nbest-known\nbest-performing\nbest-selling\nbetter\nbetter-known\nbetter-than-expected\nbeutifully\nblameless\nbless\nblessing\nbliss\nblissful\nblissfully\nblithe\nblockbuster\nbloom\nblossom\nbolster\nbonny\nbonus\nbonuses\nboom\nbooming\nboost\nboundless\nbountiful\nbrainiest\nbrainy\nbrand-new\nbrave\nbravery\nbravo\nbreakthrough\nbreakthroughs\nbreathlessness\nbreathtaking\nbreathtakingly\nbreeze\nbright\nbrighten\nbrighter\nbrightest\nbrilliance\nbrilliances\nbrilliant\nbrilliantly\nbrisk\nbrotherly\nbullish\nbuoyant\ncajole\ncalm\ncalming\ncalmness\ncapability\ncapable\ncapably\ncaptivate\ncaptivating\ncarefree\ncashback\ncashbacks\ncatchy\ncelebrate\ncelebrated\ncelebration\ncelebratory\nchamp\nchampion\ncharisma\ncharismatic\ncharitable\ncharm\ncharming\ncharmingly\nchaste\ncheaper\ncheapest\ncheer\ncheerful\ncheery\ncherish\ncherished\ncherub\nchic\nchivalrous\nchivalry\ncivility\ncivilize\nclarity\nclassic\nclassy\nclean\ncleaner\ncleanest\ncleanliness\ncleanly\nclear\nclear-cut\ncleared\nclearer\nclearly\nclears\nclever\ncleverly\ncohere\ncoherence\ncoherent\ncohesive\ncolorful\ncomely\ncomfort\ncomfortable\ncomfortably\ncomforting\ncomfy\ncommend\ncommendable\ncommendably\ncommitment\ncommodious\ncompact\ncompactly\ncompassion\ncompassionate\ncompatible\ncompetitive\ncomplement\ncomplementary\ncomplemented\ncomplements\ncompliant\ncompliment\ncomplimentary\ncomprehensive\nconciliate\nconciliatory\nconcise\nconfidence\nconfident\ncongenial\ncongratulate\ncongratulation\ncongratulations\ncongratulatory\nconscientious\nconsiderate\nconsistent\nconsistently\nconstructive\nconsummate\ncontentment\ncontinuity\ncontrasty\ncontribution\nconvenience\nconvenient\nconveniently\nconvience\nconvienient\nconvient\nconvincing\nconvincingly\ncool\ncoolest\ncooperative\ncooperatively\ncornerstone\ncorrect\ncorrectly\ncost-effective\ncost-saving\ncounter-attack\ncounter-attacks\ncourage\ncourageous\ncourageously\ncourageousness\ncourteous\ncourtly\ncovenant\ncozy\ncreative\ncredence\ncredible\ncrisp\ncrisper\ncure\ncure-all\ncushy\ncute\ncuteness\ndanke\ndanken\ndaring\ndaringly\ndarling\ndashing\ndauntless\ndawn\ndazzle\ndazzled\ndazzling\ndead-cheap\ndead-on\ndecency\ndecent\ndecisive\ndecisiveness\ndedicated\ndefeat\ndefeated\ndefeating\ndefeats\ndefender\ndeference\ndeft\ndeginified\ndelectable\ndelicacy\ndelicate\ndelicious\ndelight\ndelighted\ndelightful\ndelightfully\ndelightfulness\ndependable\ndependably\ndeservedly\ndeserving\ndesirable\ndesiring\ndesirous\ndestiny\ndetachable\ndevout\ndexterous\ndexterously\ndextrous\ndignified\ndignify\ndignity\ndiligence\ndiligent\ndiligently\ndiplomatic\ndirt-cheap\ndistinction\ndistinctive\ndistinguished\ndiversified\ndivine\ndivinely\ndominate\ndominated\ndominates\ndote\ndotingly\ndoubtless\ndreamland\ndumbfounded\ndumbfounding\ndummy-proof\ndurable\ndynamic\neager\neagerly\neagerness\nearnest\nearnestly\nearnestness\nease\neased\neases\neasier\neasiest\neasiness\neasing\neasy\neasy-to-use\neasygoing\nebullience\nebullient\nebulliently\necenomical\neconomical\necstasies\necstasy\necstatic\necstatically\nedify\neducated\neffective\neffectively\neffectiveness\neffectual\nefficacious\nefficient\nefficiently\neffortless\neffortlessly\neffusion\neffusive\neffusively\neffusiveness\nelan\nelate\nelated\nelatedly\nelation\nelectrify\nelegance\nelegant\nelegantly\nelevate\nelite\neloquence\neloquent\neloquently\nembolden\neminence\neminent\nempathize\nempathy\nempower\nempowerment\nenchant\nenchanted\nenchanting\nenchantingly\nencourage\nencouragement\nencouraging\nencouragingly\nendear\nendearing\nendorse\nendorsed\nendorsement\nendorses\nendorsing\nenergetic\nenergize\nenergy-efficient\nenergy-saving\nengaging\nengrossing\nenhance\nenhanced\nenhancement\nenhances\nenjoy\nenjoyable\nenjoyably\nenjoyed\nenjoying\nenjoyment\nenjoys\nenlighten\nenlightenment\nenliven\nennoble\nenough\nenrapt\nenrapture\nenraptured\nenrich\nenrichment\nenterprising\nentertain\nentertaining\nentertains\nenthral\nenthrall\nenthralled\nenthuse\nenthusiasm\nenthusiast\nenthusiastic\nenthusiastically\nentice\nenticed\nenticing\nenticingly\nentranced\nentrancing\nentrust\nenviable\nenviably\nenvious\nenviously\nenviousness\nenvy\nequitable\nergonomical\nerr-free\nerudite\nethical\neulogize\neuphoria\neuphoric\neuphorically\nevaluative\nevenly\neventful\neverlasting\nevocative\nexalt\nexaltation\nexalted\nexaltedly\nexalting\nexaltingly\nexamplar\nexamplary\nexcallent\nexceed\nexceeded\nexceeding\nexceedingly\nexceeds\nexcel\nexceled\nexcelent\nexcellant\nexcelled\nexcellence\nexcellency\nexcellent\nexcellently\nexcels\nexceptional\nexceptionally\nexcite\nexcited\nexcitedly\nexcitedness\nexcitement\nexcites\nexciting\nexcitingly\nexellent\nexemplar\nexemplary\nexhilarate\nexhilarating\nexhilaratingly\nexhilaration\nexonerate\nexpansive\nexpeditiously\nexpertly\nexquisite\nexquisitely\nextol\nextoll\nextraordinarily\nextraordinary\nexuberance\nexuberant\nexuberantly\nexult\nexultant\nexultation\nexultingly\neye-catch\neye-catching\neyecatch\neyecatching\nfabulous\nfabulously\nfacilitate\nfair\nfairly\nfairness\nfaith\nfaithful\nfaithfully\nfaithfulness\nfame\nfamed\nfamous\nfamously\nfancier\nfancinating\nfancy\nfanfare\nfans\nfantastic\nfantastically\nfascinate\nfascinating\nfascinatingly\nfascination\nfashionable\nfashionably\nfast\nfast-growing\nfast-paced\nfaster\nfastest\nfastest-growing\nfaultless\nfav\nfave\nfavor\nfavorable\nfavored\nfavorite\nfavorited\nfavour\nfearless\nfearlessly\nfeasible\nfeasibly\nfeat\nfeature-rich\nfecilitous\nfeisty\nfelicitate\nfelicitous\nfelicity\nfertile\nfervent\nfervently\nfervid\nfervidly\nfervor\nfestive\nfidelity\nfiery\nfine\nfine-looking\nfinely\nfiner\nfinest\nfirmer\nfirst-class\nfirst-in-class\nfirst-rate\nflashy\nflatter\nflattering\nflatteringly\nflawless\nflawlessly\nflexibility\nflexible\nflourish\nflourishing\nfluent\nflutter\nfond\nfondly\nfondness\nfoolproof\nforemost\nforesight\nformidable\nfortitude\nfortuitous\nfortuitously\nfortunate\nfortunately\nfortune\nfragrant\nfree\nfreed\nfreedom\nfreedoms\nfresh\nfresher\nfreshest\nfriendliness\nfriendly\nfrolic\nfrugal\nfruitful\nftw\nfulfillment\nfun\nfuturestic\nfuturistic\ngaiety\ngaily\ngain\ngained\ngainful\ngainfully\ngaining\ngains\ngallant\ngallantly\ngalore\ngeekier\ngeeky\ngem\ngems\ngenerosity\ngenerous\ngenerously\ngenial\ngenius\ngentle\ngentlest\ngenuine\ngifted\nglad\ngladden\ngladly\ngladness\nglamorous\nglee\ngleeful\ngleefully\nglimmer\nglimmering\nglisten\nglistening\nglitter\nglitz\nglorify\nglorious\ngloriously\nglory\nglow\nglowing\nglowingly\ngod-given\ngod-send\ngodlike\ngodsend\ngold\ngolden\ngood\ngoodly\ngoodness\ngoodwill\ngoood\ngooood\ngorgeous\ngorgeously\ngrace\ngraceful\ngracefully\ngracious\ngraciously\ngraciousness\ngrand\ngrandeur\ngrateful\ngratefully\ngratification\ngratified\ngratifies\ngratify\ngratifying\ngratifyingly\ngratitude\ngreat\ngreatest\ngreatness\ngrin\ngroundbreaking\nguarantee\nguidance\nguiltless\ngumption\ngush\ngusto\ngutsy\nhail\nhalcyon\nhale\nhallmark\nhallmarks\nhallowed\nhandier\nhandily\nhands-down\nhandsome\nhandsomely\nhandy\nhappier\nhappily\nhappiness\nhappy\nhard-working\nhardier\nhardy\nharmless\nharmonious\nharmoniously\nharmonize\nharmony\nheadway\nheal\nhealthful\nhealthy\nhearten\nheartening\nheartfelt\nheartily\nheartwarming\nheaven\nheavenly\nhelped\nhelpful\nhelping\nhero\nheroic\nheroically\nheroine\nheroize\nheros\nhigh-quality\nhigh-spirited\nhilarious\nholy\nhomage\nhonest\nhonesty\nhonor\nhonorable\nhonored\nhonoring\nhooray\nhopeful\nhospitable\nhot\nhotcake\nhotcakes\nhottest\nhug\nhumane\nhumble\nhumility\nhumor\nhumorous\nhumorously\nhumour\nhumourous\nideal\nidealize\nideally\nidol\nidolize\nidolized\nidyllic\nilluminate\nilluminati\nilluminating\nillumine\nillustrious\nilu\nimaculate\nimaginative\nimmaculate\nimmaculately\nimmense\nimpartial\nimpartiality\nimpa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surance\nreassure\nreceptive\nreclaim\nrecomend\nrecommend\nrecommendation\nrecommendations\nrecommended\nreconcile\nreconciliation\nrecord-setting\nrecover\nrecovery\nrectification\nrectify\nrectifying\nredeem\nredeeming\nredemption\nrefine\nrefined\nrefinement\nreform\nreformed\nreforming\nreforms\nrefresh\nrefreshed\nrefreshing\nrefund\nrefunded\nregal\nregally\nregard\nrejoice\nrejoicing\nrejoicingly\nrejuvenate\nrejuvenated\nrejuvenating\nrelaxed\nrelent\nreliable\nreliably\nrelief\nrelish\nremarkable\nremarkably\nremedy\nremission\nremunerate\nrenaissance\nrenewed\nrenown\nrenowned\nreplaceable\nreputable\nreputation\nresilient\nresolute\nresound\nresounding\nresourceful\nresourcefulness\nrespect\nrespectable\nrespectful\nrespectfully\nrespite\nresplendent\nresponsibly\nresponsive\nrestful\nrestored\nrestructure\nrestructured\nrestructuring\nretractable\nrevel\nrevelation\nrevere\nreverence\nreverent\nreverently\nrevitalize\nrevival\nrevive\nrevives\nrevolutionary\nrevolutionize\nrevolutionized\nrevolutionizes\nreward\nrewarding\nrewardingly\nrich\nricher\nrichly\nrichness\nright\nrighten\nrighteous\nrighteously\nrighteousness\nrightful\nrightfully\nrightly\nrightness\nrisk-free\nrobust\nrock-star\nrock-stars\nrockstar\nrockstars\nromantic\nromantically\nromanticize\nroomier\nroomy\nrosy\nsafe\nsafely\nsagacity\nsagely\nsaint\nsaintliness\nsaintly\nsalutary\nsalute\nsane\nsatisfactorily\nsatisfactory\nsatisfied\nsatisfies\nsatisfy\nsatisfying\nsatisified\nsaver\nsavings\nsavior\nsavvy\nscenic\nseamless\nseasoned\nsecure\nsecurely\nselective\nself-determination\nself-respect\nself-satisfaction\nself-sufficiency\nself-sufficient\nsensation\nsensational\nsensationally\nsensations\nsensible\nsensibly\nsensitive\nserene\nserenity\nsexy\nsharp\nsharper\nsharpest\nshimmering\nshimmeringly\nshine\nshiny\nsignificant\nsilent\nsimpler\nsimplest\nsimplified\nsimplifies\nsimplify\nsimplifying\nsincere\nsincerely\nsincerity\nskill\nskilled\nskillful\nskillfully\nslammin\nsleek\nslick\nsmart\nsmarter\nsmartest\nsmartly\nsmile\nsmiles\nsmiling\nsmilingly\nsmitten\nsmooth\nsmoother\nsmoothes\nsmoothest\nsmoothly\nsnappy\nsnazzy\nsociable\nsoft\nsofter\nsolace\nsolicitous\nsolicitously\nsolid\nsolidarity\nsoothe\nsoothingly\nsophisticated\nsoulful\nsoundly\nsoundness\nspacious\nsparkle\nsparkling\nspectacular\nspectacularly\nspeedily\nspeedy\nspellbind\nspellbinding\nspellbindingly\nspellbound\nspirited\nspiritual\nsplendid\nsplendidly\nsplendor\nspontaneous\nsporty\nspotless\nsprightly\nstability\nstabilize\nstable\nstainless\nstandout\nstate-of-the-art\nstately\nstatuesque\nstaunch\nstaunchly\nstaunchness\nsteadfast\nsteadfastly\nsteadfastness\nsteadiest\nsteadiness\nsteady\nstellar\nstellarly\nstimulate\nstimulates\nstimulating\nstimulative\nstirringly\nstraighten\nstraightforward\nstreamlined\nstriking\nstrikingly\nstriving\nstrong\nstronger\nstrongest\nstunned\nstunning\nstunningly\nstupendous\nstupendously\nsturdier\nsturdy\nstylish\nstylishly\nstylized\nsuave\nsuavely\nsublime\nsubsidize\nsubsidized\nsubsidizes\nsubsidizing\nsubstantive\nsucceed\nsucceeded\nsucceeding\nsucceeds\nsucces\nsuccess\nsuccesses\nsuccessful\nsuccessfully\nsuffice\nsufficed\nsuffices\nsufficient\nsufficiently\nsuitable\nsumptuous\nsumptuously\nsumptuousness\nsuper\nsuperb\nsuperbly\nsuperior\nsuperiority\nsupple\nsupport\nsupported\nsupporter\nsupporting\nsupportive\nsupports\nsupremacy\nsupreme\nsupremely\nsupurb\nsupurbly\nsurmount\nsurpass\nsurreal\nsurvival\nsurvivor\nsustainability\nsustainable\nswank\nswankier\nswankiest\nswanky\nsweeping\nsweet\nsweeten\nsweetheart\nsweetly\nsweetness\nswift\nswiftness\ntalent\ntalented\ntalents\ntantalize\ntantalizing\ntantalizingly\ntempt\ntempting\ntemptingly\ntenacious\ntenaciously\ntenacity\ntender\ntenderly\nterrific\nterrifically\nthank\nthankful\nthinner\nthoughtful\nthoughtfully\nthoughtfulness\nthrift\nthrifty\nthrill\nthrilled\nthrilling\nthrillingly\nthrills\nthrive\nthriving\nthumb-up\nthumbs-up\ntickle\ntidy\ntime-honored\ntimely\ntingle\ntitillate\ntitillating\ntitillatingly\ntogetherness\ntolerable\ntoll-free\ntop\ntop-notch\ntop-quality\ntopnotch\ntops\ntough\ntougher\ntoughest\ntraction\ntranquil\ntranquility\ntransparent\ntreasure\ntremendously\ntrendy\ntriumph\ntriumphal\ntriumphant\ntriumphantly\ntrivially\ntrophy\ntrouble-free\ntrump\ntrumpet\ntrust\ntrusted\ntrusting\ntrustingly\ntrustworthiness\ntrustworthy\ntrusty\ntruthful\ntruthfully\ntruthfulness\ntwinkly\nultra-crisp\nunabashed\nunabashedly\nunaffected\nunassailable\nunbeatable\nunbiased\nunbound\nuncomplicated\nunconditional\nundamaged\nundaunted\nunderstandable\nundisputable\nundisputably\nundisputed\nunencumbered\nunequivocal\nunequivocally\nunfazed\nunfettered\nunforgettable\nunity\nunlimited\nunmatched\nunparalleled\nunquestionable\nunquestionably\nunreal\nunrestricted\nunrivaled\nunselfish\nunwavering\nupbeat\nupgradable\nupgradeable\nupgraded\nupheld\nuphold\nuplift\nuplifting\nupliftingly\nupliftment\nupscale\nusable\nuseable\nuseful\nuser-friendly\nuser-replaceable\nvaliant\nvaliantly\nvalor\nvaluable\nvariety\nvenerate\nverifiable\nveritable\nversatile\nversatility\nvibrant\nvibrantly\nvictorious\nvictory\nviewable\nvigilance\nvigilant\nvirtue\nvirtuous\nvirtuously\nvisionary\nvivacious\nvivid\nvouch\nvouchsafe\nwarm\nwarmer\nwarmhearted\nwarmly\nwarmth\nwealthy\nwelcome\nwell\nwell-backlit\nwell-balanced\nwell-behaved\nwell-being\nwell-bred\nwell-connected\nwell-educated\nwell-established\nwell-informed\nwell-intentioned\nwell-known\nwell-made\nwell-managed\nwell-mannered\nwell-positioned\nwell-received\nwell-regarded\nwell-rounded\nwell-run\nwell-wishers\nwellbeing\nwhoa\nwholeheartedly\nwholesome\nwhooa\nwhoooa\nwieldy\nwilling\nwillingly\nwillingness\nwin\nwindfall\nwinnable\nwinner\nwinners\nwinning\nwins\nwisdom\nwise\nwisely\nwitty\nwon\nwonder\nwonderful\nwonderfully\nwonderous\nwonderously\nwonders\nwondrous\nwoo\nwork\nworkable\nworked\nworks\nworld-famous\nworth\nworth-while\nworthiness\nworthwhile\nworthy\nwow\nwowed\nwowing\nwows\nyay\nyouthful\nzeal\nzenith\nzest\nzippy"
  },
  {
    "path": "NewsSentiment/knowledge/knowledgeutils.py",
    "content": "def find_key_original_or_lc(data: dict, data_keys_lower: dict, key: str):\n    # try to get the key as it is from the dict\n    if key in data.keys():\n        return data[key]\n    # if not contained, try whether if using case insensitivity we find an entry\n    if key.lower() in data_keys_lower.keys():\n        return data_keys_lower[key.lower()]\n    # if not, return None\n    return set()\n"
  },
  {
    "path": "NewsSentiment/knowledge/liwc/data/.gitignore",
    "content": "# Ignore everything in this directory\n*\n# Except this file\n!.gitignore\n!readme.txt\n"
  },
  {
    "path": "NewsSentiment/knowledge/liwc/data/readme.txt",
    "content": "In order to use LIWC, you need to acquire a license from them.\n"
  },
  {
    "path": "NewsSentiment/knowledge/liwc/dic.py",
    "content": "def _parse_categories(lines):\n    \"\"\"\n    Read (category_id, category_name) pairs from the categories section.\n    Each line consists of an integer followed a tab and then the category name.\n    This section is separated from the lexicon by a line consisting of a single \"%\".\n    \"\"\"\n    for line in lines:\n        line = line.strip()\n        if line == \"%\":\n            return\n        # ignore non-matching groups of categories\n        if \"\\t\" in line:\n            category_id, category_name = line.split(\"\\t\", 1)\n            yield category_id, category_name\n\n\ndef _parse_lexicon(lines, category_mapping):\n    \"\"\"\n    Read (match_expression, category_names) pairs from the lexicon section.\n    Each line consists of a match expression followed by a tab and then one or more\n    tab-separated integers, which are mapped to category names using `category_mapping`.\n    \"\"\"\n    for line in lines:\n        line = line.strip()\n        parts = line.split(\"\\t\")\n        yield parts[0], [category_mapping[category_id] for category_id in parts[1:]]\n\n\ndef read_dic(filepath):\n    \"\"\"\n    Reads a LIWC lexicon from a file in the .dic format, returning a tuple of\n    (lexicon, category_names), where:\n    * `lexicon` is a dict mapping string patterns to lists of category names\n    * `category_names` is a list of category names (as strings)\n    \"\"\"\n    with open(filepath) as lines:\n        # read up to first \"%\" (should be very first line of file)\n        for line in lines:\n            if line.strip() == \"%\":\n                break\n        # read categories (a mapping from integer string to category name)\n        category_mapping = dict(_parse_categories(lines))\n        # read lexicon (a mapping from matching string to a list of category names)\n        lexicon = dict(_parse_lexicon(lines, category_mapping))\n    return lexicon, list(category_mapping.values())\n"
  },
  {
    "path": "NewsSentiment/knowledge/liwc/liwc.py",
    "content": "import torch\n\nfrom NewsSentiment.knowledge.liwc.liwchelper import load_token_parser\n\nparse, category_names = load_token_parser()\n\nLIWC_CATEGORY2INDEX = {}\nfor index, category_name in enumerate(category_names):\n    LIWC_CATEGORY2INDEX[category_name] = index\n\n\ndef get_num_liwc_categories():\n    return len(category_names)\n\n\ndef get_liwc_categories_as_tensor(term: str):\n    categories = parse(term)\n    categories_of_lowercased = parse(term.lower())\n\n    if len(categories) == 0 and len(categories_of_lowercased) > 0:\n        # if we do not have categories of original term, but have them for lowercased term, use the latter\n        categories = categories_of_lowercased\n\n    tensor_emotions = torch.zeros(get_num_liwc_categories(), dtype=torch.long)\n    for category in categories:\n        index = LIWC_CATEGORY2INDEX[category]\n        assert index < get_num_liwc_categories()\n        tensor_emotions[index] = 1\n    return tensor_emotions\n"
  },
  {
    "path": "NewsSentiment/knowledge/liwc/liwchelper.py",
    "content": "from .dic import read_dic\nfrom .trie import build_trie, search_trie\n\ntry:\n    import pkg_resources\n\n    __version__ = pkg_resources.get_distribution(\"liwc\").version\nexcept Exception:\n    __version__ = None\n\n\ndef load_token_parser(filepath=\"knowledge/liwc/data/LIWC2015_English.dic\"):\n    \"\"\"\n    Reads a LIWC lexicon from a file in the .dic format, returning a tuple of\n    (parse, category_names), where:\n    * `parse` is a function from a token to a list of strings (potentially\n      empty) of matching categories\n    * `category_names` is a list of strings representing all LIWC categories in\n      the lexicon\n    \"\"\"\n    lexicon, category_names = read_dic(filepath)\n    trie = build_trie(lexicon)\n\n    def parse_token(token):\n        return search_trie(trie, token)\n\n    return parse_token, category_names\n"
  },
  {
    "path": "NewsSentiment/knowledge/liwc/trie.py",
    "content": "def build_trie(lexicon):\n    \"\"\"\n    Build a character-trie from the plain pattern_string -> categories_list\n    mapping provided by `lexicon`.\n\n    Some LIWC patterns end with a `*` to indicate a wildcard match.\n    \"\"\"\n    trie = {}\n    for pattern, category_names in lexicon.items():\n        cursor = trie\n        for char in pattern:\n            if char == \"*\":\n                cursor[\"*\"] = category_names\n                break\n            if char not in cursor:\n                cursor[char] = {}\n            cursor = cursor[char]\n        cursor[\"$\"] = category_names\n    return trie\n\n\ndef search_trie(trie, token, token_i=0):\n    \"\"\"\n    Search the given character-trie for paths that match the `token` string.\n    \"\"\"\n    if \"*\" in trie:\n        return trie[\"*\"]\n    if \"$\" in trie and token_i == len(token):\n        return trie[\"$\"]\n    if token_i < len(token):\n        char = token[token_i]\n        if char in trie:\n            return search_trie(trie[char], token, token_i + 1)\n    return []\n"
  },
  {
    "path": "NewsSentiment/knowledge/mpqasubjectivity/converter.py",
    "content": "import os\nfrom collections import defaultdict, Counter\nfrom pathlib import Path\nimport csv\n\nfrom tqdm import tqdm\n\nfrom NewsSentiment.fxlogger import get_logger\nfrom NewsSentiment.diskdict import DiskDict\n\nPOLARITY2INDEX = {\n    \"positive\": 2,\n    \"neutral\": 1,\n    \"negative\": 0,\n}\nTHIS_DIR = Path(os.path.dirname(os.path.realpath(__file__)))\nPATH_DICT_MPQA_SUBJECTIVITY = THIS_DIR / \"subjclueslen1-HLTEMNLP05.tff.ddict\"\n\nlogger = get_logger()\n\n\ndef get_value(entry_key_value: str):\n    return entry_key_value.split(\"=\")[1]\n\n\ndef convert_txt_to_dict():\n    path_dict = THIS_DIR / \"subjclueslen1-HLTEMNLP05.tff\"\n\n    term2polarity = defaultdict(set)\n    polarity_counter = Counter()\n    with open(path_dict, \"r\") as csv_file:\n        csv_reader = csv.reader(csv_file, delimiter=\" \")\n        for line in csv_reader:\n            entry_type, entry_length, entry_word, entry_pos, entry_is_stemmed, entry_polarity = line\n            entry_type = get_value(entry_type)\n            entry_length = get_value(entry_length)\n            entry_word = get_value(entry_word)\n            entry_pos = get_value(entry_pos)\n            entry_is_stemmed = get_value(entry_is_stemmed)\n            entry_polarity = get_value(entry_polarity)\n\n            assert \" \" not in entry_word, f\"cannot handle spaces in word\"\n            assert entry_polarity in POLARITY2INDEX.keys() or entry_polarity == \"both\", f\"polarity label not known: {entry_polarity} for {entry_word}\"\n\n            if entry_polarity == \"both\":\n                polarities = [POLARITY2INDEX[\"positive\"], POLARITY2INDEX[\"negative\"]]\n            else:\n                polarities = (POLARITY2INDEX[entry_polarity],)\n\n            for polarity in polarities:\n                term2polarity[entry_word].add(polarity)\n                polarity_counter[polarity] += 1\n\n    logger.info(\"read %s terms\", len(term2polarity))\n    logger.info(\"polarity count:\\n%s\", polarity_counter.most_common())\n\n    logger.info(\"saving to %s...\", PATH_DICT_MPQA_SUBJECTIVITY)\n    ddict_emolex = DiskDict(PATH_DICT_MPQA_SUBJECTIVITY)\n    ddict_emolex.update(term2polarity)\n    ddict_emolex.sync_to_disk()\n    logger.info(\"done\")\n\n\nif __name__ == \"__main__\":\n    convert_txt_to_dict()\n"
  },
  {
    "path": "NewsSentiment/knowledge/mpqasubjectivity/mpqasubjectivity.py",
    "content": "import torch\n\nfrom NewsSentiment.diskdict import DiskDict\nfrom NewsSentiment.knowledge.knowledgeutils import find_key_original_or_lc\nfrom NewsSentiment.knowledge.mpqasubjectivity.converter import POLARITY2INDEX, PATH_DICT_MPQA_SUBJECTIVITY\n\n__ddict_emolex = DiskDict(PATH_DICT_MPQA_SUBJECTIVITY)\n__ddict_emolex_keys_lower = {k.lower(): v for k, v in __ddict_emolex.items()}\n__num_emotions = 3\nassert len(__ddict_emolex) == 6886, len(__ddict_emolex)\nassert len(POLARITY2INDEX) == __num_emotions\n\n\ndef get_num_mpqa_subjectivity_polarities():\n    return __num_emotions\n\n\ndef get_mpqa_subjectivity_polarities_as_tensor(term: str):\n    emotions = find_key_original_or_lc(__ddict_emolex, __ddict_emolex_keys_lower, term)\n    tensor_emotions = torch.zeros(__num_emotions, dtype=torch.long)\n    for emotion_index in emotions:\n        tensor_emotions[emotion_index] = 1\n    return tensor_emotions\n"
  },
  {
    "path": "NewsSentiment/knowledge/mpqasubjectivity/subjclueslen1-HLTEMNLP05.tff",
    "content": "type=weaksubj len=1 word1=abandoned pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=abandonment pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=abandon pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=abase pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=abasement pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=abash pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=abate pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=abdicate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=aberration pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=aberration pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=abhor pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=abhor pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj 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pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=anti-proliferation pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=anti-proliferation pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=anti-social pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=anti-white pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=anti-white pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=antipathy pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=antiquated pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=antithetical pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=antithetical pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=anxieties pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=anxiety pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj 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pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inclined pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=inclusive pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=incognizant pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incoherence pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incoherent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incoherently pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incommensurate pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incomparable pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incomparably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incompatibility pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incompatible pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incompatible pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incompetence pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incompetent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incompetently pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incomplete pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incompliant pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incomprehensible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incomprehension pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconceivable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconceivably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inconclusive pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incongruous pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incongruously pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsequent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsequently pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsequential pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsequentially pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsiderate pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsiderately pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsistence pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsistencies pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsistencies pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inconsistency pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inconsistent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsolable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconsolably pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconstant pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incontestable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=incontrovertible pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inconvenience pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconvenience pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconvenient pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inconveniently pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=incorrect pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incorrectly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incorrigible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incorrigibly pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incorruptible pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=increasing pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=increasingly pos1=adverb stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=incredible pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=incredibly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=incredulous pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=incredulously pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inculcate pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=indebted pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indecency pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indecent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indecently pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indecision pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indecisive pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indecisively pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indecorum pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indeed pos1=anypos stemmed1=y priorpolarity=neutral\ntype=strongsubj len=1 word1=indefatigable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indefensible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indefensible pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indefinite pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indefinitely pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indelible pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indelibly pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indelicate pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=independence pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=independence pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=independent pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indescribable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indescribably pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indestructible pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=indeterminable pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indeterminably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indeterminate pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indication pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=indication pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=indicative pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=indicative pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=indifference pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indifferent pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indigent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indignant pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indignantly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indignation pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indignity pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indignity pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indirect pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=indiscernible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indiscreet pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indiscreet pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indiscreetly pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indiscretion pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=indiscriminate pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indiscriminating pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indiscriminately pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indispensable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indispensability pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indisposed pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indisputable pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=indistinct pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=indistinctive pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=individuality pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indoctrinate pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=indoctrination pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indoctrination pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indolent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=indomitable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indomitably pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indubitable pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indubitably pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indulge pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=indulgence pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=indulgent pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=industrious pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=ineffective pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=ineffectively pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=ineffectiveness pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=ineffectual pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=ineffectually pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=ineffectualness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inefficacious pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inefficacious pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inefficacy pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inefficiency pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inefficient pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inefficiently pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=ineligible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inelegance pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inelegant pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ineloquent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ineloquently pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inept pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ineptitude pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=ineptitude pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ineptly pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inequalities pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inequalities pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inequality pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inequality pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inequitable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inequitably pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inequities pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inequities pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inertia pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inertia pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inescapable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inescapably pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inessential pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inestimable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inestimably pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inevitable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inevitable pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inevitably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inexact pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inexcusable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inexcusably pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inexorable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inexorably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inexpensive pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=inexperience pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inexperienced pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inexpert pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inexpertly pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inexpiable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inexplainable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inexplicable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inextricable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inextricably pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infallible pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=infallibly pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=infallibility pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=infamous pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infamously pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infamy pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infatuated pos1=anypos stemmed1=n priorpolarity=both\ntype=weaksubj len=1 word1=infected pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=infectious pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=infer pos1=verb stemmed1=y priorpolarity=neutral\ntype=weaksubj len=1 word1=inference pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=inference pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=inferior pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inferiority pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infernal pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=infest pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=infested pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infidel pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infidels pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=infiltrator pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=infiltrators pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=infiltrators pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infirm pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inflame pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=inflammatory pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inflated pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=inflationary pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inflexible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inflict pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=influence pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=influence pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=influential pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=informational pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=informative pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=infraction pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infringe pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=infringement pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infringements pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infringements pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infuriate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=infuriated pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infuriating pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=infuriatingly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ingenious pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=ingeniously pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=ingenuity pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=ingenuous pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=ingenuously pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inglorious pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ingrate pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ingratiate pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=ingratiating pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=ingratiatingly pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=ingratitude pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inherent pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=inherent pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=inhibit pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=inhibition pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inhospitable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inhospitality pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inhuman pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inhumane pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inhumanity pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inimical pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inimically pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=iniquitous pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=iniquity pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=injudicious pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=injure pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=injurious pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=injury pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=injustice pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=injustice pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=injustices pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=injustices pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inkling pos1=anypos stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=inklings pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=inklings pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=innocence pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=innocence pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=innocent pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=innocently pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=innocuous pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=innocuous pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=innovation pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=innovation pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=innovative pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=innumerable pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=innumerably pos1=adverb stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=innumerous pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=innuendo pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=innuendo pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inoffensive pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inopportune pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inordinate pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inordinately pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inquisitive pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insane pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insanely pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insanity pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insatiable pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insecure pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insecurity pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insecurity pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insensible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insensitive pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insensitively pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insensitivity pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insensitivity pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insidious pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insidiously pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insight pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insight pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insightful pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insightfully pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insights pos1=anypos stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=insignificance pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insignificant pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insignificantly pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insincere pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insincerely pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insincerity pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insinuate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=insinuating pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insinuation pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insinuation pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insist pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=insistence pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=insistence pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insistent pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insistently pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=insociable pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=isolation pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insolence pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insolence pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insolent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insolently pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insolvent pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insouciance pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inspiration pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inspirational pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inspire pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=inspiring pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inspiring pos1=anypos stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=instability pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=instable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=instigate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=instigator pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=instigators pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=instructive pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=instrumental pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=insubordinate pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insubstantial pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insubstantially pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insufferable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insufferably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insufficiency pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insufficient pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insufficiently pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insular pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insult pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insult pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=insulted pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insulting pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insulting pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insultingly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insupportable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=insupportably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insurmountable pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insurmountably pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insurrection pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=insurrection pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=intact pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=integral pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=integrity pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intelligent pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=intelligence pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intelligible pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=intend pos1=verb stemmed1=y priorpolarity=neutral\ntype=weaksubj len=1 word1=intense pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intense pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intensive pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intensively pos1=adverb stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intent pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intent pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intention pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intention pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intentions pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intentions pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intents pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intents pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=intercede pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=interest pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=interest pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=interest pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=interested pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=interesting pos1=anypos stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=interests pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=interests pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=interfere pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=interference pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=interference pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=intermittent pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=interrupt pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=interruption pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intimacy pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intimacy pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=intimate pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intimate pos1=verb stemmed1=y priorpolarity=neutral\ntype=weaksubj len=1 word1=intimidate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=intimidating pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intimidatingly pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=intimidation pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=intimidation pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intolerable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intolerablely pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intolerance pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intolerance pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intolerant pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=intoxicate pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=intractable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intransigence pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intransigence pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intransigent pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=intricate pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intrigue pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intrigue pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=intrigue pos1=verb stemmed1=y priorpolarity=neutral\ntype=strongsubj len=1 word1=intriguing pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intriguing pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intriguingly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=intrude pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=intrusion pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intrusive pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=intuitive pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inundate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=inundated pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=invader pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=invader pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=invalid pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=invalidate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=invalidity pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=invaluable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=invaluablely pos1=anypos stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=invasive pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=invective pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=inveigle pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=inventive pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=invidious pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=invidiously pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=invidiousness pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=invigorate pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=invigorating pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=invincibility pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=invincible pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inviolable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=inviolate pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=invisible pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=invulnerable pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=involuntarily pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=involuntary pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irate pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irately pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ire pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irk pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=irksome pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ironic pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ironies pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=ironies pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irony pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irrational pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irrationality pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irrationally pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irreconcilable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irredeemable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irredeemably pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irreformable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irrefutable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=irrefutably pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=irregardless pos1=anypos stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=irregular pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=irregularity pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irrelevance pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irrelevant pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irreparable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irreplacible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irrepressible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irreproachable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=irresistible pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=irresistibly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=irresolute pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=irresolvable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irresponsible pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irresponsibly pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=irretrievable pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irreverence pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=irreverent pos1=adj stemmed1=n 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stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=reconciliation pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=record-setting pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=recourses pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=recourses pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=recover pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=rectification pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=rectification pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=rectify pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=rectifying pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=rectifying pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=redeem pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=redeeming pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=redemption pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=redundancy pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=redundant pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=reestablish pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=refine pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=refined pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=refinement pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=reflecting pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=reflecting pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=reflective pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=reform pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=reform pos1=verb stemmed1=n 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priorpolarity=negative\ntype=strongsubj len=1 word1=regrettably pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=rehabilitate pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=rehabilitation pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=reinforce pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=reinforcement pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=reiterate pos1=verb stemmed1=y priorpolarity=neutral\ntype=weaksubj len=1 word1=reiterated pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=reiterated pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=reiterates pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=reiterates pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=reject pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=rejection pos1=adj stemmed1=n 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priorpolarity=negative\ntype=strongsubj len=1 word1=relentlessness pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=relevant pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=relevance pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=reliable pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=reliability pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=reliably pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=relief pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=relief pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=relieve pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=relish pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=reluctance pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=reluctance pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=reluctant pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=reluctantly pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=remark pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=remark pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=remarkable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=remarkable pos1=anypos stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=remarkably pos1=anypos stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=remedy pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=reminiscent pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=reminiscent pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=remorse pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=remorse pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=remorseful pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=remorseful pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=remorsefully pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=remorseless pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=remorselessly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=remorselessness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=remunerate pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=renaissance pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=renewable pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=renewal pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=renovate pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=renovation pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=renounce pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=renown pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=renowned pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=renunciation pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=repair pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=repair pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=reparation pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=repay pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=repel pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=repent pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=repentance pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=repetitive pos1=adj stemmed1=n 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priorpolarity=negative\ntype=weaksubj len=1 word1=snare pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=snarl pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=snarl pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=snatch pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=sneak pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sneak pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=sneakily pos1=adverb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sneaky pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sneer pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sneer pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=sneering pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sneeringly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=snub pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=so pos1=anypos stemmed1=y priorpolarity=neutral\ntype=strongsubj len=1 word1=so-cal pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=so-called pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sob pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=sober pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sober pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=sobering pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sociable pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=soft-spoken pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=soften pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=soften pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=soften pos1=verb stemmed1=y 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priorpolarity=negative\ntype=strongsubj len=1 word1=soothe pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=soothingly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=sophisticated pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=sore pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sore pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sorely pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=soreness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sorrow pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sorrow pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=sorrowful pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sorrowfully pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=sorry pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sound pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=sounding pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=soundness pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=sour pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sourly pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sovereignty pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=sovereignty pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=spacious pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spade pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spade pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spank pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=spare pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=sparing pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=sparingly pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=sparkle pos1=anypos stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=sparkling pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=specific pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=specifically pos1=anypos stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=special pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spectacular pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spectacularly pos1=anypos stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=speculate pos1=verb stemmed1=y priorpolarity=neutral\ntype=weaksubj len=1 word1=speculation pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=speculation pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=speedy pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spellbind pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=spellbinding pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spellbindingly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spellbound pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=spilling pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spilling pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=spinster pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=spirit pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=spirit pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=spirited pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spiritless pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spiritual pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spiritual pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=spite pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spiteful pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spitefully pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spitefulness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=splayed-finger pos1=adj stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=splayed-finger pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=splendid pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=splendidly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=splendor pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=split pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=split pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=splitting pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spoil pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=spook pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=spookier pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spookiest pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spookily pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spooky pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spooky pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spoon-fed pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=spoon-feed pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=spoonfed pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=sporadic pos1=adj stemmed1=n 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priorpolarity=positive\ntype=strongsubj len=1 word1=squash pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=squirm pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=stab pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=stability pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=stability pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=stabilize pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=stable pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=stable pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=stagger pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=staggering pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=staggeringly pos1=anypos stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=stagnant pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=stagnate pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=stagnation pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=staid pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=stain pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=stainless pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=stake pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=stake pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=stale pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=stalemate pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=stammer pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=stampede pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=stampede pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=stance pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=stance pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=stances pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=stances pos1=noun stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=stand pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=stands pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=stands pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=standstill pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=star pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=star pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=stark pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=starkly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=stars pos1=adj stemmed1=n 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word1=war pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=war pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=war-like pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=war-like pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=warfare pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=warlike pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=warm pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=warmhearted pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=warmly pos1=adverb stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=warmth pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=warning pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=warning pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=warp pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=warped pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wary pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=warily pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wariness pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=waste pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=waste pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=wasteful pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wastefulness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=watchdog pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=watchdog pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wayward pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=weak pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weaken pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=weakening pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weakening pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weakness pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weakness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weaknesses pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weaknesses pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wealthy pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=weariness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wearisome pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weary pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weary pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=weary pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=wedge pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wedge pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wee pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=weed pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=weep pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=weird pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weird pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=weirdly pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=welcome pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=welcome pos1=anypos stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=welcome pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=welcome pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=welfare pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=welfare pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=well pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=well pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-being pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-being pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-connected pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=well-educated pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=well-established pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-informed pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-intentioned pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-managed pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=well-positioned pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=well-publicized pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-received pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-regarded pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-run pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-wishers pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=well-wishers pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wellbeing pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wellbeing pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=whatever pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=wheedle pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=whiff pos1=adj stemmed1=n priorpolarity=neutral\ntype=weaksubj len=1 word1=whiff pos1=noun stemmed1=n priorpolarity=neutral\ntype=strongsubj len=1 word1=whimper pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=whimsical pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=whine pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=whine pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=whips pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=whips pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=white pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wholeheartedly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wholesome pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wicked pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wickedly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wickedness pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wide pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=wide-open pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=wide-ranging pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=widespread pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wild pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wildly pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wiles pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=will pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=will pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=willful pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=willfully pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=willing pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=willingness pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=willingness pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wilt pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=wily pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wince pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=wink pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wink pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=winnable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=winnable pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=winners pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=winners pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wisdom pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wisdom pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wise pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wise pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wisely pos1=adverb stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wish pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wish pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wish pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=wishes pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wishes pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wishing pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wishing pos1=noun stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=withheld pos1=verb stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=withhold pos1=verb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=witty pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=woe pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=woebegone pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=woeful pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=woefully pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wonder pos1=anypos stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=wonderful pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wonderful pos1=anypos stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=wonderfully pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wonderous pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wonderously pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wondrous pos1=anypos stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=woo pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=workable pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=world-famous pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=worn pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=worn pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=worried pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worriedly pos1=adverb stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worrier pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worries pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worries pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worrisome pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worry pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worry pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worry pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=worrying pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=worryingly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worse pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worsen pos1=anypos stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=worsening pos1=anypos stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=worship pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=worst pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worth pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=worth pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=worth-while pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=worthiness pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=worthless pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worthlessly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worthlessness pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=worthwhile pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=worthy pos1=adj stemmed1=n priorpolarity=positive\ntype=weaksubj len=1 word1=would pos1=anypos stemmed1=y priorpolarity=neutral\ntype=strongsubj len=1 word1=wound pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wound pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wound pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=wounds pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wounds pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wow pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=wow pos1=verb stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=wreck pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wreck pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=wrangle pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=wrath pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wrest pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=wrestle pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=wretch pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wretched pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wretchedly pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wretchedness pos1=noun stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=writhe pos1=verb stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=wrong pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wrong pos1=anypos stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=wrongful pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wrongly pos1=anypos stemmed1=y priorpolarity=negative\ntype=weaksubj len=1 word1=wrought pos1=adj stemmed1=n priorpolarity=negative\ntype=weaksubj len=1 word1=wrought pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=wry pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=yawn pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=yawn pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=yeah pos1=anypos stemmed1=y priorpolarity=neutral\ntype=strongsubj len=1 word1=yearn pos1=verb stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=yearning pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=yearningly pos1=anypos stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=yelp pos1=verb stemmed1=y priorpolarity=negative\ntype=strongsubj len=1 word1=yep pos1=anypos stemmed1=y priorpolarity=positive\ntype=strongsubj len=1 word1=yes pos1=anypos stemmed1=y priorpolarity=positive\ntype=weaksubj len=1 word1=youthful pos1=adj stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=zeal pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=zealot pos1=noun stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=zealous pos1=adj stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=zealously pos1=anypos stemmed1=n priorpolarity=negative\ntype=strongsubj len=1 word1=zenith pos1=noun stemmed1=n priorpolarity=positive\ntype=strongsubj len=1 word1=zest pos1=noun stemmed1=n priorpolarity=positive\n"
  },
  {
    "path": "NewsSentiment/knowledge/nrcemolex/NRC-Emotion-Lexicon-Wordlevel-v0.92.txt",
    "content": "aback\tanger\t0\naback\tanticipation\t0\naback\tdisgust\t0\naback\tfear\t0\naback\tjoy\t0\naback\tnegative\t0\naback\tpositive\t0\naback\tsadness\t0\naback\tsurprise\t0\naback\ttrust\t0\nabacus\tanger\t0\nabacus\tanticipation\t0\nabacus\tdisgust\t0\nabacus\tfear\t0\nabacus\tjoy\t0\nabacus\tnegative\t0\nabacus\tpositive\t0\nabacus\tsadness\t0\nabacus\tsurprise\t0\nabacus\ttrust\t1\nabandon\tanger\t0\nabandon\tanticipation\t0\nabandon\tdisgust\t0\nabandon\tfear\t1\nabandon\tjoy\t0\nabandon\tnegative\t1\nabandon\tpositive\t0\nabandon\tsadness\t1\nabandon\tsurprise\t0\nabandon\ttrust\t0\nabandoned\tanger\t1\nabandoned\tanticipation\t0\nabandoned\tdisgust\t0\nabandoned\tfear\t1\nabandoned\tjoy\t0\nabandoned\tnegative\t1\nabandoned\tpositive\t0\nabandoned\tsadness\t1\nabandoned\tsurprise\t0\nabandoned\ttrust\t0\nabandonment\tanger\t1\nabandonment\tanticipation\t0\nabandonment\tdisgust\t0\nabandonment\tfear\t1\nabandonment\tjoy\t0\nabandonment\tnegative\t1\nabandonment\tpositive\t0\nabandonment\tsadness\t1\nabandonment\tsurprise\t1\nabandonment\ttrust\t0\nabate\tanger\t0\nabate\tanticipation\t0\nabate\tdisgust\t0\nabate\tfear\t0\nabate\tjoy\t0\nabate\tnegative\t0\nabate\tpositive\t0\nabate\tsadness\t0\nabate\tsurprise\t0\nabate\ttrust\t0\nabatement\tanger\t0\nabatement\tanticipation\t0\nabatement\tdisgust\t0\nabatement\tfear\t0\nabatement\tjoy\t0\nabatement\tnegative\t0\nabatement\tpositive\t0\nabatement\tsadness\t0\nabatement\tsurprise\t0\nabatement\ttrust\t0\nabba\tanger\t0\nabba\tanticipation\t0\nabba\tdisgust\t0\nabba\tfear\t0\nabba\tjoy\t0\nabba\tnegative\t0\nabba\tpositive\t1\nabba\tsadness\t0\nabba\tsurprise\t0\nabba\ttrust\t0\nabbot\tanger\t0\nabbot\tanticipation\t0\nabbot\tdisgust\t0\nabbot\tfear\t0\nabbot\tjoy\t0\nabbot\tnegative\t0\nabbot\tpositive\t0\nabbot\tsadness\t0\nabbot\tsurprise\t0\nabbot\ttrust\t1\nabbreviate\tanger\t0\nabbreviate\tanticipation\t0\nabbreviate\tdisgust\t0\nabbreviate\tfear\t0\nabbreviate\tjoy\t0\nabbreviate\tnegative\t0\nabbreviate\tpositive\t0\nabbreviate\tsadness\t0\nabbreviate\tsurprise\t0\nabbreviate\ttrust\t0\nabbreviation\tanger\t0\nabbreviation\tanticipation\t0\nabbreviation\tdisgust\t0\nabbreviation\tfear\t0\nabbreviation\tjoy\t0\nabbreviation\tnegative\t0\nabbreviation\tpositive\t0\nabbreviation\tsadness\t0\nabbreviation\tsurprise\t0\nabbreviation\ttrust\t0\nabdomen\tanger\t0\nabdomen\tanticipation\t0\nabdomen\tdisgust\t0\nabdomen\tfear\t0\nabdomen\tjoy\t0\nabdomen\tnegative\t0\nabdomen\tpositive\t0\nabdomen\tsadness\t0\nabdomen\tsurprise\t0\nabdomen\ttrust\t0\nabdominal\tanger\t0\nabdominal\tanticipation\t0\nabdominal\tdisgust\t0\nabdominal\tfear\t0\nabdominal\tjoy\t0\nabdominal\tnegative\t0\nabdominal\tpositive\t0\nabdominal\tsadness\t0\nabdominal\tsurprise\t0\nabdominal\ttrust\t0\nabduction\tanger\t0\nabduction\tanticipation\t0\nabduction\tdisgust\t0\nabduction\tfear\t1\nabduction\tjoy\t0\nabduction\tnegative\t1\nabduction\tpositive\t0\nabduction\tsadness\t1\nabduction\tsurprise\t1\nabduction\ttrust\t0\naberrant\tanger\t0\naberrant\tanticipation\t0\naberrant\tdisgust\t0\naberrant\tfear\t0\naberrant\tjoy\t0\naberrant\tnegative\t1\naberrant\tpositive\t0\naberrant\tsadness\t0\naberrant\tsurprise\t0\naberrant\ttrust\t0\naberration\tanger\t0\naberration\tanticipation\t0\naberration\tdisgust\t1\naberration\tfear\t0\naberration\tjoy\t0\naberration\tnegative\t1\naberration\tpositive\t0\naberration\tsadness\t0\naberration\tsurprise\t0\naberration\ttrust\t0\nabeyance\tanger\t0\nabeyance\tanticipation\t0\nabeyance\tdisgust\t0\nabeyance\tfear\t0\nabeyance\tjoy\t0\nabeyance\tnegative\t0\nabeyance\tpositive\t0\nabeyance\tsadness\t0\nabeyance\tsurprise\t0\nabeyance\ttrust\t0\nabhor\tanger\t1\nabhor\tanticipation\t0\nabhor\tdisgust\t1\nabhor\tfear\t1\nabhor\tjoy\t0\nabhor\tnegative\t1\nabhor\tpositive\t0\nabhor\tsadness\t0\nabhor\tsurprise\t0\nabhor\ttrust\t0\nabhorrent\tanger\t1\nabhorrent\tanticipation\t0\nabhorrent\tdisgust\t1\nabhorrent\tfear\t1\nabhorrent\tjoy\t0\nabhorrent\tnegative\t1\nabhorrent\tpositive\t0\nabhorrent\tsadness\t0\nabhorrent\tsurprise\t0\nabhorrent\ttrust\t0\nabide\tanger\t0\nabide\tanticipation\t0\nabide\tdisgust\t0\nabide\tfear\t0\nabide\tjoy\t0\nabide\tnegative\t0\nabide\tpositive\t0\nabide\tsadness\t0\nabide\tsurprise\t0\nabide\ttrust\t0\nability\tanger\t0\nability\tanticipation\t0\nability\tdisgust\t0\nability\tfear\t0\nability\tjoy\t0\nability\tnegative\t0\nability\tpositive\t1\nability\tsadness\t0\nability\tsurprise\t0\nability\ttrust\t0\nabject\tanger\t0\nabject\tanticipation\t0\nabject\tdisgust\t1\nabject\tfear\t0\nabject\tjoy\t0\nabject\tnegative\t1\nabject\tpositive\t0\nabject\tsadness\t0\nabject\tsurprise\t0\nabject\ttrust\t0\nablation\tanger\t0\nablation\tanticipation\t0\nablation\tdisgust\t0\nablation\tfear\t0\nablation\tjoy\t0\nablation\tnegative\t0\nablation\tpositive\t0\nablation\tsadness\t0\nablation\tsurprise\t0\nablation\ttrust\t0\nablaze\tanger\t0\nablaze\tanticipation\t0\nablaze\tdisgust\t0\nablaze\tfear\t0\nablaze\tjoy\t0\nablaze\tnegative\t0\nablaze\tpositive\t0\nablaze\tsadness\t0\nablaze\tsurprise\t0\nablaze\ttrust\t0\nabnormal\tanger\t0\nabnormal\tanticipation\t0\nabnormal\tdisgust\t1\nabnormal\tfear\t0\nabnormal\tjoy\t0\nabnormal\tnegative\t1\nabnormal\tpositive\t0\nabnormal\tsadness\t0\nabnormal\tsurprise\t0\nabnormal\ttrust\t0\naboard\tanger\t0\naboard\tanticipation\t0\naboard\tdisgust\t0\naboard\tfear\t0\naboard\tjoy\t0\naboard\tnegative\t0\naboard\tpositive\t0\naboard\tsadness\t0\naboard\tsurprise\t0\naboard\ttrust\t0\nabode\tanger\t0\nabode\tanticipation\t0\nabode\tdisgust\t0\nabode\tfear\t0\nabode\tjoy\t0\nabode\tnegative\t0\nabode\tpositive\t0\nabode\tsadness\t0\nabode\tsurprise\t0\nabode\ttrust\t0\nabolish\tanger\t1\nabolish\tanticipation\t0\nabolish\tdisgust\t0\nabolish\tfear\t0\nabolish\tjoy\t0\nabolish\tnegative\t1\nabolish\tpositive\t0\nabolish\tsadness\t0\nabolish\tsurprise\t0\nabolish\ttrust\t0\nabolition\tanger\t0\nabolition\tanticipation\t0\nabolition\tdisgust\t0\nabolition\tfear\t0\nabolition\tjoy\t0\nabolition\tnegative\t1\nabolition\tpositive\t0\nabolition\tsadness\t0\nabolition\tsurprise\t0\nabolition\ttrust\t0\nabominable\tanger\t0\nabominable\tanticipation\t0\nabominable\tdisgust\t1\nabominable\tfear\t1\nabominable\tjoy\t0\nabominable\tnegative\t1\nabominable\tpositive\t0\nabominable\tsadness\t0\nabominable\tsurprise\t0\nabominable\ttrust\t0\nabomination\tanger\t1\nabomination\tanticipation\t0\nabomination\tdisgust\t1\nabomination\tfear\t1\nabomination\tjoy\t0\nabomination\tnegative\t1\nabomination\tpositive\t0\nabomination\tsadness\t0\nabomination\tsurprise\t0\nabomination\ttrust\t0\naboriginal\tanger\t0\naboriginal\tanticipation\t0\naboriginal\tdisgust\t0\naboriginal\tfear\t0\naboriginal\tjoy\t0\naboriginal\tnegative\t0\naboriginal\tpositive\t0\naboriginal\tsadness\t0\naboriginal\tsurprise\t0\naboriginal\ttrust\t0\nabort\tanger\t0\nabort\tanticipation\t0\nabort\tdisgust\t0\nabort\tfear\t0\nabort\tjoy\t0\nabort\tnegative\t1\nabort\tpositive\t0\nabort\tsadness\t0\nabort\tsurprise\t0\nabort\ttrust\t0\nabortion\tanger\t0\nabortion\tanticipation\t0\nabortion\tdisgust\t1\nabortion\tfear\t1\nabortion\tjoy\t0\nabortion\tnegative\t1\nabortion\tpositive\t0\nabortion\tsadness\t1\nabortion\tsurprise\t0\nabortion\ttrust\t0\nabortive\tanger\t0\nabortive\tanticipation\t0\nabortive\tdisgust\t0\nabortive\tfear\t0\nabortive\tjoy\t0\nabortive\tnegative\t1\nabortive\tpositive\t0\nabortive\tsadness\t1\nabortive\tsurprise\t0\nabortive\ttrust\t0\nabound\tanger\t0\nabound\tanticipation\t0\nabound\tdisgust\t0\nabound\tfear\t0\nabound\tjoy\t0\nabound\tnegative\t0\nabound\tpositive\t0\nabound\tsadness\t0\nabound\tsurprise\t0\nabound\ttrust\t0\nabovementioned\tanger\t0\nabovementioned\tanticipation\t0\nabovementioned\tdisgust\t0\nabovementioned\tfear\t0\nabovementioned\tjoy\t0\nabovementioned\tnegative\t0\nabovementioned\tpositive\t1\nabovementioned\tsadness\t0\nabovementioned\tsurprise\t0\nabovementioned\ttrust\t0\nabrasion\tanger\t0\nabrasion\tanticipation\t0\nabrasion\tdisgust\t0\nabrasion\tfear\t0\nabrasion\tjoy\t0\nabrasion\tnegative\t1\nabrasion\tpositive\t0\nabrasion\tsadness\t0\nabrasion\tsurprise\t0\nabrasion\ttrust\t0\nabroad\tanger\t0\nabroad\tanticipation\t0\nabroad\tdisgust\t0\nabroad\tfear\t0\nabroad\tjoy\t0\nabroad\tnegative\t0\nabroad\tpositive\t0\nabroad\tsadness\t0\nabroad\tsurprise\t0\nabroad\ttrust\t0\nabrogate\tanger\t0\nabrogate\tanticipation\t0\nabrogate\tdisgust\t0\nabrogate\tfear\t0\nabrogate\tjoy\t0\nabrogate\tnegative\t1\nabrogate\tpositive\t0\nabrogate\tsadness\t0\nabrogate\tsurprise\t0\nabrogate\ttrust\t0\nabrupt\tanger\t0\nabrupt\tanticipation\t0\nabrupt\tdisgust\t0\nabrupt\tfear\t0\nabrupt\tjoy\t0\nabrupt\tnegative\t0\nabrupt\tpositive\t0\nabrupt\tsadness\t0\nabrupt\tsurprise\t1\nabrupt\ttrust\t0\nabruptly\tanger\t0\nabruptly\tanticipation\t0\nabruptly\tdisgust\t0\nabruptly\tfear\t0\nabruptly\tjoy\t0\nabruptly\tnegative\t0\nabruptly\tpositive\t0\nabruptly\tsadness\t0\nabruptly\tsurprise\t0\nabruptly\ttrust\t0\nabscess\tanger\t0\nabscess\tanticipation\t0\nabscess\tdisgust\t0\nabscess\tfear\t0\nabscess\tjoy\t0\nabscess\tnegative\t1\nabscess\tpositive\t0\nabscess\tsadness\t1\nabscess\tsurprise\t0\nabscess\ttrust\t0\nabsence\tanger\t0\nabsence\tanticipation\t0\nabsence\tdisgust\t0\nabsence\tfear\t1\nabsence\tjoy\t0\nabsence\tnegative\t1\nabsence\tpositive\t0\nabsence\tsadness\t1\nabsence\tsurprise\t0\nabsence\ttrust\t0\nabsent\tanger\t0\nabsent\tanticipation\t0\nabsent\tdisgust\t0\nabsent\tfear\t0\nabsent\tjoy\t0\nabsent\tnegative\t1\nabsent\tpositive\t0\nabsent\tsadness\t1\nabsent\tsurprise\t0\nabsent\ttrust\t0\nabsentee\tanger\t0\nabsentee\tanticipation\t0\nabsentee\tdisgust\t0\nabsentee\tfear\t0\nabsentee\tjoy\t0\nabsentee\tnegative\t1\nabsentee\tpositive\t0\nabsentee\tsadness\t1\nabsentee\tsurprise\t0\nabsentee\ttrust\t0\nabsenteeism\tanger\t0\nabsenteeism\tanticipation\t0\nabsenteeism\tdisgust\t0\nabsenteeism\tfear\t0\nabsenteeism\tjoy\t0\nabsenteeism\tnegative\t1\nabsenteeism\tpositive\t0\nabsenteeism\tsadness\t0\nabsenteeism\tsurprise\t0\nabsenteeism\ttrust\t0\nabsinthe\tanger\t0\nabsinthe\tanticipation\t0\nabsinthe\tdisgust\t0\nabsinthe\tfear\t0\nabsinthe\tjoy\t0\nabsinthe\tnegative\t0\nabsinthe\tpositive\t0\nabsinthe\tsadness\t0\nabsinthe\tsurprise\t0\nabsinthe\ttrust\t0\nabsolute\tanger\t0\nabsolute\tanticipation\t0\nabsolute\tdisgust\t0\nabsolute\tfear\t0\nabsolute\tjoy\t0\nabsolute\tnegative\t0\nabsolute\tpositive\t1\nabsolute\tsadness\t0\nabsolute\tsurprise\t0\nabsolute\ttrust\t0\nabsolution\tanger\t0\nabsolution\tanticipation\t0\nabsolution\tdisgust\t0\nabsolution\tfear\t0\nabsolution\tjoy\t1\nabsolution\tnegative\t0\nabsolution\tpositive\t1\nabsolution\tsadness\t0\nabsolution\tsurprise\t0\nabsolution\ttrust\t1\nabsorbed\tanger\t0\nabsorbed\tanticipation\t0\nabsorbed\tdisgust\t0\nabsorbed\tfear\t0\nabsorbed\tjoy\t0\nabsorbed\tnegative\t0\nabsorbed\tpositive\t1\nabsorbed\tsadness\t0\nabsorbed\tsurprise\t0\nabsorbed\ttrust\t0\nabsorbent\tanger\t0\nabsorbent\tanticipation\t0\nabsorbent\tdisgust\t0\nabsorbent\tfear\t0\nabsorbent\tjoy\t0\nabsorbent\tnegative\t0\nabsorbent\tpositive\t0\nabsorbent\tsadness\t0\nabsorbent\tsurprise\t0\nabsorbent\ttrust\t0\nabsorbing\tanger\t0\nabsorbing\tanticipation\t0\nabsorbing\tdisgust\t0\nabsorbing\tfear\t0\nabsorbing\tjoy\t0\nabsorbing\tnegative\t0\nabsorbing\tpositive\t0\nabsorbing\tsadness\t0\nabsorbing\tsurprise\t0\nabsorbing\ttrust\t0\nabsorption\tanger\t0\nabsorption\tanticipation\t0\nabsorption\tdisgust\t0\nabsorption\tfear\t0\nabsorption\tjoy\t0\nabsorption\tnegative\t0\nabsorption\tpositive\t0\nabsorption\tsadness\t0\nabsorption\tsurprise\t0\nabsorption\ttrust\t0\nabstain\tanger\t0\nabstain\tanticipation\t0\nabstain\tdisgust\t0\nabstain\tfear\t0\nabstain\tjoy\t0\nabstain\tnegative\t0\nabstain\tpositive\t0\nabstain\tsadness\t0\nabstain\tsurprise\t0\nabstain\ttrust\t0\nabstention\tanger\t0\nabstention\tanticipation\t0\nabstention\tdisgust\t0\nabstention\tfear\t0\nabstention\tjoy\t0\nabstention\tnegative\t0\nabstention\tpositive\t0\nabstention\tsadness\t0\nabstention\tsurprise\t0\nabstention\ttrust\t0\nabstinence\tanger\t0\nabstinence\tanticipation\t0\nabstinence\tdisgust\t0\nabstinence\tfear\t0\nabstinence\tjoy\t0\nabstinence\tnegative\t0\nabstinence\tpositive\t0\nabstinence\tsadness\t0\nabstinence\tsurprise\t0\nabstinence\ttrust\t0\nabstract\tanger\t0\nabstract\tanticipation\t0\nabstract\tdisgust\t0\nabstract\tfear\t0\nabstract\tjoy\t0\nabstract\tnegative\t0\nabstract\tpositive\t0\nabstract\tsadness\t0\nabstract\tsurprise\t0\nabstract\ttrust\t0\nabstraction\tanger\t0\nabstraction\tanticipation\t0\nabstraction\tdisgust\t0\nabstraction\tfear\t0\nabstraction\tjoy\t0\nabstraction\tnegative\t0\nabstraction\tpositive\t0\nabstraction\tsadness\t0\nabstraction\tsurprise\t0\nabstraction\ttrust\t0\nabsurd\tanger\t0\nabsurd\tanticipation\t0\nabsurd\tdisgust\t0\nabsurd\tfear\t0\nabsurd\tjoy\t0\nabsurd\tnegative\t1\nabsurd\tpositive\t0\nabsurd\tsadness\t0\nabsurd\tsurprise\t0\nabsurd\ttrust\t0\nabsurdity\tanger\t0\nabsurdity\tanticipation\t0\nabsurdity\tdisgust\t0\nabsurdity\tfear\t0\nabsurdity\tjoy\t0\nabsurdity\tnegative\t1\nabsurdity\tpositive\t0\nabsurdity\tsadness\t0\nabsurdity\tsurprise\t0\nabsurdity\ttrust\t0\nabundance\tanger\t0\nabundance\tanticipation\t1\nabundance\tdisgust\t1\nabundance\tfear\t0\nabundance\tjoy\t1\nabundance\tnegative\t1\nabundance\tpositive\t1\nabundance\tsadness\t0\nabundance\tsurprise\t0\nabundance\ttrust\t1\nabundant\tanger\t0\nabundant\tanticipation\t0\nabundant\tdisgust\t0\nabundant\tfear\t0\nabundant\tjoy\t1\nabundant\tnegative\t0\nabundant\tpositive\t1\nabundant\tsadness\t0\nabundant\tsurprise\t0\nabundant\ttrust\t0\nabuse\tanger\t1\nabuse\tanticipation\t0\nabuse\tdisgust\t1\nabuse\tfear\t1\nabuse\tjoy\t0\nabuse\tnegative\t1\nabuse\tpositive\t0\nabuse\tsadness\t1\nabuse\tsurprise\t0\nabuse\ttrust\t0\nabutment\tanger\t0\nabutment\tanticipation\t0\nabutment\tdisgust\t0\nabutment\tfear\t0\nabutment\tjoy\t0\nabutment\tnegative\t0\nabutment\tpositive\t0\nabutment\tsadness\t0\nabutment\tsurprise\t0\nabutment\ttrust\t0\naby\tanger\t0\naby\tanticipation\t0\naby\tdisgust\t0\naby\tfear\t0\naby\tjoy\t0\naby\tnegative\t0\naby\tpositive\t0\naby\tsadness\t0\naby\tsurprise\t0\naby\ttrust\t0\nabysmal\tanger\t0\nabysmal\tanticipation\t0\nabysmal\tdisgust\t0\nabysmal\tfear\t0\nabysmal\tjoy\t0\nabysmal\tnegative\t1\nabysmal\tpositive\t0\nabysmal\tsadness\t1\nabysmal\tsurprise\t0\nabysmal\ttrust\t0\nabyss\tanger\t0\nabyss\tanticipation\t0\nabyss\tdisgust\t0\nabyss\tfear\t1\nabyss\tjoy\t0\nabyss\tnegative\t1\nabyss\tpositive\t0\nabyss\tsadness\t1\nabyss\tsurprise\t0\nabyss\ttrust\t0\nacademic\tanger\t0\nacademic\tanticipation\t0\nacademic\tdisgust\t0\nacademic\tfear\t0\nacademic\tjoy\t0\nacademic\tnegative\t0\nacademic\tpositive\t1\nacademic\tsadness\t0\nacademic\tsurprise\t0\nacademic\ttrust\t1\nacademy\tanger\t0\nacademy\tanticipation\t0\nacademy\tdisgust\t0\nacademy\tfear\t0\nacademy\tjoy\t0\nacademy\tnegative\t0\nacademy\tpositive\t1\nacademy\tsadness\t0\n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amant\tjoy\t0\nadamant\tnegative\t0\nadamant\tpositive\t0\nadamant\tsadness\t0\nadamant\tsurprise\t0\nadamant\ttrust\t0\nadapt\tanger\t0\nadapt\tanticipation\t0\nadapt\tdisgust\t0\nadapt\tfear\t0\nadapt\tjoy\t0\nadapt\tnegative\t0\nadapt\tpositive\t1\nadapt\tsadness\t0\nadapt\tsurprise\t0\nadapt\ttrust\t0\nadaptable\tanger\t0\nadaptable\tanticipation\t0\nadaptable\tdisgust\t0\nadaptable\tfear\t0\nadaptable\tjoy\t0\nadaptable\tnegative\t0\nadaptable\tpositive\t1\nadaptable\tsadness\t0\nadaptable\tsurprise\t0\nadaptable\ttrust\t0\nadd\tanger\t0\nadd\tanticipation\t0\nadd\tdisgust\t0\nadd\tfear\t0\nadd\tjoy\t0\nadd\tnegative\t0\nadd\tpositive\t0\nadd\tsadness\t0\nadd\tsurprise\t0\nadd\ttrust\t0\nadded\tanger\t0\nadded\tanticipation\t0\nadded\tdisgust\t0\nadded\tfear\t0\nadded\tjoy\t0\nadded\tnegative\t0\nadded\tpositive\t0\nadded\tsadness\t0\nadded\tsurprise\t0\nadded\ttrust\t0\naddendum\tanger\t0\naddendum\tanticipation\t0\naddendum\tdisgust\t0\naddendum\tfear\t0\naddendum\tjoy\t0\naddendum\tnegative\t0\naddendum\tpositive\t0\naddendum\tsadness\t0\naddendum\tsurprise\t0\naddendum\ttrust\t0\nadder\tanger\t1\nadder\tanticipation\t0\nadder\tdisgust\t1\nadder\tfear\t1\nadder\tjoy\t0\nadder\tnegative\t1\nadder\tpositive\t0\nadder\tsadness\t1\nadder\tsurprise\t0\nadder\ttrust\t0\naddiction\tanger\t0\naddiction\tanticipation\t0\naddiction\tdisgust\t0\naddiction\tfear\t0\naddiction\tjoy\t0\naddiction\tnegative\t1\naddiction\tpositive\t0\naddiction\tsadness\t0\naddiction\tsurprise\t0\naddiction\ttrust\t0\naddition\tanger\t0\naddition\tanticipation\t0\naddition\tdisgust\t0\naddition\tfear\t0\naddition\tjoy\t0\naddition\tnegative\t0\naddition\tpositive\t0\naddition\tsadness\t0\naddition\tsurprise\t0\naddition\ttrust\t0\nadditional\tanger\t0\nadditional\tanticipation\t0\nadditional\tdisgust\t0\nadditional\tfear\t0\nadditional\tjoy\t0\nadditional\tnegative\t0\nadditional\tpositive\t0\nadditional\tsadness\t0\nadditional\tsurprise\t0\nadditional\ttrust\t0\nadditive\tanger\t0\nadditive\tanticipation\t0\nadditive\tdisgust\t0\nadditive\tfear\t0\nadditive\tjoy\t0\nadditive\tnegative\t0\nadditive\tpositive\t0\nadditive\tsadness\t0\nadditive\tsurprise\t0\nadditive\ttrust\t0\naddress\tanger\t0\naddress\tanticipation\t0\naddress\tdisgust\t0\naddress\tfear\t0\naddress\tjoy\t0\naddress\tnegative\t0\naddress\tpositive\t0\naddress\tsadness\t0\naddress\tsurprise\t0\naddress\ttrust\t0\naddressee\tanger\t0\naddressee\tanticipation\t0\naddressee\tdisgust\t0\naddressee\tfear\t0\naddressee\tjoy\t0\naddressee\tnegative\t0\naddressee\tpositive\t0\naddressee\tsadness\t0\naddressee\tsurprise\t0\naddressee\ttrust\t0\naddresses\tanger\t0\naddresses\tanticipation\t1\naddresses\tdisgust\t0\naddresses\tfear\t0\naddresses\tjoy\t0\naddresses\tnegative\t0\naddresses\tpositive\t1\naddresses\tsadness\t0\naddresses\tsurprise\t0\naddresses\ttrust\t0\nadept\tanger\t0\nadept\tanticipation\t0\nadept\tdisgust\t0\nadept\tfear\t0\nadept\tjoy\t0\nadept\tnegative\t0\nadept\tpositive\t1\nadept\tsadness\t0\nadept\tsurprise\t0\nadept\ttrust\t0\nadequacy\tanger\t0\nadequacy\tanticipation\t0\nadequacy\tdisgust\t0\nadequacy\tfear\t0\nadequacy\tjoy\t0\nadequacy\tnegative\t0\nadequacy\tpositive\t1\nadequacy\tsadness\t0\nadequacy\tsurprise\t0\nadequacy\ttrust\t0\nadequate\tanger\t0\nadequate\tanticipation\t0\nadequate\tdisgust\t0\nadequate\tfear\t0\nadequate\tjoy\t0\nadequate\tnegative\t0\nadequate\tpositive\t0\nadequate\tsadness\t0\nadequate\tsurprise\t0\nadequate\ttrust\t0\nadhere\tanger\t0\nadhere\tanticipation\t0\nadhere\tdisgust\t0\nadhere\tfear\t0\nadhere\tjoy\t0\nadhere\tnegative\t0\nadhere\tpositive\t0\nadhere\tsadness\t0\nadhere\tsurprise\t0\nadhere\ttrust\t0\nadherence\tanger\t0\nadherence\tanticipation\t0\nadherence\tdisgust\t0\nadherence\tfear\t0\nadherence\tjoy\t0\nadherence\tnegative\t0\nadherence\tpositive\t0\nadherence\tsadness\t0\nadherence\tsurprise\t0\nadherence\ttrust\t0\nadherent\tanger\t0\nadherent\tanticipation\t0\nadherent\tdisgust\t0\nadherent\tfear\t0\nadherent\tjoy\t0\nadherent\tnegative\t0\nadherent\tpositive\t0\nadherent\tsadness\t0\nadherent\tsurprise\t0\nadherent\ttrust\t0\nadhering\tanger\t0\nadhering\tanticipation\t0\nadhering\tdisgust\t0\nadhering\tfear\t0\nadhering\tjoy\t0\nadhering\tnegative\t0\nadhering\tpositive\t0\nadhering\tsadness\t0\nadhering\tsurprise\t0\nadhering\ttrust\t1\nadhesion\tanger\t0\nadhesion\tanticipation\t0\nadhesion\tdisgust\t0\nadhesion\tfear\t0\nadhesion\tjoy\t0\nadhesion\tnegative\t0\nadhesion\tpositive\t0\nadhesion\tsadness\t0\nadhesion\tsurprise\t0\nadhesion\ttrust\t0\nadhesive\tanger\t0\nadhesive\tanticipation\t0\nadhesive\tdisgust\t0\nadhesive\tfear\t0\nadhesive\tjoy\t0\nadhesive\tnegative\t0\nadhesive\tpositive\t0\nadhesive\tsadness\t0\nadhesive\tsurprise\t0\nadhesive\ttrust\t0\nadieu\tanger\t0\nadieu\tanticipation\t0\nadieu\tdisgust\t0\nadieu\tfear\t0\nadieu\tjoy\t0\nadieu\tnegative\t0\nadieu\tpositive\t0\nadieu\tsadness\t0\nadieu\tsurprise\t0\nadieu\ttrust\t0\nadipose\tanger\t0\nadipose\tanticipation\t0\nadi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fterthought\ttrust\t0\naga\tanger\t0\naga\tanticipation\t0\naga\tdisgust\t0\naga\tfear\t1\naga\tjoy\t0\naga\tnegative\t0\naga\tpositive\t1\naga\tsadness\t0\naga\tsurprise\t0\naga\ttrust\t1\nagate\tanger\t0\nagate\tanticipation\t0\nagate\tdisgust\t0\nagate\tfear\t0\nagate\tjoy\t0\nagate\tnegative\t0\nagate\tpositive\t0\nagate\tsadness\t0\nagate\tsurprise\t0\nagate\ttrust\t0\nage\tanger\t0\nage\tanticipation\t0\nage\tdisgust\t0\nage\tfear\t0\nage\tjoy\t0\nage\tnegative\t0\nage\tpositive\t0\nage\tsadness\t0\nage\tsurprise\t0\nage\ttrust\t0\naged\tanger\t0\naged\tanticipation\t0\naged\tdisgust\t0\naged\tfear\t0\naged\tjoy\t0\naged\tnegative\t0\naged\tpositive\t0\naged\tsadness\t0\naged\tsurprise\t0\naged\ttrust\t0\nagency\tanger\t0\nagency\tanticipation\t0\nagency\tdisgust\t0\nagency\tfear\t0\nagency\tjoy\t0\nagency\tnegative\t0\nagency\tpositive\t0\nagency\tsadness\t0\nagency\tsurprise\t0\nagency\ttrust\t0\nagent\tanger\t0\nagent\tanticipation\t0\nagent\tdisgust\t0\nagent\tfear\t0\nagent\tjoy\t0\nagent\tnegative\t0\nagent\tpositive\t0\nagent\tsadness\t0\nagent\tsurprise\t0\nagent\ttrust\t0\nagglomeration\tanger\t0\nagglomeration\tanticipation\t0\nagglomeration\tdisgust\t0\nagglomeration\tfear\t0\nagglomeration\tjoy\t0\nagglomeration\tnegative\t0\nagglomeration\tpositive\t0\nagglomeration\tsadness\t0\nagglomeration\tsurprise\t0\nagglomeration\ttrust\t0\naggravated\tanger\t1\naggravated\tanticipation\t0\naggravated\tdisgust\t0\naggravated\tfear\t0\naggravated\tjoy\t0\naggravated\tnegative\t1\naggravated\tpositive\t0\naggravated\tsadness\t0\naggravated\tsurprise\t0\naggravated\ttrust\t0\naggravating\tanger\t1\naggravating\tanticipation\t0\naggravating\tdisgust\t0\naggravating\tfear\t0\naggravating\tjoy\t0\naggravating\tnegative\t1\naggravating\tpositive\t0\naggravating\tsadness\t1\naggravating\tsurprise\t0\naggravating\ttrust\t0\naggravation\tanger\t1\naggravation\tanticipation\t0\naggravation\tdisgust\t1\naggravation\tfear\t0\naggravation\tjoy\t0\naggravation\tnegative\t1\naggravation\tpositive\t0\naggravation\tsadness\t0\naggravation\tsurprise\t0\naggravation\ttrust\t0\naggregate\tanger\t0\naggregate\tanticipation\t0\naggregate\tdisgust\t0\naggregate\tfear\t0\naggregate\tjoy\t0\naggregate\tnegative\t0\naggregate\tpositive\t0\naggregate\tsadness\t0\naggregate\tsurprise\t0\naggregate\ttrust\t0\naggregation\tanger\t0\naggregation\tanticipation\t0\naggregation\tdisgust\t0\naggregation\tfear\t0\naggregation\tjoy\t0\naggregation\tnegative\t0\naggregation\tpositive\t0\naggregation\tsadness\t0\naggregation\tsurprise\t0\naggregation\ttrust\t0\naggression\tanger\t1\naggression\tanticipation\t0\naggression\tdisgust\t0\naggression\tfear\t1\naggression\tjoy\t0\naggression\tnegative\t1\naggression\tpositive\t0\naggression\tsadness\t0\naggression\tsurprise\t0\naggression\ttrust\t0\naggressive\tanger\t1\naggressive\tanticipation\t0\naggressive\tdisgust\t0\naggressive\tfear\t1\naggressive\tjoy\t0\naggressive\tnegative\t1\naggressive\tpositive\t0\naggressive\tsadness\t0\naggressive\tsurprise\t0\naggressive\ttrust\t0\naggressor\tanger\t1\naggressor\tanticipation\t0\naggressor\tdisgust\t0\naggressor\tfear\t1\naggressor\tjoy\t0\naggressor\tnegative\t1\naggressor\tpositive\t0\naggressor\tsadness\t0\naggressor\tsurprise\t0\naggressor\ttrust\t0\naghast\tanger\t0\naghast\tanticipation\t0\naghast\tdisgust\t1\naghast\tfear\t1\naghast\tjoy\t0\naghast\tnegative\t1\naghast\tpositive\t0\naghast\tsadness\t0\naghast\tsurprise\t1\naghast\ttrust\t0\nagile\tanger\t0\nagile\tanticipation\t0\nagile\tdisgust\t0\nagile\tfear\t0\nagile\tjoy\t0\nagile\tnegative\t0\nagile\tpositive\t1\nagile\tsadness\t0\nagile\tsurprise\t0\nagile\ttrust\t0\nagility\tanger\t0\nagility\tanticipation\t0\nagility\tdisgust\t0\nagility\tfear\t0\nagility\tjoy\t0\nagility\tnegative\t0\nagility\tpositive\t1\nagility\tsadness\t0\nagility\tsurprise\t0\nagility\ttrust\t0\nagitated\tanger\t1\nagitated\tanticipation\t0\nagitated\tdisgust\t0\nagitated\tfear\t0\nagitated\tjoy\t0\nagitated\tnegative\t1\nagitated\tpositive\t0\nagitated\tsadness\t0\nagitated\tsurprise\t0\nagitated\ttrust\t0\nagitation\tanger\t1\nagitation\tanticipation\t0\nagitation\tdisgust\t0\nagitation\tfear\t0\nagitation\tjoy\t0\nagitation\tnegative\t1\nagitation\tpositive\t0\nagitation\tsadness\t0\nagitation\tsurprise\t0\nagitation\ttrust\t0\nagnostic\tanger\t0\nagnostic\tanticipation\t0\nagnostic\tdisgust\t0\nagnostic\tfear\t0\nagnostic\tjoy\t0\nagnostic\tnegative\t0\nagnostic\tpositive\t0\nagnostic\tsadness\t0\nagnostic\tsurprise\t0\nagnostic\ttrust\t0\nago\tanger\t0\nago\tanticipation\t0\nago\tdisgust\t0\nago\tfear\t0\nago\tjoy\t0\nago\tnegative\t0\nago\tpositive\t0\nago\tsadness\t0\nago\tsurprise\t0\nago\ttrust\t0\nagonizing\tanger\t0\nagonizing\tanticipation\t0\nagonizing\tdisgust\t0\nagonizing\tfear\t1\nagonizing\tjoy\t0\nagonizing\tnegative\t1\nagonizing\tpositive\t0\nagonizing\tsadness\t0\nagonizing\tsurprise\t0\nagonizing\ttrust\t0\nagony\tanger\t1\nagony\tanticipation\t0\nagony\tdisgust\t0\nagony\tfear\t1\n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ar\t0\nalphabetical\tjoy\t0\nalphabetical\tnegative\t0\nalphabetical\tpositive\t0\nalphabetical\tsadness\t0\nalphabetical\tsurprise\t0\nalphabetical\ttrust\t0\naltar\tanger\t0\naltar\tanticipation\t0\naltar\tdisgust\t0\naltar\tfear\t0\naltar\tjoy\t0\naltar\tnegative\t0\naltar\tpositive\t0\naltar\tsadness\t0\naltar\tsurprise\t0\naltar\ttrust\t0\nalter\tanger\t0\nalter\tanticipation\t0\nalter\tdisgust\t0\nalter\tfear\t0\nalter\tjoy\t0\nalter\tnegative\t0\nalter\tpositive\t0\nalter\tsadness\t0\nalter\tsurprise\t0\nalter\ttrust\t0\nalteration\tanger\t0\nalteration\tanticipation\t0\nalteration\tdisgust\t0\nalteration\tfear\t0\nalteration\tjoy\t0\nalteration\tnegative\t0\nalteration\tpositive\t0\nalteration\tsadness\t0\nalteration\tsurprise\t0\nalteration\ttrust\t0\naltercation\tanger\t1\naltercation\tanticipation\t0\naltercation\tdisgust\t0\naltercation\tfear\t0\naltercation\tjoy\t0\naltercation\tnegative\t1\naltercation\tpositive\t0\naltercation\tsadness\t0\naltercation\tsurprise\t0\naltercation\ttrust\t0\naltered\tanger\t0\naltered\tanticipation\t0\naltered\tdisgust\t0\naltered\tfear\t0\naltered\tjoy\t0\naltered\tnegative\t0\naltered\tpositive\t0\naltered\tsadness\t0\naltered\tsurprise\t0\naltered\ttrust\t0\nalternate\tanger\t0\nalternate\tanticipation\t0\nalternate\tdisgust\t0\nalternate\tfear\t0\nalternate\tjoy\t0\nalternate\tnegative\t0\nalternate\tpositive\t0\nalternate\tsadness\t0\nalternate\tsurprise\t0\nalternate\ttrust\t0\nalternative\tanger\t0\nalternative\tanticipation\t0\nalternative\tdisgust\t0\nalternative\tfear\t0\nalternative\tjoy\t0\nalternative\tnegative\t0\nalternative\tpositive\t0\nalternative\tsadness\t0\nalternative\tsurprise\t0\nalternative\ttrust\t0\naltitude\tanger\t0\naltitude\tanticipation\t0\naltitude\tdisgust\t0\naltitude\tfear\t0\naltitude\tjoy\t0\naltitude\tnegative\t0\naltitude\tpositive\t0\naltitude\tsadness\t0\naltitude\tsurprise\t0\naltitude\ttrust\t0\nalto\tanger\t0\nalto\tanticipation\t0\nalto\tdisgust\t0\nalto\tfear\t0\nalto\tjoy\t0\nalto\tnegative\t0\nalto\tpositive\t0\nalto\tsadness\t0\nalto\tsurprise\t0\nalto\ttrust\t0\naltogether\tanger\t0\naltogether\tanticipation\t0\naltogether\tdisgust\t0\naltogether\tfear\t0\naltogether\tjoy\t0\naltogether\tnegative\t0\naltogether\tpositive\t0\naltogether\tsadness\t0\naltogether\tsurprise\t0\naltogether\ttrust\t0\nalumnus\tanger\t0\nalumnus\tanticipation\t0\nalumnus\tdisgust\t0\nalumnus\tfear\t0\nalumnus\tjoy\t0\nalumnus\tnegative\t0\nalumnus\tpositive\t0\nalumnus\tsadness\t0\nalumnus\tsurprise\t0\nalumnus\ttrust\t0\nalveolar\tanger\t0\nalveolar\tanticipation\t0\nalveolar\tdisgust\t0\nalveolar\tfear\t0\nalveolar\tjoy\t0\nalveolar\tnegative\t0\nalveolar\tpositive\t0\nalveolar\tsadness\t0\nalveolar\tsurprise\t0\nalveolar\ttrust\t0\namalgam\tanger\t0\namalgam\tanticipation\t0\namalgam\tdisgust\t0\namalgam\tfear\t0\namalgam\tjoy\t0\namalgam\tnegative\t0\namalgam\tpositive\t0\namalgam\tsadness\t0\namalgam\tsurprise\t0\namalgam\ttrust\t0\namalgamation\tanger\t0\namalgamation\tanticipation\t0\namalgamation\tdisgust\t0\namalgamation\tfear\t0\namalgamation\tjoy\t0\namalgamation\tnegative\t0\namalgamation\tpositive\t0\namalgamation\tsadness\t0\namalgamation\tsurprise\t0\namalgamation\ttrust\t0\namass\tanger\t0\namass\tanticipation\t0\namass\tdisgust\t0\namass\tfear\t0\namass\tjoy\t0\namass\tnegative\t0\namass\tpositive\t0\namass\tsadness\t0\namass\tsurprise\t0\namass\ttrust\t0\namateur\tanger\t0\namateur\tanticipation\t0\namateur\tdisgust\t0\namateur\tfear\t0\namateur\tjoy\t0\namateur\tnegative\t0\namateur\tpositive\t0\namateur\tsadness\t0\namateur\tsurprise\t0\namateur\ttrust\t0\namaze\tanger\t0\namaze\tanticipation\t0\namaze\tdisgust\t0\namaze\tfear\t0\namaze\tjoy\t0\namaze\tnegative\t0\namaze\tpositive\t0\namaze\tsadness\t0\namaze\tsurprise\t1\namaze\ttrust\t0\namazement\tanger\t0\namazement\tanticipation\t0\namazement\tdisgust\t0\namazement\tfear\t0\namazement\tjoy\t0\namazement\tnegative\t0\namazement\tpositive\t0\namazement\tsadness\t0\namazement\tsurprise\t0\namazement\ttrust\t0\namazingly\tanger\t0\namazingly\tanticipation\t0\namazingly\tdisgust\t0\namazingly\tfear\t0\namazingly\tjoy\t1\namazingly\tnegative\t0\namazingly\tpositive\t1\namazingly\tsadness\t0\namazingly\tsurprise\t1\namazingly\ttrust\t0\nambassador\tanger\t0\nambassador\tanticipation\t0\nambassador\tdisgust\t0\nambassador\tfear\t0\nambassador\tjoy\t0\nambassador\tnegative\t0\nambassador\tpositive\t1\nambassador\tsadness\t0\nambassador\tsurprise\t0\nambassador\ttrust\t1\namber\tanger\t0\namber\tanticipation\t0\namber\tdisgust\t0\namber\tfear\t0\namber\tjoy\t0\namber\tnegative\t0\namber\tpositive\t0\namber\tsadness\t0\namber\tsurprise\t0\namber\ttrust\t0\nambient\tanger\t0\nambient\tanticipation\t0\nambient\tdisgust\t0\nambient\tfear\t0\nambient\tjoy\t0\nambient\tnegative\t0\nambient\tpositive\t0\nambient\tsadness\t0\nambient\tsurprise\t0\nambient\ttrust\t0\nambiguity\tanger\t0\nambiguity\tanticipation\t0\nambiguity\tdisgust\t0\nambiguity\tfear\t0\nambiguity\tjoy\t0\nambiguity\tnegative\t0\nambiguity\tpositive\t0\nambiguity\tsadness\t0\nambiguity\tsurprise\t0\nambiguity\ttrust\t0\nambiguous\tanger\t0\nambiguous\tanticipation\t0\nambiguous\tdisgust\t0\nambiguous\tfear\t0\nambiguous\tjoy\t0\nambiguous\tnegative\t1\nambiguous\tpositive\t0\nambiguous\tsadness\t0\nambiguous\tsurprise\t0\nambiguous\ttrust\t0\nambit\tanger\t0\nambit\tanticipation\t0\nambit\tdisgust\t0\nambit\tfear\t0\nambit\tjoy\t0\nambit\tnegative\t0\nambit\tpositive\t0\nambit\tsadness\t0\nambit\tsurprise\t0\nambit\ttrust\t0\nambition\tanger\t0\nambition\tanticipation\t1\nambition\tdisgust\t0\nambition\tfear\t0\nambition\tjoy\t1\nambition\tnegative\t0\nambition\tpositive\t1\nambition\tsadness\t0\nambition\tsurprise\t0\nambition\ttrust\t1\nambitious\tanger\t0\nambitious\tanticipation\t0\nambitious\tdisgust\t0\nambitious\tfear\t0\nambitious\tjoy\t0\nambitious\tnegative\t0\nambitious\tpositive\t0\nambitious\tsadness\t0\nambitious\tsurprise\t0\nambitious\ttrust\t0\nambulance\tanger\t0\nambulance\tanticipation\t0\nambulance\tdisgust\t0\nambulance\tfear\t1\nambulance\tjoy\t0\nambulance\tnegative\t0\nambulance\tpositive\t0\nambulance\tsadness\t0\nambulance\tsurprise\t0\nambulance\ttrust\t1\nambush\tanger\t1\nambush\tanticipation\t0\nambush\tdisgust\t0\nambush\tfear\t1\nambush\tjoy\t0\nambush\tnegative\t1\nambush\tpositive\t0\nambush\tsadness\t0\nambush\tsurprise\t1\nambush\ttrust\t0\nameliorate\tanger\t0\nameliorate\tanticipation\t0\nameliorate\tdisgust\t0\nameliorate\tfear\t0\nameliorate\tjoy\t0\nameliorate\tnegative\t0\nameliorate\tpositive\t1\nameliorate\tsadness\t0\nameliorate\tsurprise\t0\nameliorate\ttrust\t0\namen\tanger\t0\namen\tanticipation\t0\namen\tdisgust\t0\namen\tfear\t0\namen\tjoy\t1\namen\tnegative\t0\namen\tpositive\t1\namen\tsadness\t0\namen\tsurprise\t0\namen\ttrust\t1\namenable\tanger\t0\namenable\tanticipation\t0\namenable\tdisgust\t0\namenable\tfear\t0\namenable\tjoy\t0\namenable\tnegative\t0\namenable\tpositive\t1\namenable\tsadness\t0\namenable\tsurprise\t0\namenable\ttrust\t0\namend\tanger\t0\namend\tanticipation\t0\namend\tdisgust\t0\namend\tfear\t0\namend\tjoy\t0\namend\tnegative\t0\namend\tpositive\t1\namend\tsadness\t0\namend\tsurprise\t0\namend\ttrust\t0\namendment\tanger\t0\namendment\tanticipation\t0\namendment\tdisgust\t0\namendment\tfear\t0\namendment\tjoy\t0\namendment\tnegative\t0\namendment\tpositive\t0\namendment\tsadness\t0\namendment\tsurprise\t0\namendment\ttrust\t0\namends\tanger\t0\namends\tanticipation\t0\namends\tdisgust\t0\namends\tfear\t0\namends\tjoy\t0\namends\tnegative\t0\namends\tpositive\t1\namends\tsadness\t0\namends\tsurprise\t0\namends\ttrust\t0\namenity\tanger\t0\namenity\tanticipation\t0\namenity\tdisgust\t0\namenity\tfear\t0\namenity\tjoy\t0\namenity\tnegative\t0\namenity\tpositive\t1\namenity\tsadness\t0\namenity\tsurprise\t0\namenity\ttrust\t0\namethyst\tanger\t0\namethyst\tanticipation\t0\namethyst\tdisgust\t0\namethyst\tfear\t0\namethyst\tjoy\t0\namethyst\tnegative\t0\namethyst\tpositive\t0\namethyst\tsadness\t0\namethyst\tsurprise\t0\namethyst\ttrust\t0\namiable\tanger\t0\namiable\tanticipation\t0\namiable\tdisgust\t0\namiable\tfear\t0\namiable\tjoy\t0\namiable\tnegative\t0\namiable\tpositive\t1\namiable\tsadness\t0\namiable\tsurprise\t0\namiable\ttrust\t0\namicable\tanger\t0\namicable\tanticipation\t0\namicable\tdisgust\t0\namicable\tfear\t0\namicable\tjoy\t1\namicable\tnegative\t0\namicable\tpositive\t1\namicable\tsadness\t0\namicable\tsurprise\t0\namicable\ttrust\t0\namid\tanger\t0\namid\tanticipation\t0\namid\tdisgust\t0\namid\tfear\t0\namid\tjoy\t0\namid\tnegative\t0\namid\tpositive\t0\namid\tsadness\t0\namid\tsurprise\t0\namid\ttrust\t0\namidst\tanger\t0\namidst\tanticipation\t0\namidst\tdisgust\t0\namidst\tfear\t0\namidst\tjoy\t0\namidst\tnegative\t0\namidst\tpositive\t0\namidst\tsadness\t0\namidst\tsurprise\t0\namidst\ttrust\t0\nammonia\tanger\t0\nammonia\tanticipation\t0\nammonia\tdisgust\t1\nammonia\tfear\t0\nammonia\tjoy\t0\nammonia\tnegative\t0\nammonia\tpositive\t0\nammonia\tsadness\t0\nammonia\tsurprise\t0\nammonia\ttrust\t0\nammunition\tanger\t0\nammunition\tanticipation\t0\nammunition\tdisgust\t0\nammunition\tfear\t0\nammunition\tjoy\t0\nammunition\tnegative\t0\nammunition\tpositive\t0\nammunition\tsadness\t0\nammunition\tsurprise\t0\nammunition\ttrust\t0\namnesia\tanger\t0\namnesia\tanticipation\t0\namnesia\tdisgust\t0\namnesia\tfear\t0\namnesia\tjoy\t0\namnesia\tnegative\t1\namnesia\tpositive\t0\namnesia\tsadness\t0\namnesia\tsurprise\t0\namnesia\ttrust\t0\namnesty\tanger\t0\namnesty\tanticipation\t0\namnesty\tdisgust\t0\namnesty\tfear\t0\namnesty\tjoy\t1\namnesty\tnegative\t0\namnesty\tpositive\t1\namnesty\tsadness\t0\namnesty\tsurprise\t0\namnesty\ttrust\t0\namorphous\tanger\t0\namorphous\tanticipation\t0\namorphous\tdisgust\t0\namorphous\tfear\t0\namorphous\tjoy\t0\namorphous\tnegative\t0\namorphous\tpositive\t0\namorphous\tsadness\t0\namorphous\tsurprise\t0\namorphous\ttrust\t0\namortization\tanger\t0\namortization\tanticipation\t0\namo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se\t0\navocado\ttrust\t0\navoid\tanger\t0\navoid\tanticipation\t0\navoid\tdisgust\t0\navoid\tfear\t1\navoid\tjoy\t0\navoid\tnegative\t1\navoid\tpositive\t0\navoid\tsadness\t0\navoid\tsurprise\t0\navoid\ttrust\t0\navoidance\tanger\t0\navoidance\tanticipation\t0\navoidance\tdisgust\t0\navoidance\tfear\t1\navoidance\tjoy\t0\navoidance\tnegative\t1\navoidance\tpositive\t0\navoidance\tsadness\t0\navoidance\tsurprise\t0\navoidance\ttrust\t0\navoiding\tanger\t0\navoiding\tanticipation\t0\navoiding\tdisgust\t0\navoiding\tfear\t1\navoiding\tjoy\t0\navoiding\tnegative\t0\navoiding\tpositive\t0\navoiding\tsadness\t0\navoiding\tsurprise\t0\navoiding\ttrust\t0\nawait\tanger\t0\nawait\tanticipation\t1\nawait\tdisgust\t0\nawait\tfear\t0\nawait\tjoy\t0\nawait\tnegative\t0\nawait\tpositive\t0\nawait\tsadness\t0\nawait\tsurprise\t0\nawait\ttrust\t0\nawake\tanger\t0\nawake\tanticipation\t0\nawake\tdisgust\t0\nawake\tfear\t0\nawake\tjoy\t0\nawake\tnegative\t0\nawake\tpositive\t0\nawake\tsadness\t0\nawake\tsurprise\t0\nawake\ttrust\t0\nawaken\tanger\t0\nawaken\tanticipation\t0\nawaken\tdisgust\t0\nawaken\tfear\t0\nawaken\tjoy\t0\nawaken\tnegative\t0\nawaken\tpositive\t0\nawaken\tsadness\t0\nawaken\tsurprise\t0\nawaken\ttrust\t0\naward\tanger\t0\naward\tanticipation\t1\naward\tdisgust\t0\naward\tfear\t0\naward\tjoy\t1\naward\tnegative\t0\naward\tpositive\t1\naward\tsadness\t0\naward\tsurprise\t1\naward\ttrust\t1\nawe\tanger\t0\nawe\tanticipation\t0\nawe\tdisgust\t0\nawe\tfear\t0\nawe\tjoy\t0\nawe\tnegative\t0\nawe\tpositive\t0\nawe\tsadness\t0\nawe\tsurprise\t0\nawe\ttrust\t0\nawful\tanger\t1\nawful\tanticipation\t0\nawful\tdisgust\t1\nawful\tfear\t1\nawful\tjoy\t0\nawful\tnegative\t1\nawful\tpositive\t0\nawful\tsadness\t1\nawful\tsurprise\t0\nawful\ttrust\t0\nawkwardness\tanger\t0\nawkwardness\tanticipation\t0\nawkwardness\tdisgust\t1\nawkwardness\tfear\t0\nawkwardness\tjoy\t0\nawkwardness\tnegative\t1\nawkwardness\tpositive\t0\nawkwardness\tsadness\t0\nawkwardness\tsurprise\t0\nawkwardness\ttrust\t0\nawning\tanger\t0\nawning\tanticipation\t0\nawning\tdisgust\t0\nawning\tfear\t0\nawning\tjoy\t0\nawning\tnegative\t0\nawning\tpositive\t0\nawning\tsadness\t0\nawning\tsurprise\t0\nawning\ttrust\t0\nawry\tanger\t0\nawry\tanticipation\t0\nawry\tdisgust\t0\nawry\tfear\t0\nawry\tjoy\t0\nawry\tnegative\t1\nawry\tpositive\t0\nawry\tsadness\t0\nawry\tsurprise\t0\nawry\ttrust\t0\naxial\tanger\t0\naxial\tanticipation\t0\naxial\tdisgust\t0\naxial\tfear\t0\naxial\tjoy\t0\naxial\tnegative\t0\naxial\tpositive\t0\naxial\tsadness\t0\naxial\tsurprise\t0\naxial\ttrust\t0\naxiom\tanger\t0\naxiom\tanticipation\t0\naxiom\tdisgust\t0\naxiom\tfear\t0\naxiom\tjoy\t0\naxiom\tnegative\t0\naxiom\tpositive\t0\naxiom\tsadness\t0\naxiom\tsurprise\t0\naxiom\ttrust\t1\naxiomatic\tanger\t0\naxiomatic\tanticipation\t0\naxiomatic\tdisgust\t0\naxiomatic\tfear\t0\naxiomatic\tjoy\t0\naxiomatic\tnegative\t0\naxiomatic\tpositive\t0\naxiomatic\tsadness\t0\naxiomatic\tsurprise\t0\naxiomatic\ttrust\t1\naxis\tanger\t0\naxis\tanticipation\t0\naxis\tdisgust\t0\naxis\tfear\t0\naxis\tjoy\t0\naxis\tnegative\t0\naxis\tpositive\t0\naxis\tsadness\t0\naxis\tsurprise\t0\naxis\ttrust\t0\naxle\tanger\t0\naxle\tanticipation\t0\naxle\tdisgust\t0\naxle\tfear\t0\naxle\tjoy\t0\naxle\tnegative\t0\naxle\tpositive\t0\naxle\tsadness\t0\naxle\tsurprise\t0\naxle\ttrust\t0\nay\tanger\t0\nay\tanticipation\t0\nay\tdisgust\t0\nay\tfear\t0\nay\tjoy\t0\nay\tnegative\t0\nay\tpositive\t1\nay\tsadness\t0\nay\tsurprise\t0\nay\ttrust\t0\naye\tanger\t0\naye\tanticipation\t0\naye\tdisgust\t0\naye\tfear\t0\naye\tjoy\t0\naye\tnegative\t0\naye\tpositive\t1\naye\tsadness\t0\naye\tsurprise\t0\naye\ttrust\t0\nazimuth\tanger\t0\nazimuth\tanticipation\t0\nazimuth\tdisgust\t0\nazimuth\tfear\t0\nazimuth\tjoy\t0\nazimuth\tnegative\t0\nazimuth\tpositive\t0\nazimuth\tsadness\t0\nazimuth\tsurprise\t0\nazimuth\ttrust\t0\nazure\tanger\t0\nazure\tanticipation\t0\nazure\tdisgust\t0\nazure\tfear\t0\nazure\tjoy\t0\nazure\tnegative\t0\nazure\tpositive\t0\nazure\tsadness\t0\nazure\tsurprise\t0\nazure\ttrust\t0\nbabble\tanger\t0\nbabble\tanticipation\t0\nbabble\tdisgust\t0\nbabble\tfear\t0\nbabble\tjoy\t0\nbabble\tnegative\t1\nbabble\tpositive\t0\nbabble\tsadness\t0\nbabble\tsurprise\t0\nbabble\ttrust\t0\nbabbling\tanger\t0\nbabbling\tanticipation\t0\nbabbling\tdisgust\t0\nbabbling\tfear\t0\nbabbling\tjoy\t0\nbabbling\tnegative\t1\nbabbling\tpositive\t0\nbabbling\tsadness\t0\nbabbling\tsurprise\t0\nbabbling\ttrust\t0\nbaboon\tanger\t0\nbaboon\tanticipation\t0\nbaboon\tdisgust\t1\nbaboon\tfear\t0\nbaboon\tjoy\t0\nbaboon\tnegative\t1\nbaboon\tpositive\t0\nbaboon\tsadness\t0\nbaboon\tsurprise\t0\nbaboon\ttrust\t0\nbaby\tanger\t0\nbaby\tanticipation\t0\nbaby\tdisgust\t0\nbaby\tfear\t0\nbaby\tjoy\t1\nbaby\tnegative\t0\nbaby\tpositive\t1\nbaby\tsadness\t0\nbaby\tsurprise\t0\nbaby\ttrust\t0\nbabysitter\tanger\t0\nbabysitter\tanticipation\t0\nbabysitter\tdisgust\t0\nbabysitter\tfear\t0\nbabysitter\tjoy\t0\nbabysitter\tnegative\t0\nbabysitter\tpositive\t0\nbabysitter\tsadness\t0\nbabysitter\tsurprise\t0\nbabysitter\ttrust\t1\nbaccalaureate\tanger\t0\nbaccalaureate\tanticipation\t0\nbaccalaureate\tdisgust\t0\nbaccalaureate\tfear\t0\nbaccalaureate\tjoy\t0\nbaccalaureate\tnegative\t0\nbaccalaureate\tpositive\t1\nbaccalaureate\tsadness\t0\nbaccalaureate\tsurprise\t0\nbaccalaureate\ttrust\t0\nbaccarat\tanger\t0\nbaccarat\tanticipation\t0\nbaccarat\tdisgust\t0\nbaccarat\tfear\t0\nbaccarat\tjoy\t0\nbaccarat\tnegative\t0\nbaccarat\tpositive\t0\nbaccarat\tsadness\t0\nbaccarat\tsurprise\t0\nbaccarat\ttrust\t0\nbachelor\tanger\t0\nbachelor\tanticipation\t0\nbachelor\tdisgust\t0\nbachelor\tfear\t0\nbachelor\tjoy\t0\nbachelor\tnegative\t0\nbachelor\tpositive\t0\nbachelor\tsadness\t0\nbachelor\tsurprise\t0\nbachelor\ttrust\t0\nback\tanger\t0\nback\tanticipation\t0\nback\tdisgust\t0\nback\tfear\t0\nback\tjoy\t0\nback\tnegative\t0\nback\tpositive\t0\nback\tsadness\t0\nback\tsurprise\t0\nback\ttrust\t0\nbackbone\tanger\t1\nbackbone\tanticipation\t0\nbackbone\tdisgust\t0\nbackbone\tfear\t0\nbackbone\tjoy\t0\nbackbone\tnegative\t0\nbackbone\tpositive\t1\nbackbone\tsadness\t0\nbackbone\tsurprise\t0\nbackbone\ttrust\t1\nbacker\tanger\t0\nbacker\tanticipation\t0\nbacker\tdisgust\t0\nbacker\tfear\t0\nbacker\tjoy\t0\nbacker\tnegative\t0\nbacker\tpositive\t0\nbacker\tsadness\t0\nbacker\tsurprise\t0\nbacker\ttrust\t1\nbackfire\tanger\t0\nbackfire\tanticipation\t0\nbackfire\tdisgust\t0\nbackfire\tfear\t0\nbackfire\tjoy\t0\nbackfire\tnegative\t0\nbackfire\tpositive\t0\nbackfire\tsadness\t0\nbackfire\tsurprise\t0\nbackfire\ttrust\t0\nbackgammon\tanger\t0\nbackgammon\tanticipation\t0\nbackgammon\tdisgust\t0\nbackgammon\tfear\t0\nbackgammon\tjoy\t0\nbackgammon\tnegative\t0\nbackgammon\tpositive\t0\nbackgammon\tsadness\t0\nbackgammon\tsurprise\t0\nbackgammon\ttrust\t0\nbackground\tanger\t0\nbackground\tanticipation\t0\nbackground\tdisgust\t0\nbackground\tfear\t0\nbackground\tjoy\t0\nbackground\tnegative\t0\nbackground\tpositive\t0\nbackground\tsadness\t0\nbackground\tsurprise\t0\nbackground\ttrust\t0\nbackhoe\tanger\t0\nbackhoe\tanticipation\t0\nbackhoe\tdisgust\t0\nbackhoe\tfear\t0\nbackhoe\tjoy\t0\nbackhoe\tnegative\t0\nbackhoe\tpositive\t0\nbackhoe\tsadness\t0\nbackhoe\tsurprise\t0\nbackhoe\ttrust\t0\nbackpacker\tanger\t0\nbackpacker\tanticipation\t0\nbackpacker\tdisgust\t0\nbackpacker\tfear\t0\nbackpacker\tjoy\t0\nbackpacker\tnegative\t0\nbackpacker\tpositive\t0\nbackpacker\tsadness\t0\nbackpacker\tsurprise\t0\nbackpacker\ttrust\t0\nbacktrack\tanger\t0\nbacktrack\tanticipation\t0\nbacktrack\tdisgust\t0\nbacktrack\tfear\t0\nbacktrack\tjoy\t0\nbacktrack\tnegative\t0\nbacktrack\tpositive\t0\nbacktrack\tsadness\t0\nbacktrack\tsurprise\t0\nbacktrack\ttrust\t0\nbackward\tanger\t0\nbackward\tanticipation\t0\nbackward\tdisgust\t0\nbackward\tfear\t0\nbackward\tjoy\t0\nbackward\tnegative\t1\nbackward\tpositive\t0\nbackward\tsadness\t0\nbackward\tsurprise\t0\nbackward\ttrust\t0\nbackwards\tanger\t0\nbackwards\tanticipation\t0\nbackwards\tdisgust\t1\nbackwards\tfear\t0\nbackwards\tjoy\t0\nbackwards\tnegative\t1\nbackwards\tpositive\t0\nbackwards\tsadness\t0\nbackwards\tsurprise\t0\nbackwards\ttrust\t0\nbackwater\tanger\t0\nbackwater\tanticipation\t0\nbackwater\tdisgust\t0\nbackwater\tfear\t0\nbackwater\tjoy\t0\nbackwater\tnegative\t1\nbackwater\tpositive\t0\nbackwater\tsadness\t1\nbackwater\tsurprise\t0\nbackwater\ttrust\t0\nbacteria\tanger\t0\nbacteria\tanticipation\t0\nbacteria\tdisgust\t1\nbacteria\tfear\t1\nbacteria\tjoy\t0\nbacteria\tnegative\t1\nbacteria\tpositive\t0\nbacteria\tsadness\t1\nbacteria\tsurprise\t0\nbacteria\ttrust\t0\nbacterium\tanger\t0\nbacterium\tanticipation\t0\nbacterium\tdisgust\t1\nbacterium\tfear\t1\nbacterium\tjoy\t0\nbacterium\tnegative\t1\nbacterium\tpositive\t0\nbacterium\tsadness\t0\nbacterium\tsurprise\t0\nbacterium\ttrust\t0\nbad\tanger\t1\nbad\tanticipation\t0\nbad\tdisgust\t1\nbad\tfear\t1\nbad\tjoy\t0\nbad\tnegative\t1\nbad\tpositive\t0\nbad\tsadness\t1\nbad\tsurprise\t0\nbad\ttrust\t0\nbadge\tanger\t0\nbadge\tanticipation\t0\nbadge\tdisgust\t0\nbadge\tfear\t0\nbadge\tjoy\t0\nbadge\tnegative\t0\nbadge\tpositive\t0\nbadge\tsadness\t0\nbadge\tsurprise\t0\nbadge\ttrust\t1\nbadger\tanger\t1\nbadger\tanticipation\t0\nbadger\tdisgust\t0\nbadger\tfear\t0\nbadger\tjoy\t0\nbadger\tnegative\t1\nbadger\tpositive\t0\nbadger\tsadness\t0\nbadger\tsurprise\t0\nbadger\ttrust\t0\nbadly\tanger\t0\nbadly\tanticipation\t0\nbadly\tdisgust\t0\nbadly\tfear\t0\nbadly\tjoy\t0\nbadly\tnegative\t1\nbadly\tpositive\t0\nbadly\tsadness\t1\nbadly\tsurprise\t0\nbadly\ttrust\t0\nbadness\tanger\t1\nbadness\tanticipation\t0\nbadness\tdisgust\t1\nbadness\tfear\t1\nbadness\tjoy\t0\nbadness\tnegative\t1\nbadness\tpositive\t0\nbadness\tsadness\t0\nbadness\tsurprise\t0\nbadness\ttrust\t0\nbaffle\tanger\t0\nbaffle\tanticipation\t0\nbaffle\tdisgust\t0\nbaffle\tfear\t0\nbaffle\tjoy\t0\nbaffle\tnegative\t0\nbaffle\tpositive\t0\nbaffle\tsadness\t0\nbaffle\tsurprise\t0\nbaffle\ttrust\t0\nbag\tanger\t0\nbag\tanticipation\t0\nbag\tdisgust\t0\nbag\tfear\t0\nbag\tjoy\t0\nbag\tnegative\t0\nbag\tpositive\t0\nbag\tsadness\t0\nbag\tsurprise\t0\nbag\ttrust\t0\nbaggage\tanger\t0\nbaggage\tanticipation\t0\nbaggage\tdisgust\t0\nbaggage\tfear\t0\nbaggage\tjoy\t0\nbaggage\tnegative\t0\nbaggage\tpositive\t0\nbaggage\tsadness\t0\nbaggage\tsurprise\t0\nbaggage\ttrust\t0\nbaggy\tanger\t0\nbaggy\tanticipation\t0\nbaggy\tdisgust\t0\nbaggy\tfear\t0\nbaggy\tjoy\t0\nbaggy\tnegative\t0\nbaggy\tpositive\t0\nbaggy\tsadness\t0\nbaggy\tsurprise\t0\nbaggy\ttrust\t0\nbagpipes\tanger\t0\nbagpipes\tanticipation\t0\nbagpipes\tdisgust\t0\nbagpipes\tfear\t0\nbagpipes\tjoy\t0\nbagpipes\tnegative\t0\nbagpipes\tpositive\t0\nbagpipes\tsadness\t0\nbagpipes\tsurprise\t0\nbagpipes\ttrust\t0\nbail\tanger\t0\nbail\tanticipation\t0\nbail\tdisgust\t0\nbail\tfear\t0\nbail\tjoy\t0\nbail\tnegative\t0\nbail\tpositive\t0\nbail\tsadness\t0\nbail\tsurprise\t0\nbail\ttrust\t0\nbailiff\tanger\t0\nbailiff\tanticipation\t0\nbailiff\tdisgust\t0\nbailiff\tfear\t1\nbailiff\tjoy\t0\nbailiff\tnegative\t1\nbailiff\tpositive\t0\nbailiff\tsadness\t0\nbailiff\tsurprise\t0\nbailiff\ttrust\t1\nbait\tanger\t0\nbait\tanticipation\t0\nbait\tdisgust\t0\nbait\tfear\t1\nbait\tjoy\t0\nbait\tnegative\t1\nbait\tpositive\t0\nbait\tsadness\t0\nbait\tsurprise\t0\nbait\ttrust\t1\nbake\tanger\t0\nbake\tanticipation\t0\nbake\tdisgust\t0\nbake\tfear\t0\nbake\tjoy\t0\nbake\tnegative\t0\nbake\tpositive\t0\nbake\tsadness\t0\nbake\tsurprise\t0\nbake\ttrust\t0\nbakery\tanger\t0\nbakery\tanticipation\t0\nbakery\tdisgust\t0\nbakery\tfear\t0\nbakery\tjoy\t0\nbakery\tnegative\t0\nbakery\tpositive\t0\nbakery\tsadness\t0\nbakery\tsurprise\t0\nbakery\ttrust\t0\nbaking\tanger\t0\nbaking\tanticipation\t0\nbaking\tdisgust\t0\nbaking\tfear\t0\nbaking\tjoy\t0\nbaking\tnegative\t0\nbaking\tpositive\t0\nbaking\tsadness\t0\nbaking\tsurprise\t0\nbaking\ttrust\t0\nbal\tanger\t0\nbal\tanticipation\t0\nbal\tdisgust\t0\nbal\tfear\t0\nbal\tjoy\t0\nbal\tnegative\t0\nbal\tpositive\t0\nbal\tsadness\t0\nbal\tsurprise\t0\nbal\ttrust\t0\nbalance\tanger\t0\nbalance\tanticipation\t0\nbalance\tdisgust\t0\nbalance\tfear\t0\nbalance\tjoy\t0\nbalance\tnegative\t0\nbalance\tpositive\t1\nbalance\tsadness\t0\nbalance\tsurprise\t0\nbalance\ttrust\t0\nbalanced\tanger\t0\nbalanced\tanticipation\t0\nbalanced\tdisgust\t0\nbalanced\tfear\t0\nbalanced\tjoy\t0\nbalanced\tnegative\t0\nbalanced\tpositive\t1\nbalanced\tsadness\t0\nbalanced\tsurprise\t0\nbalanced\ttrust\t0\nbalcony\tanger\t0\nbalcony\tanticipation\t0\nbalcony\tdisgust\t0\nbalcony\tfear\t0\nbalcony\tjoy\t0\nbalcony\tnegative\t0\nbalcony\tpositive\t0\nbalcony\tsadness\t0\nbalcony\tsurprise\t0\nbalcony\ttrust\t0\nbald\tanger\t0\nbald\tanticipation\t0\nbald\tdisgust\t0\nbald\tfear\t0\nbald\tjoy\t0\nbald\tnegative\t0\nbald\tpositive\t0\nbald\tsadness\t0\nbald\tsurprise\t0\nbald\ttrust\t0\nbale\tanger\t0\nbale\tanticipation\t0\nbale\tdisgust\t0\nbale\tfear\t1\nbale\tjoy\t0\nbale\tnegative\t1\nbale\tpositive\t0\nbale\tsadness\t0\nbale\tsurprise\t0\nbale\ttrust\t0\nbalk\tanger\t0\nbalk\tanticipation\t0\nbalk\tdisgust\t0\nbalk\tfear\t0\nbalk\tjoy\t0\nbalk\tnegative\t1\nbalk\tpositive\t0\nbalk\tsadness\t0\nbalk\tsurprise\t0\nbalk\ttrust\t0\nball\tanger\t0\nball\tanticipation\t0\nball\tdisgust\t0\nball\tfear\t0\nball\tjoy\t0\nball\tnegative\t0\nball\tpositive\t0\nball\tsadness\t0\nball\tsurprise\t0\nball\ttrust\t0\nballad\tanger\t0\nballad\tanticipation\t0\nballad\tdisgust\t0\nballad\tfear\t0\nballad\tjoy\t0\nballad\tnegative\t0\nballad\tpositive\t1\nballad\tsadness\t0\nballad\tsurprise\t0\nballad\ttrust\t0\nballast\tanger\t0\nballast\tanticipation\t0\nballast\tdisgust\t0\nballast\tfear\t0\nballast\tjoy\t0\nballast\tnegative\t0\nballast\tpositive\t0\nballast\tsadness\t0\nballast\tsurprise\t0\nballast\ttrust\t0\nballet\tanger\t0\nballet\tanticipation\t0\nballet\tdisgust\t0\nballet\tfear\t0\nballet\tjoy\t0\nballet\tnegative\t0\nballet\tpositive\t1\nballet\tsadness\t0\nballet\tsurprise\t0\nballet\ttrust\t0\nballoon\tanger\t0\nballoon\tanticipation\t0\nballoon\tdisgust\t0\nballoon\tfear\t0\nballoon\tjoy\t0\nballoon\tnegative\t0\nballoon\tpositive\t0\nballoon\tsadness\t0\nballoon\tsurprise\t0\nballoon\ttrust\t0\nballot\tanger\t0\nballot\tanticipation\t1\nballot\tdisgust\t0\nballot\tfear\t0\nballot\tjoy\t0\nballot\tnegative\t0\nballot\tpositive\t1\nballot\tsadness\t0\nballot\tsurprise\t0\nballot\ttrust\t1\nballroom\tanger\t0\nballroom\tanticipation\t0\nballroom\tdisgust\t0\nballroom\tfear\t0\nballroom\tjoy\t0\nballroom\tnegative\t0\nballroom\tpositive\t0\nballroom\tsadness\t0\nballroom\tsurprise\t0\nballroom\ttrust\t0\nbalm\tanger\t0\nbalm\tanticipation\t1\nbalm\tdisgust\t0\nbalm\tfear\t0\nbalm\tjoy\t1\nbalm\tnegative\t1\nbalm\tpositive\t1\nbalm\tsadness\t0\nbalm\tsurprise\t0\nbalm\ttrust\t0\nbalmy\tanger\t0\nbalmy\tanticipation\t0\nbalmy\tdisgust\t0\nbalmy\tfear\t0\nbalmy\tjoy\t0\nbalmy\tnegative\t0\nbalmy\tpositive\t0\nbalmy\tsadness\t0\nbalmy\tsurprise\t0\nbalmy\ttrust\t0\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atch\tfear\t0\nbatch\tjoy\t0\nbatch\tnegative\t0\nbatch\tpositive\t0\nbatch\tsadness\t0\nbatch\tsurprise\t0\nbatch\ttrust\t0\nbatching\tanger\t0\nbatching\tanticipation\t0\nbatching\tdisgust\t0\nbatching\tfear\t0\nbatching\tjoy\t0\nbatching\tnegative\t0\nbatching\tpositive\t0\nbatching\tsadness\t0\nbatching\tsurprise\t0\nbatching\ttrust\t0\nbate\tanger\t0\nbate\tanticipation\t0\nbate\tdisgust\t0\nbate\tfear\t0\nbate\tjoy\t0\nbate\tnegative\t0\nbate\tpositive\t0\nbate\tsadness\t0\nbate\tsurprise\t0\nbate\ttrust\t0\nbath\tanger\t0\nbath\tanticipation\t0\nbath\tdisgust\t0\nbath\tfear\t0\nbath\tjoy\t0\nbath\tnegative\t0\nbath\tpositive\t1\nbath\tsadness\t0\nbath\tsurprise\t0\nbath\ttrust\t0\nbathe\tanger\t0\nbathe\tanticipation\t0\nbathe\tdisgust\t0\nbathe\tfear\t0\nbathe\tjoy\t0\nbathe\tnegative\t0\nbathe\tpositive\t0\nbathe\tsadness\t0\nbathe\tsurprise\t0\nbathe\ttrust\t0\nbathroom\tanger\t0\nbathroom\tanticipation\t0\nbathroom\tdisgust\t0\nbathroom\tfear\t0\nbathroom\tjoy\t0\nbathroom\tnegative\t0\nbathroom\tpositive\t0\nbathroom\tsadness\t0\nbathroom\tsurprise\t0\nbathroom\ttrust\t0\nbathymetry\tanger\t0\nbathymetry\tanticipation\t0\nbathymetry\tdisgust\t0\nbathymetry\tfear\t0\nbathymetry\tjoy\t0\nbathymetry\tnegative\t0\nbathymetry\tpositive\t0\nbathymetry\tsadness\t0\nbathymetry\tsurprise\t0\nbathymetry\ttrust\t0\nbaton\tanger\t0\nbaton\tanticipation\t0\nbaton\tdisgust\t0\nbaton\tfear\t0\nbaton\tjoy\t0\nbaton\tnegative\t0\nbaton\tpositive\t0\nbaton\tsadness\t0\nbaton\tsurprise\t0\nbaton\ttrust\t0\nbattalion\tanger\t1\nbattalion\tanticipation\t0\nbattalion\tdisgust\t0\nbattalion\tfear\t0\nbattalion\tjoy\t0\nbattalion\tnegative\t0\nbattalion\tpositive\t0\nbattalion\tsadness\t0\nbattalion\tsurprise\t0\nbattalion\ttrust\t0\nbatter\tanger\t1\nbatter\tanticipation\t0\nbatter\tdisgust\t0\nbatter\tfear\t1\nbatter\tjoy\t0\nbatter\tnegative\t1\nbatter\tpositive\t0\nbatter\tsadness\t0\nbatter\tsurprise\t0\nbatter\ttrust\t0\nbattered\tanger\t0\nbattered\tanticipation\t0\nbattered\tdisgust\t0\nbattered\tfear\t1\nbattered\tjoy\t0\nbattered\tnegative\t1\nbattered\tpositive\t0\nbattered\tsadness\t1\nbattered\tsurprise\t0\nbattered\ttrust\t0\nbattery\tanger\t1\nbattery\tanticipation\t0\nbattery\tdisgust\t0\nbattery\tfear\t0\nbattery\tjoy\t0\nbattery\tnegative\t1\nbattery\tpositive\t0\nbattery\tsadness\t0\nbattery\tsurprise\t0\nbattery\ttrust\t0\nbattle\tanger\t1\nbattle\tanticipation\t0\nbattle\tdisgust\t0\nbattle\tfear\t0\nbattle\tjoy\t0\nbattle\tnegative\t1\nbattle\tpositive\t0\nbattle\tsadness\t0\nbattle\tsurprise\t0\nbattle\ttrust\t0\nbattled\tanger\t1\nbattled\tanticipation\t0\nbattled\tdisgust\t0\nbattled\tfear\t1\nbattled\tjoy\t0\nbattled\tnegative\t1\nbattled\tpositive\t0\nbattled\tsadness\t1\nbattled\tsurprise\t0\nbattled\ttrust\t0\nbattlefield\tanger\t0\nbattlefield\tanticipation\t0\nbattlefield\tdisgust\t0\nbattlefield\tfear\t1\nbattlefield\tjoy\t0\nbattlefield\tnegative\t1\nbattlefield\tpositive\t0\nbattlefield\tsadness\t0\nbattlefield\tsurprise\t0\nbattlefield\ttrust\t0\nbawdy\tanger\t0\nbawdy\tanticipation\t0\nbawdy\tdisgust\t0\nbawdy\tfear\t0\nbawdy\tjoy\t0\nbawdy\tnegative\t1\nbawdy\tpositive\t0\nbawdy\tsadness\t0\nbawdy\tsurprise\t0\nbawdy\ttrust\t0\nbay\tanger\t0\nbay\tanticipation\t0\nbay\tdisgust\t0\nbay\tfear\t0\nbay\tjoy\t0\nbay\tnegative\t0\nbay\tpositive\t0\nbay\tsadness\t0\nbay\tsurprise\t0\nbay\ttrust\t0\nbayonet\tanger\t1\nbayonet\tanticipation\t0\nbayonet\tdisgust\t0\nbayonet\tfear\t1\nbayonet\tjoy\t0\nbayonet\tnegative\t1\nbayonet\tpositive\t0\nbayonet\tsadness\t0\nbayonet\tsurprise\t0\nbayonet\ttrust\t0\nbayou\tanger\t0\nbayou\tanticipation\t0\nbayou\tdisgust\t0\nbayou\tfear\t0\nbayou\tjoy\t0\nbayou\tnegative\t0\nbayou\tpositive\t0\nbayou\tsadness\t0\nbayou\tsurprise\t0\nbayou\ttrust\t0\nbazaar\tanger\t0\nbazaar\tanticipation\t0\nbazaar\tdisgust\t0\nbazaar\tfear\t0\nbazaar\tjoy\t0\nbazaar\tnegative\t0\nbazaar\tpositive\t0\nbazaar\tsadness\t0\nbazaar\tsurprise\t0\nbazaar\ttrust\t0\nbeach\tanger\t0\nbeach\tanticipation\t0\nbeach\tdisgust\t0\nbeach\tfear\t0\nbeach\tjoy\t1\nbeach\tnegative\t0\nbeach\tpositive\t0\nbeach\tsadness\t0\nbeach\tsurprise\t0\nbeach\ttrust\t0\nbeacon\tanger\t0\nbeacon\tanticipation\t0\nbeacon\tdisgust\t0\nbeacon\tfear\t0\nbeacon\tjoy\t0\nbeacon\tnegative\t0\nbeacon\tpositive\t0\nbeacon\tsadness\t0\nbeacon\tsurprise\t0\nbeacon\ttrust\t0\nbead\tanger\t0\nbead\tanticipation\t0\nbead\tdisgust\t0\nbead\tfear\t0\nbead\tjoy\t0\nbead\tnegative\t0\nbead\tpositive\t0\nbead\tsadness\t0\nbead\tsurprise\t0\nbead\ttrust\t0\nbeading\tanger\t0\nbeading\tanticipation\t0\nbeading\tdisgust\t0\nbeading\tfear\t0\nbeading\tjoy\t0\nbeading\tnegative\t0\nbeading\tpositive\t0\nbeading\tsadness\t0\nbeading\tsurprise\t0\nbeading\ttrust\t0\nbeads\tanger\t0\nbeads\tanticipation\t0\nbeads\tdisgust\t0\nbeads\tfear\t0\nbeads\tjoy\t0\nbeads\tnegative\t0\nbeads\tpositive\t0\nbeads\tsadness\t0\nbeads\tsurprise\t0\nbeads\ttrust\t0\nbeagle\tanger\t0\nbeagle\tanticipation\t0\nbeagle\tdisgust\t0\nbeagle\tfear\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ncacophony\tanger\t1\ncacophony\tanticipation\t0\ncacophony\tdisgust\t1\ncacophony\tfear\t0\ncacophony\tjoy\t0\ncacophony\tnegative\t1\ncacophony\tpositive\t0\ncacophony\tsadness\t0\ncacophony\tsurprise\t0\ncacophony\ttrust\t0\ncad\tanger\t1\ncad\tanticipation\t0\ncad\tdisgust\t1\ncad\tfear\t0\ncad\tjoy\t0\ncad\tnegative\t1\ncad\tpositive\t0\ncad\tsadness\t0\ncad\tsurprise\t0\ncad\ttrust\t0\ncadaver\tanger\t0\ncadaver\tanticipation\t0\ncadaver\tdisgust\t1\ncadaver\tfear\t1\ncadaver\tjoy\t0\ncadaver\tnegative\t1\ncadaver\tpositive\t0\ncadaver\tsadness\t1\ncadaver\tsurprise\t1\ncadaver\ttrust\t0\ncaddy\tanger\t0\ncaddy\tanticipation\t0\ncaddy\tdisgust\t0\ncaddy\tfear\t0\ncaddy\tjoy\t0\ncaddy\tnegative\t0\ncaddy\tpositive\t0\ncaddy\tsadness\t0\ncaddy\tsurprise\t0\ncaddy\ttrust\t0\ncadence\tanger\t0\ncadence\tanticipation\t0\ncadence\tdisgust\t0\ncadence\tfear\t0\ncadence\tjoy\t0\ncadence\tnegative\t0\ncadence\tpositive\t0\ncadence\tsadness\t0\ncadence\tsurprise\t0\ncadence\ttrust\t0\ncadet\tanger\t0\ncadet\tanticipation\t0\ncadet\tdisgust\t0\ncadet\tfear\t0\ncadet\tjoy\t0\ncadet\tnegative\t0\ncadet\tpositive\t0\ncadet\tsadness\t0\ncadet\tsurprise\t0\ncadet\ttrust\t0\ncafe\tanger\t0\ncafe\tanticipation\t0\ncafe\tdisgust\t0\ncafe\tfear\t0\ncafe\tjoy\t0\ncafe\tnegative\t0\ncafe\tpositive\t1\ncafe\tsadness\t0\ncafe\tsurprise\t0\ncafe\ttrust\t0\ncage\tanger\t0\ncage\tanticipation\t0\ncage\tdisgust\t0\ncage\tfear\t0\ncage\tjoy\t0\ncage\tnegative\t1\ncage\tpositive\t0\ncage\tsadness\t1\ncage\tsurprise\t0\ncage\ttrust\t0\ncairn\tanger\t0\ncairn\tanticipation\t0\ncairn\tdisgust\t0\ncairn\tfear\t0\ncairn\tjoy\t0\ncairn\tnegative\t0\ncairn\tpositive\t0\ncairn\tsadness\t0\ncairn\tsurprise\t0\ncairn\ttrust\t0\ncake\tanger\t0\ncake\tanticipation\t0\ncake\tdisgust\t0\ncake\tfear\t0\ncake\tjoy\t0\ncake\tnegative\t0\ncake\tpositive\t0\ncake\tsadness\t0\ncake\tsurprise\t0\ncake\ttrust\t0\ncalamity\tanger\t0\ncalamity\tanticipation\t0\ncalamity\tdisgust\t0\ncalamity\tfear\t0\ncalamity\tjoy\t0\ncalamity\tnegative\t0\ncalamity\tpositive\t0\ncalamity\tsadness\t1\ncalamity\tsurprise\t0\ncalamity\ttrust\t0\ncalcareous\tanger\t0\ncalcareous\tanticipation\t0\ncalcareous\tdisgust\t0\ncalcareous\tfear\t0\ncalcareous\tjoy\t0\ncalcareous\tnegative\t0\ncalcareous\tpositive\t0\ncalcareous\tsadness\t0\ncalcareous\tsurprise\t0\ncalcareous\ttrust\t0\ncalculate\tanger\t0\ncalculate\tanticipation\t0\ncalculate\tdisgust\t0\ncalculate\tfear\t0\ncalculate\tjoy\t0\ncalculate\tnegative\t0\ncalculate\tpositive\t0\ncalculate\tsadness\t0\ncalculate\tsurprise\t0\ncalculate\ttrust\t0\ncalculated\tanger\t0\ncalculated\tanticipation\t0\ncalculated\tdisgust\t0\ncalculated\tfear\t0\ncalculated\tjoy\t0\ncalculated\tnegative\t0\ncalculated\tpositive\t0\ncalculated\tsadness\t0\ncalculated\tsurprise\t0\ncalculated\ttrust\t0\ncalculating\tanger\t0\ncalculating\tanticipation\t0\ncalculating\tdisgust\t0\ncalculating\tfear\t0\ncalculating\tjoy\t0\ncalculating\tnegative\t1\ncalculating\tpositive\t0\ncalculating\tsadness\t0\ncalculating\tsurprise\t0\ncalculating\ttrust\t0\ncalculation\tanger\t0\ncalculation\tanticipation\t1\ncalculation\tdisgust\t0\ncalculation\tfear\t0\ncalculation\tjoy\t0\ncalculation\tnegative\t0\ncalculation\tpositive\t0\ncalculation\tsadness\t0\ncalculation\tsurprise\t0\ncalculation\ttrust\t0\ncalculator\tanger\t0\ncalculator\tanticipation\t0\ncalculator\tdisgust\t0\ncalculator\tfear\t0\ncalculator\tjoy\t0\ncalculator\tnegative\t0\ncalculator\tpositive\t1\ncalculator\tsadness\t0\ncalculator\tsurprise\t0\ncalculator\ttrust\t1\ncalculus\tanger\t0\ncalculus\tanticipation\t0\ncalculus\tdisgust\t0\ncalculus\tfear\t0\ncalculus\tjoy\t0\ncalculus\tnegative\t0\ncalculus\tpositive\t0\ncalculus\tsadness\t0\ncalculus\tsurprise\t0\ncalculus\ttrust\t0\ncalendar\tanger\t0\ncalendar\tanticipation\t0\ncalendar\tdisgust\t0\ncalendar\tfear\t0\ncalendar\tjoy\t0\ncalendar\tnegative\t0\ncalendar\tpositive\t0\ncalendar\tsadness\t0\ncalendar\tsurprise\t0\ncalendar\ttrust\t0\ncalender\tanger\t0\ncalender\tanticipation\t0\ncalender\tdisgust\t0\ncalender\tfear\t0\ncalender\tjoy\t0\ncalender\tnegative\t0\ncalender\tpositive\t0\ncalender\tsadness\t0\ncalender\tsurprise\t0\ncalender\ttrust\t0\ncalf\tanger\t0\ncalf\tanticipation\t0\ncalf\tdisgust\t0\ncalf\tfear\t0\ncalf\tjoy\t1\ncalf\tnegative\t0\ncalf\tpositive\t1\ncalf\tsadness\t0\ncalf\tsurprise\t0\ncalf\ttrust\t1\ncaliber\tanger\t0\ncaliber\tanticipation\t0\ncaliber\tdisgust\t0\ncaliber\tfear\t0\ncaliber\tjoy\t0\ncaliber\tnegative\t0\ncaliber\tpositive\t0\ncaliber\tsadness\t0\ncaliber\tsurprise\t0\ncaliber\ttrust\t0\ncalibrate\tanger\t0\ncalibrate\tanticipation\t0\ncalibrate\tdisgust\t0\ncalibrate\tfear\t0\ncalibrate\tjoy\t0\ncalibrate\tnegative\t0\ncalibrate\tpositive\t0\ncalibrate\tsadness\t0\ncalibrate\tsurprise\t0\ncalibrate\ttrust\t0\ncalico\tanger\t0\ncalico\tanticipation\t0\ncalico\tdisgust\t0\ncalico\tfear\t0\ncalico\tjoy\t0\ncalico\tnegative\t0\ncalico\tpositive\t0\ncalico\tsadness\t0\ncalico\tsurprise\t0\ncalico\tt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ess\t0\ncampus\tsurprise\t0\ncampus\ttrust\t0\ncanal\tanger\t0\ncanal\tanticipation\t0\ncanal\tdisgust\t0\ncanal\tfear\t0\ncanal\tjoy\t0\ncanal\tnegative\t0\ncanal\tpositive\t0\ncanal\tsadness\t0\ncanal\tsurprise\t0\ncanal\ttrust\t0\ncanary\tanger\t0\ncanary\tanticipation\t0\ncanary\tdisgust\t0\ncanary\tfear\t0\ncanary\tjoy\t0\ncanary\tnegative\t0\ncanary\tpositive\t1\ncanary\tsadness\t0\ncanary\tsurprise\t0\ncanary\ttrust\t0\ncancel\tanger\t0\ncancel\tanticipation\t0\ncancel\tdisgust\t0\ncancel\tfear\t0\ncancel\tjoy\t0\ncancel\tnegative\t1\ncancel\tpositive\t0\ncancel\tsadness\t1\ncancel\tsurprise\t0\ncancel\ttrust\t0\ncanceling\tanger\t0\ncanceling\tanticipation\t0\ncanceling\tdisgust\t0\ncanceling\tfear\t0\ncanceling\tjoy\t0\ncanceling\tnegative\t0\ncanceling\tpositive\t0\ncanceling\tsadness\t0\ncanceling\tsurprise\t0\ncanceling\ttrust\t0\ncancellation\tanger\t0\ncancellation\tanticipation\t0\ncancellation\tdisgust\t0\ncancellation\tfear\t0\ncancellation\tjoy\t0\ncancellation\tnegative\t0\ncancellation\tpositive\t0\ncancellation\tsadness\t0\ncancellation\tsurprise\t0\ncancellation\ttrust\t0\ncancer\tanger\t1\ncancer\tanticipation\t0\ncancer\tdisgust\t1\ncancer\tfear\t1\ncancer\tjoy\t0\ncancer\tnegative\t1\ncancer\tpositive\t0\ncancer\tsadness\t1\ncancer\tsurprise\t0\ncancer\ttrust\t0\ncandid\tanger\t0\ncandid\tanticipation\t1\ncandid\tdisgust\t0\ncandid\tfear\t0\ncandid\tjoy\t1\ncandid\tnegative\t0\ncandid\tpositive\t1\ncandid\tsadness\t0\ncandid\tsurprise\t1\ncandid\ttrust\t1\ncandidacy\tanger\t0\ncandidacy\tanticipation\t0\ncandidacy\tdisgust\t0\ncandidacy\tfear\t0\ncandidacy\tjoy\t0\ncandidacy\tnegative\t0\ncandidacy\tpositive\t0\ncandidacy\tsadness\t0\ncandidacy\tsurprise\t0\ncandidacy\ttrust\t0\ncandidate\tanger\t0\ncandidate\tanticipation\t0\ncandidate\tdisgust\t0\ncandidate\tfear\t0\ncandidate\tjoy\t0\ncandidate\tnegative\t0\ncandidate\tpositive\t1\ncandidate\tsadness\t0\ncandidate\tsurprise\t0\ncandidate\ttrust\t0\ncandied\tanger\t0\ncandied\tanticipation\t0\ncandied\tdisgust\t0\ncandied\tfear\t0\ncandied\tjoy\t0\ncandied\tnegative\t0\ncandied\tpositive\t1\ncandied\tsadness\t0\ncandied\tsurprise\t0\ncandied\ttrust\t0\ncandle\tanger\t0\ncandle\tanticipation\t0\ncandle\tdisgust\t0\ncandle\tfear\t0\ncandle\tjoy\t0\ncandle\tnegative\t0\ncandle\tpositive\t0\ncandle\tsadness\t0\ncandle\tsurprise\t0\ncandle\ttrust\t0\ncandlelight\tanger\t0\ncandlelight\tanticipation\t0\ncandlelight\tdisgust\t0\ncandlelight\tfear\t0\ncandlelight\tjoy\t0\ncandlelight\tnegative\t0\ncandlelight\tpositive\t0\ncandlelight\tsadness\t0\ncandlelight\tsurprise\t0\ncandlelight\ttrust\t0\ncandlestick\tanger\t0\ncandlestick\tanticipation\t0\ncandlestick\tdisgust\t0\ncandlestick\tfear\t0\ncandlestick\tjoy\t0\ncandlestick\tnegative\t0\ncandlestick\tpositive\t0\ncandlestick\tsadness\t0\ncandlestick\tsurprise\t0\ncandlestick\ttrust\t0\ncandor\tanger\t0\ncandor\tanticipation\t0\ncandor\tdisgust\t0\ncandor\tfear\t0\ncandor\tjoy\t0\ncandor\tnegative\t0\ncandor\tpositive\t0\ncandor\tsadness\t0\ncandor\tsurprise\t0\ncandor\ttrust\t0\ncandy\tanger\t0\ncandy\tanticipation\t0\ncandy\tdisgust\t0\ncandy\tfear\t0\ncandy\tjoy\t0\ncandy\tnegative\t0\ncandy\tpositive\t0\ncandy\tsadness\t0\ncandy\tsurprise\t0\ncandy\ttrust\t0\ncane\tanger\t1\ncane\tanticipation\t0\ncane\tdisgust\t0\ncane\tfear\t1\ncane\tjoy\t0\ncane\tnegative\t0\ncane\tpositive\t0\ncane\tsadness\t0\ncane\tsurprise\t0\ncane\ttrust\t0\ncanine\tanger\t0\ncanine\tanticipation\t0\ncanine\tdisgust\t0\ncanine\tfear\t0\ncanine\tjoy\t0\ncanine\tnegative\t0\ncanine\tpositive\t0\ncanine\tsadness\t0\ncanine\tsurprise\t0\ncanine\ttrust\t0\ncanister\tanger\t0\ncanister\tanticipation\t0\ncanister\tdisgust\t0\ncanister\tfear\t0\ncanister\tjoy\t0\ncanister\tnegative\t0\ncanister\tpositive\t0\ncanister\tsadness\t0\ncanister\tsurprise\t0\ncanister\ttrust\t0\ncanker\tanger\t1\ncanker\tanticipation\t0\ncanker\tdisgust\t1\ncanker\tfear\t0\ncanker\tjoy\t0\ncanker\tnegative\t1\ncanker\tpositive\t0\ncanker\tsadness\t0\ncanker\tsurprise\t0\ncanker\ttrust\t0\ncannibal\tanger\t0\ncannibal\tanticipation\t0\ncannibal\tdisgust\t1\ncannibal\tfear\t1\ncannibal\tjoy\t0\ncannibal\tnegative\t1\ncannibal\tpositive\t0\ncannibal\tsadness\t0\ncannibal\tsurprise\t0\ncannibal\ttrust\t0\ncannibalism\tanger\t0\ncannibalism\tanticipation\t0\ncannibalism\tdisgust\t1\ncannibalism\tfear\t0\ncannibalism\tjoy\t0\ncannibalism\tnegative\t1\ncannibalism\tpositive\t0\ncannibalism\tsadness\t0\ncannibalism\tsurprise\t0\ncannibalism\ttrust\t0\ncanning\tanger\t0\ncanning\tanticipation\t0\ncanning\tdisgust\t0\ncanning\tfear\t0\ncanning\tjoy\t0\ncanning\tnegative\t0\ncanning\tpositive\t0\ncanning\tsadness\t0\ncanning\tsurprise\t0\ncanning\ttrust\t0\ncannon\tanger\t1\ncannon\tanticipation\t0\ncannon\tdisgust\t0\ncannon\tfear\t1\ncannon\tjoy\t0\ncannon\tnegative\t1\ncannon\tpositive\t0\ncannon\tsadness\t0\ncannon\tsurprise\t0\ncannon\ttrust\t0\ncanoe\tanger\t0\ncanoe\tanticipation\t0\ncanoe\tdisgust\t0\ncanoe\tfear\t0\ncanoe\tjoy\t0\ncanoe\tnega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anticipation\t0\nchit\tdisgust\t0\nchit\tfear\t0\nchit\tjoy\t0\nchit\tnegative\t0\nchit\tpositive\t0\nchit\tsadness\t0\nchit\tsurprise\t0\nchit\ttrust\t0\nchivalry\tanger\t0\nchivalry\tanticipation\t0\nchivalry\tdisgust\t0\nchivalry\tfear\t0\nchivalry\tjoy\t0\nchivalry\tnegative\t0\nchivalry\tpositive\t1\nchivalry\tsadness\t0\nchivalry\tsurprise\t0\nchivalry\ttrust\t0\nchloroform\tanger\t0\nchloroform\tanticipation\t0\nchloroform\tdisgust\t0\nchloroform\tfear\t0\nchloroform\tjoy\t0\nchloroform\tnegative\t1\nchloroform\tpositive\t0\nchloroform\tsadness\t0\nchloroform\tsurprise\t0\nchloroform\ttrust\t0\nchocolate\tanger\t0\nchocolate\tanticipation\t1\nchocolate\tdisgust\t0\nchocolate\tfear\t0\nchocolate\tjoy\t1\nchocolate\tnegative\t0\nchocolate\tpositive\t1\nchocolate\tsadness\t0\nchocolate\tsurprise\t0\nchocolate\ttrust\t1\nchoice\tanger\t0\nchoice\tanticipation\t0\nchoice\tdisgust\t0\nchoice\tfear\t0\nchoice\tjoy\t0\nchoice\tnegative\t0\nchoice\tpositive\t1\nchoice\tsadness\t0\nchoice\tsurprise\t0\nchoice\ttrust\t0\nchoir\tanger\t0\nchoir\tanticipation\t0\nchoir\tdisgust\t0\nchoir\tfear\t0\nchoir\tjoy\t1\nchoir\tnegative\t0\nchoir\tpositive\t1\nchoir\tsadness\t0\nchoir\tsurprise\t0\nchoir\ttrust\t1\nchoke\tanger\t1\nchoke\tanticipation\t0\nchoke\tdisgust\t0\nchoke\tfear\t0\nchoke\tjoy\t0\nchoke\tnegative\t1\nchoke\tpositive\t0\nchoke\tsadness\t1\nchoke\tsurprise\t0\nchoke\ttrust\t0\ncholera\tanger\t0\ncholera\tanticipation\t0\ncholera\tdisgust\t1\ncholera\tfear\t1\ncholera\tjoy\t0\ncholera\tnegative\t1\ncholera\tpositive\t0\ncholera\tsadness\t1\ncholera\tsurprise\t0\ncholera\ttrust\t0\nchoose\tanger\t0\nchoose\tanticipation\t0\nchoose\tdisgust\t0\nchoose\tfear\t0\nchoose\tjoy\t0\nchoose\tnegative\t0\nchoose\tpositive\t0\nchoose\tsadness\t0\nchoose\tsurprise\t0\nchoose\ttrust\t0\nchoosing\tanger\t0\nchoosing\tanticipation\t0\nchoosing\tdisgust\t0\nchoosing\tfear\t0\nchoosing\tjoy\t0\nchoosing\tnegative\t0\nchoosing\tpositive\t0\nchoosing\tsadness\t0\nchoosing\tsurprise\t0\nchoosing\ttrust\t0\nchop\tanger\t0\nchop\tanticipation\t0\nchop\tdisgust\t0\nchop\tfear\t0\nchop\tjoy\t0\nchop\tnegative\t1\nchop\tpositive\t0\nchop\tsadness\t0\nchop\tsurprise\t0\nchop\ttrust\t0\nchopping\tanger\t0\nchopping\tanticipation\t0\nchopping\tdisgust\t0\nchopping\tfear\t0\nchopping\tjoy\t0\nchopping\tnegative\t0\nchopping\tpositive\t0\nchopping\tsadness\t0\nchopping\tsurprise\t0\nchopping\ttrust\t0\nchops\tanger\t0\nchops\tanticipation\t0\nchops\tdisgust\t0\nchops\tfear\t0\nchops\tjoy\t0\nchops\tnegative\t0\nchops\tpositive\t0\nchops\tsadness\t0\nchops\tsurprise\t0\nchops\ttrust\t0\nchoral\tanger\t0\nchoral\tanticipation\t0\nchoral\tdisgust\t0\nchoral\tfear\t0\nchoral\tjoy\t1\nchoral\tnegative\t0\nchoral\tpositive\t1\nchoral\tsadness\t0\nchoral\tsurprise\t0\nchoral\ttrust\t0\nchords\tanger\t0\nchords\tanticipation\t0\nchords\tdisgust\t0\nchords\tfear\t0\nchords\tjoy\t0\nchords\tnegative\t0\nchords\tpositive\t0\nchords\tsadness\t0\nchords\tsurprise\t0\nchords\ttrust\t0\nchore\tanger\t0\nchore\tanticipation\t0\nchore\tdisgust\t0\nchore\tfear\t0\nchore\tjoy\t0\nchore\tnegative\t1\nchore\tpositive\t0\nchore\tsadness\t0\nchore\tsurprise\t0\nchore\ttrust\t0\nchorus\tanger\t0\nchorus\tanticipation\t0\nchorus\tdisgust\t0\nchorus\tfear\t0\nchorus\tjoy\t0\nchorus\tnegative\t0\nchorus\tpositive\t1\nchorus\tsadness\t0\nchorus\tsurprise\t0\nchorus\ttrust\t0\nchosen\tanger\t0\nchosen\tanticipation\t0\nchosen\tdisgust\t0\nchosen\tfear\t0\nchosen\tjoy\t0\nchosen\tnegative\t0\nchosen\tpositive\t1\nchosen\tsadness\t0\nchosen\tsurprise\t0\nchosen\ttrust\t0\nchowder\tanger\t0\nchowder\tanticipation\t0\nchowder\tdisgust\t0\nchowder\tfear\t0\nchowder\tjoy\t0\nchowder\tnegative\t0\nchowder\tpositive\t1\nchowder\tsadness\t0\nchowder\tsurprise\t0\nchowder\ttrust\t0\nchristening\tanger\t0\nchristening\tanticipation\t0\nchristening\tdisgust\t0\nchristening\tfear\t0\nchristening\tjoy\t0\nchristening\tnegative\t0\nchristening\tpositive\t0\nchristening\tsadness\t0\nchristening\tsurprise\t0\nchristening\ttrust\t0\nchromatic\tanger\t0\nchromatic\tanticipation\t0\nchromatic\tdisgust\t0\nchromatic\tfear\t0\nchromatic\tjoy\t0\nchromatic\tnegative\t0\nchromatic\tpositive\t0\nchromatic\tsadness\t0\nchromatic\tsurprise\t0\nchromatic\ttrust\t0\nchromatography\tanger\t0\nchromatography\tanticipation\t0\nchromatography\tdisgust\t0\nchromatography\tfear\t0\nchromatography\tjoy\t0\nchromatography\tnegative\t0\nchromatography\tpositive\t0\nchromatography\tsadness\t0\nchromatography\tsurprise\t0\nchromatography\ttrust\t0\nchromosome\tanger\t0\nchromosome\tanticipation\t0\nchromosome\tdisgust\t0\nchromosome\tfear\t0\nchromosome\tjoy\t0\nchromosome\tnegative\t0\nchromosome\tpositive\t0\nchromosome\tsadness\t0\nchromosome\tsurprise\t0\nchromosome\ttrust\t0\nchronic\tanger\t0\nchronic\tanticipation\t0\nchronic\tdisgust\t0\nchronic\tfear\t0\nchronic\tjoy\t0\nchronic\tnegative\t1\nchronic\tpositive\t0\nchronic\tsadness\t1\nchronic\tsurprise\t0\nchronic\ttrust\t0\nchronicle\tanger\t0\nchronicle\tanticipation\t0\nchronicle\tdisgust\t0\nchronicle\tfear\t0\nchronicle\tjoy\t0\nchronicle\tnegative\t0\nchronicle\tpositive\t1\nchronicle\tsadness\t0\nchronicle\tsurprise\t0\nchronicle\ttrust\t1\nchronograph\tanger\t0\nchronograph\tanticipation\t0\nchronograph\tdisgust\t0\nchronograph\tfear\t0\nchronograph\tjoy\t0\nchronograph\tnegative\t0\nchronograph\tpositive\t0\nchronograph\tsadness\t0\nchronograph\tsurprise\t0\nchronograph\ttrust\t0\nchronological\tanger\t0\nchronological\tanticipation\t0\nchronological\tdisgust\t0\nchronological\tfear\t0\nchronological\tjoy\t0\nchronological\tnegative\t0\nchronological\tpositive\t0\nchronological\tsadness\t0\nchronological\tsurprise\t0\nchronological\ttrust\t0\nchuck\tanger\t0\nchuck\tanticipation\t0\nchuck\tdisgust\t0\nchuck\tfear\t0\nchuck\tjoy\t0\nchuck\tnegative\t0\nchuck\tpositive\t0\nchuck\tsadness\t0\nchuck\tsurprise\t0\nchuck\ttrust\t0\nchuckle\tanger\t0\nchuckle\tanticipation\t1\nchuckle\tdisgust\t0\nchuckle\tfear\t0\nchuckle\tjoy\t1\nchuckle\tnegative\t0\nchuckle\tpositive\t1\nchuckle\tsadness\t0\nchuckle\tsurprise\t1\nchuckle\ttrust\t1\nchunk\tanger\t0\nchunk\tanticipation\t0\nchunk\tdisgust\t0\nchunk\tfear\t0\nchunk\tjoy\t0\nchunk\tnegative\t0\nchunk\tpositive\t0\nchunk\tsadness\t0\nchunk\tsurprise\t0\nchunk\ttrust\t0\nchunky\tanger\t0\nchunky\tanticipation\t0\nchunky\tdisgust\t0\nchunky\tfear\t0\nchunky\tjoy\t0\nchunky\tnegative\t0\nchunky\tpositive\t0\nchunky\tsadness\t0\nchunky\tsurprise\t0\nchunky\ttrust\t0\nchurch\tanger\t0\nchurch\tanticipation\t1\nchurch\tdisgust\t0\nchurch\tfear\t0\nchurch\tjoy\t1\nchurch\tnegative\t0\nchurch\tpositive\t1\nchurch\tsadness\t0\nchurch\tsurprise\t0\nchurch\ttrust\t1\nchurchyard\tanger\t0\nchurchyard\tanticipation\t0\nchurchyard\tdisgust\t0\nchurchyard\tfear\t0\nchurchyard\tjoy\t0\nchurchyard\tnegative\t0\nchurchyard\tpositive\t0\nchurchyard\tsadness\t0\nchurchyard\tsurprise\t0\nchurchyard\ttrust\t0\nchurn\tanger\t0\nchurn\tanticipation\t0\nchurn\tdisgust\t0\nchurn\tfear\t0\nchurn\tjoy\t0\nchurn\tnegative\t0\nchurn\tpositive\t0\nchurn\tsadness\t0\nchurn\tsurprise\t0\nchurn\ttrust\t0\nchute\tanger\t0\nchute\tanticipation\t0\nchute\tdisgust\t0\nchute\tfear\t0\nchute\tjoy\t0\nchute\tnegative\t0\nchute\tpositive\t0\nchute\tsadness\t0\nchute\tsurprise\t0\nchute\ttrust\t0\nchutney\tanger\t0\nchutney\tanticipation\t0\nchutney\tdisgust\t0\nchutney\tfear\t0\nchutney\tjoy\t0\nchutney\tnegative\t0\nchutney\tpositive\t0\nchutney\tsadness\t0\nchutney\tsurprise\t0\nchutney\ttrust\t0\nciao\tanger\t0\nciao\tanticipation\t0\nciao\tdisgust\t0\nciao\tfear\t0\nciao\tjoy\t0\nciao\tnegative\t0\nciao\tpositive\t0\nciao\tsadness\t0\nciao\tsurprise\t0\nciao\ttrust\t0\ncider\tanger\t0\ncider\tanticipation\t0\ncider\tdisgust\t0\ncider\tfear\t0\ncider\tjoy\t0\ncider\tnegative\t0\ncider\tpositive\t1\ncider\tsadness\t0\ncider\tsurprise\t0\ncider\ttrust\t0\ncigar\tanger\t0\ncigar\tanticipation\t0\ncigar\tdisgust\t0\ncigar\tfear\t0\ncigar\tjoy\t0\ncigar\tnegative\t0\ncigar\tpositive\t0\ncigar\tsadness\t0\ncigar\tsurprise\t0\ncigar\ttrust\t0\ncigarette\tanger\t0\ncigarette\tanticipation\t0\ncigarette\tdisgust\t0\ncigarette\tfear\t0\ncigarette\tjoy\t0\ncigarette\tnegative\t1\ncigarette\tpositive\t0\ncigarette\tsadness\t0\ncigarette\tsurprise\t0\ncigarette\ttrust\t0\ncinch\tanger\t0\ncinch\tanticipation\t0\ncinch\tdisgust\t0\ncinch\tfear\t0\ncinch\tjoy\t0\ncinch\tnegative\t0\ncinch\tpositive\t0\ncinch\tsadness\t0\ncinch\tsurprise\t0\ncinch\ttrust\t0\ncinder\tanger\t0\ncinder\tanticipation\t0\ncinder\tdisgust\t0\ncinder\tfear\t0\ncinder\tjoy\t0\ncinder\tnegative\t0\ncinder\tpositive\t0\ncinder\tsadness\t0\ncinder\tsurprise\t0\ncinder\ttrust\t0\ncinema\tanger\t0\ncinema\tanticipation\t0\ncinema\tdisgust\t0\ncinema\tfear\t0\ncinema\tjoy\t0\ncinema\tnegative\t0\ncinema\tpositive\t0\ncinema\tsadness\t0\ncinema\tsurprise\t0\ncinema\ttrust\t0\ncinematographer\tanger\t0\ncinematographer\tanticipation\t0\ncinematographer\tdisgust\t0\ncinematographer\tfear\t0\ncinematographer\tjoy\t0\ncinematographer\tnegative\t0\ncinematographer\tpositive\t0\ncinematographer\tsadness\t0\ncinematographer\tsurprise\t0\ncinematographer\ttrust\t0\ncinematography\tanger\t0\ncinematography\tanticipation\t0\ncinematography\tdisgust\t0\ncinematography\tfear\t0\ncinematography\tjoy\t0\ncinematography\tnegative\t0\ncinematography\tpositive\t0\ncinematography\tsadness\t0\ncinematography\tsurprise\t0\ncinematography\ttrust\t0\ncinnamon\tanger\t0\ncinnamon\tanticipation\t0\ncinnamon\tdisgust\t0\ncinnamon\tfear\t0\ncinnamon\tjoy\t0\ncinnamon\tnegative\t0\ncinnamon\tpositive\t0\ncinnamon\tsadness\t0\ncinnamon\tsurprise\t0\ncinnamon\ttrust\t0\ncipher\tanger\t0\ncipher\tanticipation\t0\ncipher\tdisgust\t0\ncipher\tfear\t0\ncipher\tjoy\t0\ncipher\tnegative\t0\ncipher\tpositive\t0\ncipher\tsadness\t0\ncipher\tsurprise\t0\ncipher\ttrust\t0\ncircle\tanger\t0\ncircle\tanticipation\t0\ncircle\tdisgust\t0\ncircle\tfear\t0\ncircle\tjoy\t0\ncircle\tnegative\t0\ncircle\tpositive\t0\ncircl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icipation\t0\nconditionally\tdisgust\t0\nconditionally\tfear\t0\nconditionally\tjoy\t0\nconditionally\tnegative\t0\nconditionally\tpositive\t0\nconditionally\tsadness\t0\nconditionally\tsurprise\t0\nconditionally\ttrust\t0\nconditioned\tanger\t0\nconditioned\tanticipation\t0\nconditioned\tdisgust\t0\nconditioned\tfear\t0\nconditioned\tjoy\t0\nconditioned\tnegative\t0\nconditioned\tpositive\t0\nconditioned\tsadness\t0\nconditioned\tsurprise\t0\nconditioned\ttrust\t0\nconditions\tanger\t0\nconditions\tanticipation\t0\nconditions\tdisgust\t0\nconditions\tfear\t0\nconditions\tjoy\t0\nconditions\tnegative\t0\nconditions\tpositive\t0\nconditions\tsadness\t0\nconditions\tsurprise\t0\nconditions\ttrust\t0\ncondolence\tanger\t0\ncondolence\tanticipation\t0\ncondolence\tdisgust\t0\ncondolence\tfear\t0\ncondolence\tjoy\t0\ncondolence\tnegative\t0\ncondolence\tpositive\t1\ncondolence\tsadness\t1\ncondolence\tsurprise\t0\ncondolence\ttrust\t0\ncondone\tanger\t0\ncondone\tanticipation\t0\ncondone\tdisgust\t0\ncondone\tfear\t0\ncondone\tjoy\t0\ncondone\tnegative\t0\ncondone\tpositive\t1\ncondone\tsadness\t0\ncondone\tsurprise\t0\ncondone\ttrust\t0\nconducive\tanger\t0\nconducive\tanticipation\t0\nconducive\tdisgust\t0\nconducive\tfear\t0\nconducive\tjoy\t0\nconducive\tnegative\t0\nconducive\tpositive\t1\nconducive\tsadness\t0\nconducive\tsurprise\t0\nconducive\ttrust\t0\nconduct\tanger\t0\nconduct\tanticipation\t0\nconduct\tdisgust\t0\nconduct\tfear\t0\nconduct\tjoy\t0\nconduct\tnegative\t0\nconduct\tpositive\t0\nconduct\tsadness\t0\nconduct\tsurprise\t0\nconduct\ttrust\t0\nconduction\tanger\t0\nconduction\tanticipation\t0\nconduction\tdisgust\t0\nconduction\tfear\t0\nconduction\tjoy\t0\nconduction\tnegative\t0\nconduction\tpositive\t0\nconduction\tsadness\t0\nconduction\tsurprise\t0\nconduction\ttrust\t0\nconductivity\tanger\t0\nconductivity\tanticipation\t0\nconductivity\tdisgust\t0\nconductivity\tfear\t0\nconductivity\tjoy\t0\nconductivity\tnegative\t0\nconductivity\tpositive\t1\nconductivity\tsadness\t0\nconductivity\tsurprise\t0\nconductivity\ttrust\t0\nconductor\tanger\t0\nconductor\tanticipation\t0\nconductor\tdisgust\t0\nconductor\tfear\t0\nconductor\tjoy\t0\nconductor\tnegative\t0\nconductor\tpositive\t0\nconductor\tsadness\t0\nconductor\tsurprise\t0\nconductor\ttrust\t0\nconduit\tanger\t0\nconduit\tanticipation\t0\nconduit\tdisgust\t0\nconduit\tfear\t0\nconduit\tjoy\t0\nconduit\tnegative\t0\nconduit\tpositive\t0\nconduit\tsadness\t0\nconduit\tsurprise\t0\nconduit\ttrust\t0\ncone\tanger\t0\ncone\tanticipation\t0\ncone\tdisgust\t0\ncone\tfear\t0\ncone\tjoy\t0\ncone\tnegative\t0\ncone\tpositive\t0\ncone\tsadness\t0\ncone\tsurprise\t0\ncone\ttrust\t0\nconfederate\tanger\t0\nconfederate\tanticipation\t0\nconfederate\tdisgust\t0\nconfederate\tfear\t0\nconfederate\tjoy\t0\nconfederate\tnegative\t0\nconfederate\tpositive\t1\nconfederate\tsadness\t0\nconfederate\tsurprise\t0\nconfederate\ttrust\t1\nconfederation\tanger\t0\nconfederation\tanticipation\t0\nconfederation\tdisgust\t0\nconfederation\tfear\t0\nconfederation\tjoy\t0\nconfederation\tnegative\t0\nconfederation\tpositive\t0\nconfederation\tsadness\t0\nconfederation\tsurprise\t0\nconfederation\ttrust\t0\nconfer\tanger\t0\nconfer\tanticipation\t0\nconfer\tdisgust\t0\nconfer\tfear\t0\nconfer\tjoy\t0\nconfer\tnegative\t0\nconfer\tpositive\t0\nconfer\tsadness\t0\nconfer\tsurprise\t0\nconfer\ttrust\t0\nconference\tanger\t0\nconference\tanticipation\t0\nconference\tdisgust\t0\nconference\tfear\t0\nconference\tjoy\t0\nconference\tnegative\t0\nconference\tpositive\t0\nconference\tsadness\t0\nconference\tsurprise\t0\nconference\ttrust\t0\nconfess\tanger\t0\nconfess\tanticipation\t0\nconfess\tdisgust\t0\nconfess\tfear\t0\nconfess\tjoy\t0\nconfess\tnegative\t1\nconfess\tpositive\t1\nconfess\tsadness\t0\nconfess\tsurprise\t0\nconfess\ttrust\t1\nconfession\tanger\t0\nconfession\tanticipation\t1\nconfession\tdisgust\t0\nconfession\tfear\t1\nconfession\tjoy\t0\nconfession\tnegative\t1\nconfession\tpositive\t0\nconfession\tsadness\t1\nconfession\tsurprise\t1\nconfession\ttrust\t0\nconfessional\tanger\t0\nconfessional\tanticipation\t0\nconfessional\tdisgust\t0\nconfessional\tfear\t1\nconfessional\tjoy\t0\nconfessional\tnegative\t0\nconfessional\tpositive\t0\nconfessional\tsadness\t0\nconfessional\tsurprise\t0\nconfessional\ttrust\t1\nconfessions\tanger\t0\nconfessions\tanticipation\t0\nconfessions\tdisgust\t0\nconfessions\tfear\t0\nconfessions\tjoy\t0\nconfessions\tnegative\t0\nconfessions\tpositive\t0\nconfessions\tsadness\t0\nconfessions\tsurprise\t0\nconfessions\ttrust\t0\nconfide\tanger\t0\nconfide\tanticipation\t0\nconfide\tdisgust\t0\nconfide\tfear\t0\nconfide\tjoy\t0\nconfide\tnegative\t0\nconfide\tpositive\t0\nconfide\tsadness\t0\nconfide\tsurprise\t0\nconfide\ttrust\t1\nconfidence\tanger\t0\nconfidence\tanticipation\t0\nconfidence\tdisgust\t0\nconfidence\tfear\t1\nconfidence\tjoy\t1\nconfidence\tnegative\t0\nconfidence\tpositive\t1\nconfidence\tsadness\t0\nconfidence\tsurprise\t0\nconfidence\ttrust\t1\nconfident\tanger\t0\nconfident\tanticipation\t0\nconfident\tdisgust\t0\nconfident\tfear\t0\nconfident\tjoy\t1\nconfident\tnegative\t0\nconfident\tpositive\t1\nconfident\tsadness\t0\nconfident\tsurprise\t0\nconfident\ttrust\t1\nconfidential\tanger\t0\nconfidential\tanticipation\t0\nconfidential\tdisgust\t0\nconfidential\tfear\t0\nconfidential\tjoy\t0\nconfidential\tnegative\t0\nconfidential\tpositive\t0\nconfidential\tsadness\t0\nconfidential\tsurprise\t0\nconfidential\ttrust\t1\nconfidentially\tanger\t0\nconfidentially\tanticipation\t0\nconfidentially\tdisgust\t0\nconfidentially\tfear\t0\nconfidentially\tjoy\t0\nconfidentially\tnegative\t0\nconfidentially\tpositive\t0\nconfidentially\tsadness\t0\nconfidentially\tsurprise\t0\nconfidentially\ttrust\t1\nconfiguration\tanger\t0\nconfiguration\tanticipation\t0\nconfiguration\tdisgust\t0\nconfiguration\tfear\t0\nconfiguration\tjoy\t0\nconfiguration\tnegative\t0\nconfiguration\tpositive\t0\nconfiguration\tsadness\t0\nconfiguration\tsurprise\t0\nconfiguration\ttrust\t0\nconfine\tanger\t1\nconfine\tanticipation\t0\nconfine\tdisgust\t0\nconfine\tfear\t1\nconfine\tjoy\t0\nconfine\tnegative\t1\nconfine\tpositive\t0\nconfine\tsadness\t1\nconfine\tsurprise\t0\nconfine\ttrust\t0\nconfined\tanger\t1\nconfined\tanticipation\t0\nconfined\tdisgust\t1\nconfined\tfear\t1\nconfined\tjoy\t0\nconfined\tnegative\t1\nconfined\tpositive\t0\nconfined\tsadness\t1\nconfined\tsurprise\t0\nconfined\ttrust\t0\nconfinement\tanger\t1\nconfinement\tanticipation\t0\nconfinement\tdisgust\t0\nconfinement\tfear\t1\nconfinement\tjoy\t0\nconfinement\tnegative\t1\nconfinement\tpositive\t0\nconfinement\tsadness\t1\nconfinement\tsurprise\t0\nconfinement\ttrust\t0\nconfines\tanger\t0\nconfines\tanticipation\t0\nconfines\tdisgust\t0\nconfines\tfear\t0\nconfines\tjoy\t0\nconfines\tnegative\t0\nconfines\tpositive\t0\nconfines\tsadness\t0\nconfines\tsurprise\t0\nconfines\ttrust\t0\nconfirm\tanger\t0\nconfirm\tanticipation\t0\nconfirm\tdisgust\t0\nconfirm\tfear\t0\nconfirm\tjoy\t0\nconfirm\tnegative\t0\nconfirm\tpositive\t0\nconfirm\tsadness\t0\nconfirm\tsurprise\t0\nconfirm\ttrust\t0\nconfirmation\tanger\t0\nconfirmation\tanticipation\t0\nconfirmation\tdisgust\t0\nconfirmation\tfear\t0\nconfirmation\tjoy\t0\nconfirmation\tnegative\t0\nconfirmation\tpositive\t0\nconfirmation\tsadness\t0\nconfirmation\tsurprise\t0\nconfirmation\ttrust\t1\nconfirmatory\tanger\t0\nconfirmatory\tanticipation\t0\nconfirmatory\tdisgust\t0\nconfirmatory\tfear\t0\nconfirmatory\tjoy\t0\nconfirmatory\tnegative\t0\nconfirmatory\tpositive\t0\nconfirmatory\tsadness\t0\nconfirmatory\tsurprise\t0\nconfirmatory\ttrust\t0\nconfirmed\tanger\t0\nconfirmed\tanticipation\t0\nconfirmed\tdisgust\t0\nconfirmed\tfear\t0\nconfirmed\tjoy\t0\nconfirmed\tnegative\t0\nconfirmed\tpositive\t1\nconfirmed\tsadness\t0\nconfirmed\tsurprise\t0\nconfirmed\ttrust\t1\nconfiscate\tanger\t1\nconfiscate\tanticipation\t0\nconfiscate\tdisgust\t0\nconfiscate\tfear\t0\nconfiscate\tjoy\t0\nconfiscate\tnegative\t1\nconfiscate\tpositive\t0\nconfiscate\tsadness\t1\nconfiscate\tsurprise\t0\nconfiscate\ttrust\t0\nconfiscation\tanger\t0\nconfiscation\tanticipation\t0\nconfiscation\tdisgust\t0\nconfiscation\tfear\t0\nconfiscation\tjoy\t0\nconfiscation\tnegative\t1\nconfiscation\tpositive\t0\nconfiscation\tsadness\t0\nconfiscation\tsurprise\t0\nconfiscation\ttrust\t0\nconflagration\tanger\t1\nconflagration\tanticipation\t0\nconflagration\tdisgust\t0\nconflagration\tfear\t1\nconflagration\tjoy\t0\nconflagration\tnegative\t1\nconflagration\tpositive\t0\nconflagration\tsadness\t0\nconflagration\tsurprise\t0\nconflagration\ttrust\t0\nconflict\tanger\t1\nconflict\tanticipation\t0\nconflict\tdisgust\t0\nconflict\tfear\t1\nconflict\tjoy\t0\nconflict\tnegative\t1\nconflict\tpositive\t0\nconflict\tsadness\t1\nconflict\tsurprise\t0\nconflict\ttrust\t0\nconflicting\tanger\t0\nconflicting\tanticipation\t0\nconflicting\tdisgust\t0\nconflicting\tfear\t0\nconflicting\tjoy\t0\nconflicting\tnegative\t1\nconflicting\tpositive\t0\nconflicting\tsadness\t0\nconflicting\tsurprise\t0\nconflicting\ttrust\t0\nconfluence\tanger\t0\nconfluence\tanticipation\t0\nconfluence\tdisgust\t0\nconfluence\tfear\t0\nconfluence\tjoy\t0\nconfluence\tnegative\t0\nconfluence\tpositive\t0\nconfluence\tsadness\t0\nconfluence\tsurprise\t0\nconfluence\ttrust\t0\nconformance\tanger\t0\nconformance\tanticipation\t0\nconformance\tdisgust\t0\nconformance\tfear\t0\nconformance\tjoy\t0\nconformance\tnegative\t0\nconformance\tpositive\t1\nconformance\tsadness\t0\nconformance\tsurprise\t0\nconformance\ttrust\t0\nconformation\tanger\t0\nconformation\tanticipation\t0\nconformation\tdisgust\t0\nconformation\tfear\t0\nconformation\tjoy\t0\nconformation\tnegative\t0\nconformation\tpositive\t0\nconformation\tsadness\t0\nconformation\tsurprise\t0\nconformation\ttrust\t0\nconformity\tanger\t0\nconformity\tanticipation\t0\nconformity\tdisgust\t0\nconformity\tfear\t0\nconformity\tjoy\t0\nconformity\tnegative\t0\nconformity\tpositive\t0\nconformity\tsadness\t0\nconformity\tsurprise\t0\nconformity\ttrust\t1\nconfound\tanger\t0\nconfound\tanticipation\t0\nconfound\tdisgust\t0\nconfound\tfear\t0\nconfound\tjoy\t0\nconfound\tnegative\t1\nconfound\tpositive\t0\nconfound\tsadness\t0\nconfound\tsurprise\t0\nconfound\ttrust\t0\nconfounded\tanger\t0\nconfounded\tanticipation\t0\nconfounded\tdisgust\t0\nconfounded\tfear\t0\nconfounded\tjoy\t0\nconfounded\tnegative\t1\nconfounded\tpositive\t0\nconfounded\tsadness\t0\nconfounded\tsurprise\t0\nconfounded\ttrust\t0\nconfront\tanger\t1\nconfront\tanticipation\t0\nconfront\tdisgust\t0\nconfront\tfear\t0\nconfront\tjoy\t0\nconfront\tnegative\t0\nconfront\tpositive\t0\nconfront\tsadness\t0\nconfront\tsurprise\t0\nconfront\ttrust\t0\nconfuse\tanger\t0\nconfuse\tanticipation\t0\nconfuse\tdisgust\t0\nconfuse\tfear\t0\nconfuse\tjoy\t0\nconfuse\tnegative\t1\nconfuse\tpositive\t0\nconfuse\tsadness\t0\nconfuse\tsurprise\t0\nconfuse\ttrust\t0\nconfusion\tanger\t1\nconfusion\tanticipation\t0\nconfusion\tdisgust\t0\nconfusion\tfear\t1\nconfusion\tjoy\t0\nconfusion\tnegative\t1\nconfusion\tpositive\t0\nconfusion\tsadness\t0\nconfusion\tsurprise\t0\nconfusion\ttrust\t0\ncongenial\tanger\t0\ncongenial\tanticipation\t0\ncongenial\tdisgust\t0\ncongenial\tfear\t0\ncongenial\tjoy\t0\ncongenial\tnegative\t0\ncongenial\tpositive\t1\ncongenial\tsadness\t0\ncongenial\tsurprise\t0\ncongenial\ttrust\t0\ncongenital\tanger\t0\ncongenital\tanticipation\t0\ncongenital\tdisgust\t0\ncongenital\tfear\t0\ncongenital\tjoy\t0\ncongenital\tnegative\t0\ncongenital\tpositive\t0\ncongenital\tsadness\t0\ncongenital\tsurprise\t0\ncongenital\ttrust\t0\ncongestion\tanger\t0\ncongestion\tanticipation\t0\ncongestion\tdisgust\t0\ncongestion\tfear\t0\ncongestion\tjoy\t0\ncongestion\tnegative\t1\ncongestion\tpositive\t0\ncongestion\tsadness\t0\ncongestion\tsurprise\t0\ncongestion\ttrust\t0\nconglomerate\tanger\t0\nconglomerate\tanticipation\t0\nconglomerate\tdisgust\t0\nconglomerate\tfear\t0\nconglomerate\tjoy\t0\nconglomerate\tnegative\t0\nconglomerate\tpositive\t0\nconglomerate\tsadness\t0\nconglomerate\tsurprise\t0\nconglomerate\ttrust\t1\nconglomeration\tanger\t0\nconglomeration\tanticipation\t0\nconglomeration\tdisgust\t0\nconglomeration\tfear\t0\nconglomeration\tjoy\t0\nconglomeration\tnegative\t0\nconglomeration\tpositive\t0\nconglomeration\tsadness\t0\nconglomeration\tsurprise\t0\nconglomeration\ttrust\t0\ncongratulatory\tanger\t0\ncongratulatory\tanticipation\t0\ncongratulatory\tdisgust\t0\ncongratulatory\tfear\t0\ncongratulatory\tjoy\t1\ncongratulatory\tnegative\t0\ncongratulatory\tpositive\t1\ncongratulatory\tsadness\t0\ncongratulatory\tsurprise\t0\ncongratulatory\ttrust\t0\ncongregate\tanger\t0\ncongregate\tanticipation\t0\ncongregate\tdisgust\t0\ncongregate\tfear\t0\ncongregate\tjoy\t0\ncongregate\tnegative\t0\ncongregate\tpositive\t0\ncongregate\tsadness\t0\ncongregate\tsurprise\t0\ncongregate\ttrust\t0\ncongregation\tanger\t0\ncongregation\tanticipation\t0\ncongregation\tdisgust\t0\ncongregation\tfear\t0\ncongregation\tjoy\t0\ncongregation\tnegative\t0\ncongregation\tpositive\t1\ncongregation\tsadness\t0\ncongregation\tsurprise\t0\ncongregation\ttrust\t1\ncongress\tanger\t0\ncongress\tanticipation\t0\ncongress\tdisgust\t1\ncongress\tfear\t0\ncongress\tjoy\t0\ncongress\tnegative\t0\ncongress\tpositive\t0\ncongress\tsadness\t0\ncongress\tsurprise\t0\ncongress\ttrust\t1\ncongressional\tanger\t0\ncongressional\tanticipation\t0\ncongressional\tdisgust\t0\ncongressional\tfear\t0\ncongressional\tjoy\t0\ncongressional\tnegative\t0\ncongressional\tpositive\t0\ncongressional\tsadness\t0\ncongressional\tsurprise\t0\ncongressional\ttrust\t0\ncongressman\tanger\t0\ncongressman\tanticipation\t0\ncongressman\tdisgust\t0\ncongressman\tfear\t0\ncongressman\tjoy\t0\ncongressman\tnegative\t0\ncongressman\tpositive\t0\ncongressman\tsadness\t0\ncongressman\tsurprise\t0\ncongressman\ttrust\t1\ncongruence\tanger\t0\ncongruence\tanticipation\t0\ncongruence\tdisgust\t0\ncongruence\tfear\t0\ncongruence\tjoy\t0\ncongruence\tnegative\t0\ncongruence\tpositive\t1\ncongruence\tsadness\t0\ncongruence\tsurprise\t0\ncongruence\ttrust\t1\nconic\tanger\t0\nconic\tanticipation\t0\nconic\tdisgust\t0\nconic\tfear\t0\nconic\tjoy\t0\nconic\tnegative\t0\nconic\tpositive\t0\nconic\tsadness\t0\nconic\tsurprise\t0\nconic\ttrust\t0\nconical\tanger\t0\nconical\tanticipation\t0\nconical\tdisgust\t0\nconical\tfear\t0\nconical\tjoy\t0\nconical\tnegative\t0\nconical\tpositive\t0\nconical\tsadness\t0\nconical\tsurprise\t0\nconical\ttrust\t0\nconjecture\tanger\t0\nconjecture\tanticipation\t1\nconjecture\tdisgust\t0\nconjecture\tfear\t0\nconjecture\tjoy\t0\nconjecture\tnegative\t0\nconjecture\tpositive\t0\nconjecture\tsadness\t0\nconjecture\tsurprise\t0\nconjecture\ttrust\t0\nconjugal\tanger\t0\nconjugal\tanticipation\t0\nconjugal\tdisgust\t0\nconjugal\tfear\t0\nconjugal\tjoy\t0\nconjugal\tnegative\t0\nconjugal\tpositive\t0\nconjugal\tsadness\t0\nconjugal\tsurprise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conspicuous\tsurprise\t0\nconspicuous\ttrust\t0\nconspiracy\tanger\t0\nconspiracy\tanticipation\t0\nconspiracy\tdisgust\t0\nconspiracy\tfear\t1\nconspiracy\tjoy\t0\nconspiracy\tnegative\t0\nconspiracy\tpositive\t0\nconspiracy\tsadness\t0\nconspiracy\tsurprise\t0\nconspiracy\ttrust\t0\nconspirator\tanger\t1\nconspirator\tanticipation\t1\nconspirator\tdisgust\t1\nconspirator\tfear\t1\nconspirator\tjoy\t0\nconspirator\tnegative\t1\nconspirator\tpositive\t0\nconspirator\tsadness\t0\nconspirator\tsurprise\t0\nconspirator\ttrust\t0\nconspire\tanger\t0\nconspire\tanticipation\t0\nconspire\tdisgust\t0\nconspire\tfear\t1\nconspire\tjoy\t0\nconspire\tnegative\t1\nconspire\tpositive\t0\nconspire\tsadness\t0\nconspire\tsurprise\t0\nconspire\ttrust\t0\nconstable\tanger\t0\nconstable\tanticipation\t0\nconstable\tdisgust\t0\nconstable\tfear\t0\nconstable\tjoy\t0\nconstable\tnegative\t0\nconstable\tpositive\t0\nconstable\tsadness\t0\nconstable\tsurprise\t0\nconstable\ttrust\t1\nconstancy\tanger\t0\nconstancy\tanticipation\t0\nconstancy\tdisgust\t0\nconstancy\tfear\t0\nconstancy\tjoy\t0\nconstancy\tnegative\t0\nconstancy\tpositive\t1\nconstancy\tsadness\t0\nconstancy\tsurprise\t0\nconstancy\ttrust\t1\nconstant\tanger\t0\nconstant\tanticipation\t0\nconstant\tdisgust\t0\nconstant\tfear\t0\nconstant\tjoy\t0\nconstant\tnegative\t0\nconstant\tpositive\t1\nconstant\tsadness\t0\nconstant\tsurprise\t0\nconstant\ttrust\t1\nconstantly\tanger\t0\nconstantly\tanticipation\t0\nconstantly\tdisgust\t0\nconstantly\tfear\t0\nconstantly\tjoy\t0\nconstantly\tnegative\t0\nconstantly\tpositive\t0\nconstantly\tsadness\t0\nconstantly\tsurprise\t0\nconstantly\ttrust\t1\nconstellation\tanger\t0\nconstellation\tanticipation\t0\nconstellation\tdisgust\t0\nconstellation\tfear\t0\nconstellation\tjoy\t0\nconstellation\tnegative\t0\nconstellation\tpositive\t0\nconstellation\tsadness\t0\nconstellation\tsurprise\t0\nconstellation\ttrust\t0\nconsternation\tanger\t1\nconsternation\tanticipation\t0\nconsternation\tdisgust\t0\nconsternation\tfear\t1\nconsternation\tjoy\t0\nconsternation\tnegative\t1\nconsternation\tpositive\t0\nconsternation\tsadness\t0\nconsternation\tsurprise\t0\nconsternation\ttrust\t0\nconstipation\tanger\t0\nconstipation\tanticipation\t0\nconstipation\tdisgust\t1\nconstipation\tfear\t0\nconstipation\tjoy\t0\nconstipation\tnegative\t1\nconstipation\tpositive\t0\nconstipation\tsadness\t0\nconstipation\tsurprise\t0\nconstipation\ttrust\t0\nconstituent\tanger\t0\nconstituent\tanticipation\t0\nconstituent\tdisgust\t0\nconstituent\tfear\t0\nconstituent\tjoy\t0\nconstituent\tnegative\t0\nconstituent\tpositive\t0\nconstituent\tsadness\t0\nconstituent\tsurprise\t0\nconstituent\ttrust\t0\nconstituents\tanger\t0\nconstituents\tanticipation\t0\nconstituents\tdisgust\t0\nconstituents\tfear\t0\nconstituents\tjoy\t0\nconstituents\tnegative\t0\nconstituents\tpositive\t0\nconstituents\tsadness\t0\nconstituents\tsurprise\t0\nconstituents\ttrust\t0\nconstitute\tanger\t0\nconstitute\tanticipation\t0\nconstitute\tdisgust\t0\nconstitute\tfear\t0\nconstitute\tjoy\t0\nconstitute\tnegative\t0\nconstitute\tpositive\t0\nconstitute\tsadness\t0\nconstitute\tsurprise\t0\nconstitute\ttrust\t1\nconstitution\tanger\t0\nconstitution\tanticipation\t0\nconstitution\tdisgust\t0\nconstitution\tfear\t0\nconstitution\tjoy\t0\nconstitution\tnegative\t0\nconstitution\tpositive\t0\nconstitution\tsadness\t0\nconstitution\tsurprise\t0\nconstitution\ttrust\t0\nconstitutional\tanger\t0\nconstitutional\tanticipation\t0\nconstitutional\tdisgust\t0\nconstitutional\tfear\t0\nconstitutional\tjoy\t0\nconstitutional\tnegative\t0\nconstitutional\tpositive\t1\nconstitutional\tsadness\t0\nconstitutional\tsurprise\t0\nconstitutional\ttrust\t1\nconstitutionality\tanger\t0\nconstitutionality\tanticipation\t0\nconstitutionality\tdisgust\t0\nconstitutionality\tfear\t0\nconstitutionality\tjoy\t0\nconstitutionality\tnegative\t0\nconstitutionality\tpositive\t0\nconstitutionality\tsadness\t0\nconstitutionality\tsurprise\t0\nconstitutionality\ttrust\t0\nconstrain\tanger\t0\nconstrain\tanticipation\t0\nconstrain\tdisgust\t0\nconstrain\tfear\t1\nconstrain\tjoy\t0\nconstrain\tnegative\t1\nconstrain\tpositive\t0\nconstrain\tsadness\t0\nconstrain\tsurprise\t0\nconstrain\ttrust\t0\nconstrained\tanger\t0\nconstrained\tanticipation\t0\nconstrained\tdisgust\t0\nconstrained\tfear\t0\nconstrained\tjoy\t0\nconstrained\tnegative\t1\nconstrained\tpositive\t0\nconstrained\tsadness\t0\nconstrained\tsurprise\t0\nconstrained\ttrust\t0\nconstraint\tanger\t1\nconstraint\tanticipation\t0\nconstraint\tdisgust\t0\nconstraint\tfear\t1\nconstraint\tjoy\t0\nconstraint\tnegative\t1\nconstraint\tpositive\t0\nconstraint\tsadness\t1\nconstraint\tsurprise\t0\nconstraint\ttrust\t0\nconstruct\tanger\t0\nconstruct\tanticipation\t0\nconstruct\tdisgust\t0\nconstruct\tfear\t0\nconstruct\tjoy\t0\nconstruct\tnegative\t0\nconstruct\tpositive\t1\nconstruct\tsadness\t0\nconstruct\tsurprise\t0\nconstruct\ttrust\t0\nconstruction\tanger\t0\nconstruction\tanticipation\t0\nconstruction\tdisgust\t0\nconstruction\tfear\t0\nconstruction\tjoy\t0\nconstruction\tnegative\t0\nconstruction\tpositive\t0\nconstruction\tsadness\t0\nconstruction\tsurprise\t0\nconstruction\ttrust\t0\nconstrue\tanger\t0\nconstrue\tanticipation\t0\nconstrue\tdisgust\t0\nconstrue\tfear\t0\nconstrue\tjoy\t0\nconstrue\tnegative\t0\nconstrue\tpositive\t0\nconstrue\tsadness\t0\nconstrue\tsurprise\t0\nconstrue\ttrust\t0\nconsul\tanger\t0\nconsul\tanticipation\t0\nconsul\tdisgust\t0\nconsul\tfear\t0\nconsul\tjoy\t0\nconsul\tnegative\t0\nconsul\tpositive\t0\nconsul\tsadness\t0\nconsul\tsurprise\t0\nconsul\ttrust\t1\nconsult\tanger\t0\nconsult\tanticipation\t0\nconsult\tdisgust\t0\nconsult\tfear\t0\nconsult\tjoy\t0\nconsult\tnegative\t0\nconsult\tpositive\t0\nconsult\tsadness\t0\nconsult\tsurprise\t0\nconsult\ttrust\t1\nconsultation\tanger\t0\nconsultation\tanticipation\t0\nconsultation\tdisgust\t0\nconsultation\tfear\t0\nconsultation\tjoy\t0\nconsultation\tnegative\t0\nconsultation\tpositive\t0\nconsultation\tsadness\t0\nconsultation\tsurprise\t0\nconsultation\ttrust\t0\nconsume\tanger\t0\nconsume\tanticipation\t0\nconsume\tdisgust\t0\nconsume\tfear\t0\nconsume\tjoy\t0\nconsume\tnegative\t0\nconsume\tpositive\t0\nconsume\tsadness\t0\nconsume\tsurprise\t0\nconsume\ttrust\t0\nconsuming\tanger\t0\nconsuming\tanticipation\t0\nconsuming\tdisgust\t0\nconsuming\tfear\t0\nconsuming\tjoy\t0\nconsuming\tnegative\t0\nconsuming\tpositive\t0\nconsuming\tsadness\t0\nconsuming\tsurprise\t0\nconsuming\ttrust\t0\nconsummate\tanger\t0\nconsummate\tanticipation\t0\nconsummate\tdisgust\t0\nconsummate\tfear\t0\nconsummate\tjoy\t0\nconsummate\tnegative\t0\nconsummate\tpositive\t1\nconsummate\tsadness\t0\nconsummate\tsurprise\t0\nconsummate\ttrust\t0\nconsummation\tanger\t0\nconsummation\tanticipation\t0\nconsummation\tdisgust\t0\nconsummation\tfear\t0\nconsummation\tjoy\t0\nconsummation\tnegative\t0\nconsummation\tpositive\t0\nconsummation\tsadness\t0\nconsummation\tsurprise\t0\nconsummation\ttrust\t0\nconsumption\tanger\t0\nconsumption\tanticipation\t0\nconsumption\tdisgust\t0\nconsumption\tfear\t0\nconsumption\tjoy\t0\nconsumption\tnegative\t0\nconsumption\tpositive\t0\nconsumption\tsadness\t0\nconsumption\tsurprise\t0\nconsumption\ttrust\t0\ncontact\tanger\t0\ncontact\tanticipation\t0\ncontact\tdisgust\t0\ncontact\tfear\t0\ncontact\tjoy\t0\ncontact\tnegative\t0\ncontact\tpositive\t1\ncontact\tsadness\t0\ncontact\tsurprise\t0\ncontact\ttrust\t0\ncontagion\tanger\t0\ncontagion\tanticipation\t1\ncontagion\tdisgust\t1\ncontagion\tfear\t1\ncontagion\tjoy\t0\ncontagion\tnegative\t1\ncontagion\tpositive\t0\ncontagion\tsadness\t0\ncontagion\tsurprise\t0\ncontagion\ttrust\t0\ncontagious\tanger\t0\ncontagious\tanticipation\t0\ncontagious\tdisgust\t1\ncontagious\tfear\t1\ncontagious\tjoy\t0\ncontagious\tnegative\t1\ncontagious\tpositive\t0\ncontagious\tsadness\t0\ncontagious\tsurprise\t0\ncontagious\ttrust\t0\ncontainment\tanger\t0\ncontainment\tanticipation\t0\ncontainment\tdisgust\t0\ncontainment\tfear\t0\ncontainment\tjoy\t0\ncontainment\tnegative\t0\ncontainment\tpositive\t0\ncontainment\tsadness\t0\ncontainment\tsurprise\t0\ncontainment\ttrust\t0\ncontaminate\tanger\t0\ncontaminate\tanticipation\t0\ncontaminate\tdisgust\t1\ncontaminate\tfear\t0\ncontaminate\tjoy\t0\ncontaminate\tnegative\t1\ncontaminate\tpositive\t0\ncontaminate\tsadness\t0\ncontaminate\tsurprise\t0\ncontaminate\ttrust\t0\ncontaminated\tanger\t0\ncontaminated\tanticipation\t0\ncontaminated\tdisgust\t1\ncontaminated\tfear\t1\ncontaminated\tjoy\t0\ncontaminated\tnegative\t1\ncontaminated\tpositive\t0\ncontaminated\tsadness\t1\ncontaminated\tsurprise\t0\ncontaminated\ttrust\t0\ncontamination\tanger\t0\ncontamination\tanticipation\t0\ncontamination\tdisgust\t1\ncontamination\tfear\t0\ncontamination\tjoy\t0\ncontamination\tnegative\t1\ncontamination\tpositive\t0\ncontamination\tsadness\t0\ncontamination\tsurprise\t0\ncontamination\ttrust\t0\ncontemplate\tanger\t0\ncontemplate\tanticipation\t0\ncontemplate\tdisgust\t0\ncontemplate\tfear\t0\ncontemplate\tjoy\t0\ncontemplate\tnegative\t0\ncontemplate\tpositive\t0\ncontemplate\tsadness\t0\ncontemplate\tsurprise\t0\ncontemplate\ttrust\t0\ncontemplation\tanger\t0\ncontemplation\tanticipation\t0\ncontemplation\tdisgust\t0\ncontemplation\tfear\t0\ncontemplation\tjoy\t0\ncontemplation\tnegative\t0\ncontemplation\tpositive\t1\ncontemplation\tsadness\t0\ncontemplation\tsurprise\t0\ncontemplation\ttrust\t0\ncontemplative\tanger\t0\ncontemplative\tanticipation\t0\ncontemplative\tdisgust\t0\ncontemplative\tfear\t0\ncontemplative\tjoy\t0\ncontemplative\tnegative\t0\ncontemplative\tpositive\t0\ncontemplative\tsadness\t0\ncontemplative\tsurprise\t0\ncontemplative\ttrust\t0\ncontemporaneous\tanger\t0\ncontemporaneous\tanticipation\t0\ncontemporaneous\tdisgust\t0\ncontemporaneous\tfear\t0\ncontemporaneous\tjoy\t0\ncontemporaneous\tnegative\t0\ncontemporaneous\tpositive\t0\ncontemporaneous\tsadness\t0\ncontemporaneous\tsurprise\t0\ncontemporaneous\ttrust\t0\ncontemporary\tanger\t0\ncontemporary\tanticipation\t0\ncontemporary\tdisgust\t0\ncontemporary\tfear\t0\ncontemporary\tjoy\t0\ncontemporary\tnegative\t0\ncontemporary\tpositive\t0\ncontemporary\tsadness\t0\ncontemporary\tsurprise\t0\ncontemporary\ttrust\t0\ncontempt\tanger\t1\ncontempt\tanticipation\t0\ncontempt\tdisgust\t1\ncontempt\tfear\t1\ncontempt\tjoy\t0\ncontempt\tnegative\t1\ncontempt\tpositive\t0\ncontempt\tsadness\t0\ncontempt\tsurprise\t0\ncontempt\ttrust\t0\ncontemptible\tanger\t1\ncontemptible\tanticipation\t0\ncontemptible\tdisgust\t1\ncontemptible\tfear\t0\ncontemptible\tjoy\t0\ncontemptible\tnegative\t1\ncontemptible\tpositive\t0\ncontemptible\tsadness\t0\ncontemptible\tsurprise\t0\ncontemptible\ttrust\t0\ncontemptuous\tanger\t1\ncontemptuous\tanticipation\t0\ncontemptuous\tdisgust\t0\ncontemptuous\tfear\t0\ncontemptuous\tjoy\t0\ncontemptuous\tnegative\t1\ncontemptuous\tpositive\t0\ncontemptuous\tsadness\t0\ncontemptuous\tsurprise\t0\ncontemptuous\ttrust\t0\ncontending\tanger\t0\ncontending\tanticipation\t0\ncontending\tdisgust\t0\ncontending\tfear\t0\ncontending\tjoy\t0\ncontending\tnegative\t0\ncontending\tpositive\t0\ncontending\tsadness\t0\ncontending\tsurprise\t0\ncontending\ttrust\t0\ncontent\tanger\t0\ncontent\tanticipation\t0\ncontent\tdisgust\t0\ncontent\tfear\t0\ncontent\tjoy\t1\ncontent\tnegative\t0\ncontent\tpositive\t1\ncontent\tsadness\t0\ncontent\tsurprise\t0\ncontent\ttrust\t1\ncontention\tanger\t0\ncontention\tanticipation\t0\ncontention\tdisgust\t0\ncontention\tfear\t0\ncontention\tjoy\t0\ncontention\tnegative\t0\ncontention\tpositive\t0\ncontention\tsadness\t0\ncontention\tsurprise\t0\ncontention\ttrust\t0\ncontentious\tanger\t1\ncontentious\tanticipation\t0\ncontentious\tdisgust\t1\ncontentious\tfear\t1\ncontentious\tjoy\t0\ncontentious\tnegative\t1\ncontentious\tpositive\t0\ncontentious\tsadness\t0\ncontentious\tsurprise\t0\ncontentious\ttrust\t0\ncontents\tanger\t0\ncontents\tanticipation\t0\ncontents\tdisgust\t0\ncontents\tfear\t0\ncontents\tjoy\t0\ncontents\tnegative\t0\ncontents\tpositive\t0\ncontents\tsadness\t0\ncontents\tsurprise\t0\ncontents\ttrust\t0\ncontext\tanger\t0\ncontext\tanticipation\t0\ncontext\tdisgust\t0\ncontext\tfear\t0\ncontext\tjoy\t0\ncontext\tnegative\t0\ncontext\tpositive\t0\ncontext\tsadness\t0\ncontext\tsurprise\t0\ncontext\ttrust\t0\ncontiguous\tanger\t0\ncontiguous\tanticipation\t0\ncontiguous\tdisgust\t0\ncontiguous\tfear\t0\ncontiguous\tjoy\t0\ncontiguous\tnegative\t0\ncontiguous\tpositive\t0\ncontiguous\tsadness\t0\ncontiguous\tsurprise\t0\ncontiguous\ttrust\t0\ncontinence\tanger\t0\ncontinence\tanticipation\t0\ncontinence\tdisgust\t0\ncontinence\tfear\t0\ncontinence\tjoy\t0\ncontinence\tnegative\t0\ncontinence\tpositive\t0\ncontinence\tsadness\t0\ncontinence\tsurprise\t0\ncontinence\ttrust\t0\ncontinent\tanger\t0\ncontinent\tanticipation\t0\ncontinent\tdisgust\t0\ncontinent\tfear\t0\ncontinent\tjoy\t0\ncontinent\tnegative\t0\ncontinent\tpositive\t0\ncontinent\tsadness\t0\ncontinent\tsurprise\t0\ncontinent\ttrust\t0\ncontinental\tanger\t0\ncontinental\tanticipation\t0\ncontinental\tdisgust\t0\ncontinental\tfear\t0\ncontinental\tjoy\t0\ncontinental\tnegative\t0\ncontinental\tpositive\t0\ncontinental\tsadness\t0\ncontinental\tsurprise\t0\ncontinental\ttrust\t0\ncontingency\tanger\t0\ncontingency\tanticipation\t0\ncontingency\tdisgust\t0\ncontingency\tfear\t0\ncontingency\tjoy\t0\ncontingency\tnegative\t0\ncontingency\tpositive\t0\ncontingency\tsadness\t0\ncontingency\tsurprise\t0\ncontingency\ttrust\t0\ncontingent\tanger\t0\ncontingent\tanticipation\t1\ncontingent\tdisgust\t0\ncontingent\tfear\t0\ncontingent\tjoy\t0\ncontingent\tnegative\t0\ncontingent\tpositive\t0\ncontingent\tsadness\t0\ncontingent\tsurprise\t0\ncontingent\ttrust\t0\ncontinual\tanger\t0\ncontinual\tanticipation\t0\ncontinual\tdisgust\t0\ncontinual\tfear\t0\ncontinual\tjoy\t0\ncontinual\tnegative\t0\ncontinual\tpositive\t0\ncontinual\tsadness\t0\ncontinual\tsurprise\t0\ncontinual\ttrust\t0\ncontinually\tanger\t0\ncontinually\tanticipation\t0\ncontinually\tdisgust\t0\ncontinually\tfear\t0\ncontinually\tjoy\t0\ncontinually\tnegative\t0\ncontinually\tpositive\t0\ncontinually\tsadness\t0\ncontinually\tsurprise\t0\ncontinually\ttrust\t0\ncontinuance\tanger\t0\ncontinuance\tanticipation\t0\ncontinuance\tdisgust\t0\ncontinuance\tfear\t0\ncontinuance\tjoy\t0\ncontinuance\tnegative\t0\ncontinuance\tpositive\t0\ncontinuance\tsadness\t0\ncontinuance\tsurprise\t0\ncontinuance\ttrust\t0\ncontinuation\tanger\t0\ncontinuation\tanticipation\t1\ncontinuation\tdisgust\t0\ncontinuation\tfear\t0\ncontinuation\tjoy\t0\ncontinuation\tnegative\t0\ncontinuation\tpositive\t0\ncontinuation\tsadness\t0\ncontinuation\tsurprise\t0\ncontinuation\ttrust\t0\ncontinue\tanger\t0\ncontinue\tanticipation\t1\ncontinue\tdisgust\t0\ncontinue\tfear\t0\ncontinue\tjoy\t0\ncontinue\tnegative\t0\ncontinue\tpositive\t1\ncontinue\tsadness\t0\ncontinue\tsurprise\t0\ncontinue\ttrust\t1\ncontinued\tanger\t0\ncontinued\tanticipation\t0\ncontinued\tdisgust\t0\ncontinued\tfear\t0\ncontinued\tjoy\t0\ncontinued\tnegative\t0\ncontinued\tpositive\t0\ncontinued\tsadness\t0\ncontinued\tsurprise\t0\ncontinued\ttrust\t0\ncontinuing\tanger\t0\ncontinuing\tanticipation\t0\ncontinuing\tdisgust\t0\ncontinuing\tfear\t0\ncontinuing\tjoy\t0\ncontinuing\tnegative\t0\ncontinuing\tpositive\t0\ncontinuing\tsadness\t0\ncontinuing\tsurprise\t0\ncontinuing\ttrust\t0\ncontinuity\tanger\t0\ncontinuity\tanticipation\t0\ncontinuity\tdisgust\t0\ncontinuity\tfear\t0\ncontinuity\tjoy\t0\ncontinuity\tnegative\t0\ncontinuity\tpositive\t0\ncontinuity\tsadness\t0\ncontinuity\tsurprise\t0\ncontinuity\ttrust\t0\ncontinuous\tanger\t0\ncontinuous\tanticipation\t0\ncontinuous\tdisgust\t0\ncontinuous\tfear\t0\ncontinuous\tjoy\t0\ncontinuous\tnegative\t0\ncontinuous\tpositive\t0\ncontinuous\tsadness\t0\ncontinuous\tsurprise\t0\ncontinuous\ttrust\t0\ncontinuously\tanger\t0\ncontinuously\tanticipation\t0\ncontinuously\tdisgust\t0\ncontinuously\tfear\t0\ncontinuously\tjoy\t0\ncontinuously\tnegative\t0\ncontinuously\tpositive\t0\ncontinuously\tsadness\t0\ncontinuously\tsurprise\t0\ncontinuously\ttrust\t0\ncontour\tanger\t0\ncontour\tanticipation\t0\ncontour\tdisgust\t0\ncontour\tfear\t0\ncontour\tjoy\t0\ncontour\tnegative\t0\ncontour\tpositive\t1\ncontour\tsadness\t0\ncontour\tsurprise\t0\ncontour\ttrust\t0\ncontraband\tanger\t1\ncontraband\tanticipation\t0\ncontraband\tdisgust\t1\ncontraband\tfear\t1\ncontraband\tjoy\t0\ncontraband\tnegative\t1\ncontraband\tpositive\t0\ncontraband\tsadness\t0\ncontraband\tsurprise\t0\ncontraband\ttrust\t0\ncontract\tanger\t0\ncontract\tanticipation\t0\ncontract\tdisgust\t0\ncontract\tfear\t0\ncontract\tjoy\t0\ncontract\tnegative\t0\ncontract\tpositive\t0\ncontract\tsadness\t0\ncontract\tsurprise\t0\ncontract\ttrust\t0\ncontracted\tanger\t0\ncontracted\tanticipation\t0\ncontracted\tdisgust\t0\ncontracted\tfear\t0\ncontracted\tjoy\t0\ncontracted\tnegative\t1\ncontracted\tpositive\t0\ncontracted\tsadness\t0\ncontracted\tsurprise\t0\ncontracted\ttrust\t0\ncontractile\tanger\t0\ncontractile\tanticipation\t0\ncontractile\tdisgust\t0\ncontractile\tfear\t0\ncontractile\tjoy\t0\ncontractile\tnegative\t0\ncontractile\tpositive\t0\ncontractile\tsadness\t0\ncontractile\tsurprise\t0\ncontractile\ttrust\t0\ncontracting\tanger\t0\ncontracting\tanticipation\t0\ncontracting\tdisgust\t0\ncontracting\tfear\t0\ncontracting\tjoy\t0\ncontracting\tnegative\t0\ncontracting\tpositive\t0\ncontracting\tsadness\t0\ncontracting\tsurprise\t0\ncontracting\ttrust\t0\ncontraction\tanger\t0\ncontraction\tanticipation\t0\ncontraction\tdisgust\t0\ncontraction\tfear\t0\ncontraction\tjoy\t0\ncontraction\tnegative\t0\ncontraction\tpositive\t0\ncontraction\tsadness\t0\ncontraction\tsurprise\t0\ncontraction\ttrust\t0\ncontradict\tanger\t1\ncontradict\tanticipation\t0\ncontradict\tdisgust\t0\ncontradict\tfear\t0\ncontradict\tjoy\t0\ncontradict\tnegative\t1\ncontradict\tpositive\t0\ncontradict\tsadness\t0\ncontradict\tsurprise\t0\ncontradict\ttrust\t0\ncontradiction\tanger\t0\ncontradiction\tanticipation\t0\ncontradiction\tdisgust\t0\ncontradiction\tfear\t0\ncontradiction\tjoy\t0\ncontradiction\tnegative\t1\ncontradiction\tpositive\t0\ncontradiction\tsadness\t0\ncontradiction\tsurprise\t0\ncontradiction\ttrust\t0\ncontradictory\tanger\t0\ncontradictory\tanticipation\t0\ncontradictory\tdisgust\t0\ncontradictory\tfear\t0\ncontradictory\tjoy\t0\ncontradictory\tnegative\t1\ncontradictory\tpositive\t0\ncontradictory\tsadness\t0\ncontradictory\tsurprise\t0\ncontradictory\ttrust\t0\ncontrary\tanger\t0\ncontrary\tanticipation\t0\ncontrary\tdisgust\t0\ncontrary\tfear\t0\ncontrary\tjoy\t0\ncontrary\tnegative\t1\ncontrary\tpositive\t0\ncontrary\tsadness\t0\ncontrary\tsurprise\t0\ncontrary\ttrust\t0\ncontrast\tanger\t0\ncontrast\tanticipation\t0\ncontrast\tdisgust\t0\ncontrast\tfear\t0\ncontrast\tjoy\t0\ncontrast\tnegative\t0\ncontrast\tpositive\t0\ncontrast\tsadness\t0\ncontrast\tsurprise\t0\ncontrast\ttrust\t0\ncontrasted\tanger\t0\ncontrasted\tanticipation\t0\ncontrasted\tdisgust\t0\ncontrasted\tfear\t0\ncontrasted\tjoy\t0\ncontrasted\tnegative\t1\ncontrasted\tpositive\t0\ncontrasted\tsadness\t0\ncontrasted\tsurprise\t0\ncontrasted\ttrust\t0\ncontravene\tanger\t0\ncontravene\tanticipation\t0\ncontravene\tdisgust\t0\ncontravene\tfear\t0\ncontravene\tjoy\t0\ncontravene\tnegative\t1\ncontravene\tpositive\t0\ncontravene\tsadness\t0\ncontravene\tsurprise\t0\ncontravene\ttrust\t0\ncontravention\tanger\t0\ncontravention\tanticipation\t0\ncontravention\tdisgust\t0\ncontravention\tfear\t0\ncontravention\tjoy\t0\ncontravention\tnegative\t1\ncontravention\tpositive\t0\ncontravention\tsadness\t0\ncontravention\tsurprise\t0\ncontravention\ttrust\t0\ncontribute\tanger\t0\ncontribute\tanticipation\t0\ncontribute\tdisgust\t0\ncontribute\tfear\t0\ncontribute\tjoy\t0\ncontribute\tnegative\t0\ncontribute\tpositive\t1\ncontribute\tsadness\t0\ncontribute\tsurprise\t0\ncontribute\ttrust\t0\ncontributor\tanger\t0\ncontributor\tanticipation\t0\ncontributor\tdisgust\t0\ncontributor\tfear\t0\ncontributor\tjoy\t0\ncontributor\tnegative\t0\ncontributor\tpositive\t1\ncontributor\tsadness\t0\ncontributor\tsurprise\t0\ncontributor\ttrust\t1\ncontrived\tanger\t0\ncontrived\tanticipation\t0\ncontrived\tdisgust\t0\ncontrived\tfear\t0\ncontrived\tjoy\t0\ncontrived\tnegative\t0\ncontrived\tpositive\t0\ncontrived\tsadness\t0\ncontrived\tsurprise\t0\ncontrived\ttrust\t0\ncontrol\tanger\t0\ncontrol\tanticipation\t0\ncontrol\tdisgust\t0\ncontrol\tfear\t0\ncontrol\tjoy\t0\ncontrol\tnegative\t0\ncontrol\tpositive\t0\ncontrol\tsadness\t0\ncontrol\tsurprise\t0\ncontrol\ttrust\t0\ncontroversial\tanger\t1\ncontroversial\tanticipation\t0\ncontroversial\tdisgust\t0\ncontroversial\tfear\t0\ncontroversial\tjoy\t0\ncontroversial\tnegative\t1\ncontroversial\tpositive\t0\ncontroversial\tsadness\t0\ncontroversial\tsurprise\t0\ncontroversial\ttrust\t0\ncontroversy\tanger\t0\ncontroversy\tanticipation\t0\ncontroversy\tdisgust\t0\ncontroversy\tfear\t0\ncontroversy\tjoy\t0\ncontroversy\tnegative\t1\ncontroversy\tpositive\t0\ncontroversy\tsadness\t0\ncontroversy\tsurprise\t0\ncontroversy\ttrust\t0\nconundrum\tanger\t0\nconundrum\tanticipation\t0\nconundrum\tdisgust\t0\nconundrum\tfear\t0\nconundrum\tjoy\t0\nconundrum\tnegative\t0\nconundrum\tpositive\t0\nconundrum\tsadness\t0\nconundrum\tsurprise\t0\nconundrum\ttrust\t0\nconvalescent\tanger\t0\nconvalescent\tanticipation\t0\nconvalescent\tdisgust\t0\nconvalescent\tfear\t0\nconvalescent\tjoy\t0\nconvalescent\tnegative\t0\nconvalescent\tpositive\t0\nconvalescent\tsadness\t0\nconvalescent\tsurprise\t0\nconvalescent\ttrust\t0\nconvection\tanger\t0\nconvection\tanticipation\t0\nconvection\tdisgust\t0\nconvection\tfear\t0\nconvection\tjoy\t0\nconvection\tnegative\t0\nconvection\tpositive\t0\nconvection\tsadness\t0\nconvection\tsurprise\t0\nconvection\ttrust\t0\nconvene\tanger\t0\nconvene\tanticipation\t0\nconvene\tdisgust\t0\nconvene\tfear\t0\nconvene\tjoy\t0\nconvene\tnegative\t0\nconvene\tpositive\t0\nconvene\tsadness\t0\nconvene\tsurprise\t0\nconvene\ttrust\t0\nconvenience\tanger\t0\nconvenience\tanticipation\t0\nconvenience\tdisgust\t0\nconvenience\tfear\t0\nconvenience\tjoy\t0\nconvenience\tnegative\t0\nconvenience\tpositive\t1\nconvenience\tsadness\t0\nconvenience\tsurprise\t0\nconvenience\ttrust\t0\nconveniences\tanger\t0\nconveniences\tanticipation\t0\nconveniences\tdisgust\t0\nconveniences\tfear\t0\nconveniences\tjoy\t0\nconveniences\tnegative\t0\nconveniences\tpositive\t0\nconveniences\tsadness\t0\nconveniences\tsurprise\t0\nconveniences\ttrust\t0\nconvenient\tanger\t0\nconvenient\tanticipation\t0\nconvenient\tdisgust\t0\nconvenient\tfear\t0\nconvenient\tjoy\t0\nconvenient\tnegative\t0\nconvenient\tpositive\t1\nconvenient\tsadness\t0\nconvenient\tsurprise\t0\nconvenient\ttrust\t0\nconvent\tanger\t0\nconvent\tanticipation\t0\nconvent\tdisgust\t0\nconvent\tfear\t0\nconvent\tjoy\t0\nconvent\tnegative\t0\nconvent\tpositive\t1\nconvent\tsadness\t0\nconvent\tsurprise\t0\nconvent\ttrust\t1\nconvention\tanger\t0\nconvention\tanticipation\t0\nconvention\tdisgust\t0\nconvention\tfear\t0\nconvention\tjoy\t0\nconvention\tnegative\t0\nconvention\tpositive\t1\nconvention\tsadness\t0\nconvention\tsurprise\t0\nconvention\ttrust\t0\nconventional\tanger\t0\nconventional\tanticipation\t0\nconventional\tdisgust\t0\nconventional\tfear\t0\nconventional\tjoy\t0\nconventional\tnegative\t0\nconventional\tpositive\t0\nconventional\tsadness\t0\nconventional\tsurprise\t0\nconventional\ttrust\t0\nconverge\tanger\t0\nconverge\tanticipation\t0\nconverge\tdisgust\t0\nconverge\tfear\t0\nconverge\tjoy\t0\nconverge\tnegative\t0\nconverge\tpositive\t0\nconverge\tsadness\t0\nconverge\tsurprise\t0\nconverge\ttrust\t0\nconvergence\tanger\t0\nconvergence\tanticipation\t1\nconvergence\tdisgust\t0\nconvergence\tfear\t0\nconvergence\tjoy\t0\nconvergence\tnegative\t0\nconvergence\tpositive\t0\nconvergence\tsadness\t0\nconvergence\tsurprise\t0\nconvergence\ttrust\t0\nconvergent\tanger\t0\nconvergent\tanticipation\t0\nconvergent\tdisgust\t0\nconvergent\tfear\t0\nconvergent\tjoy\t0\nconvergent\tnegative\t0\nconvergent\tpositive\t0\nconvergent\tsadness\t0\nconvergent\tsurprise\t0\nconvergent\ttrust\t0\nconversant\tanger\t0\nconversant\tanticipation\t0\nconversant\tdisgust\t0\nconversant\tfear\t0\nconversant\tjoy\t0\nconversant\tnegative\t0\nconversant\tpositive\t1\nconversant\tsadness\t0\nconversant\tsurprise\t0\nconversant\ttrust\t0\nconversation\tanger\t0\nconversation\tanticipation\t0\nconversation\tdisgust\t0\nconversation\tfear\t0\nconversation\tjoy\t0\nconversation\tnegative\t0\nconversation\tpositive\t0\nconversation\tsadness\t0\nconversation\tsurprise\t0\nconversation\ttrust\t0\nconversational\tanger\t0\nconversational\tanticipation\t0\nconversational\tdisgust\t0\nconversational\tfear\t0\nconversational\tjoy\t0\nconversational\tnegative\t0\nconversational\tpositive\t1\nconversational\tsadness\t0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ion\t0\ndecay\tdisgust\t0\ndecay\tfear\t1\ndecay\tjoy\t0\ndecay\tnegative\t1\ndecay\tpositive\t0\ndecay\tsadness\t1\ndecay\tsurprise\t0\ndecay\ttrust\t0\ndecayed\tanger\t0\ndecayed\tanticipation\t0\ndecayed\tdisgust\t1\ndecayed\tfear\t0\ndecayed\tjoy\t0\ndecayed\tnegative\t1\ndecayed\tpositive\t0\ndecayed\tsadness\t1\ndecayed\tsurprise\t0\ndecayed\ttrust\t0\ndeceased\tanger\t0\ndeceased\tanticipation\t0\ndeceased\tdisgust\t0\ndeceased\tfear\t0\ndeceased\tjoy\t0\ndeceased\tnegative\t1\ndeceased\tpositive\t0\ndeceased\tsadness\t1\ndeceased\tsurprise\t0\ndeceased\ttrust\t0\ndeceit\tanger\t1\ndeceit\tanticipation\t0\ndeceit\tdisgust\t1\ndeceit\tfear\t1\ndeceit\tjoy\t0\ndeceit\tnegative\t1\ndeceit\tpositive\t0\ndeceit\tsadness\t1\ndeceit\tsurprise\t1\ndeceit\ttrust\t0\ndeceitful\tanger\t0\ndeceitful\tanticipation\t0\ndeceitful\tdisgust\t1\ndeceitful\tfear\t0\ndeceitful\tjoy\t0\ndeceitful\tnegative\t1\ndeceitful\tpositive\t0\ndeceitful\tsadness\t1\ndeceitful\tsurprise\t0\ndeceitful\ttrust\t0\ndeceive\tanger\t1\ndeceive\tanticipation\t0\ndeceive\tdisgust\t1\ndeceive\tfear\t0\ndeceive\tjoy\t0\ndeceive\tnegative\t1\ndeceive\tpositive\t0\ndeceive\tsadness\t1\ndeceive\tsurprise\t0\ndeceive\ttrust\t0\ndeceived\tanger\t1\ndeceived\tanticipation\t0\ndeceived\tdisgust\t0\ndeceived\tfear\t0\ndeceived\tjoy\t0\ndeceived\tnegative\t1\ndeceived\tpositive\t0\ndeceived\tsadness\t0\ndeceived\tsurprise\t0\ndeceived\ttrust\t0\ndeceiving\tanger\t0\ndeceiving\tanticipation\t0\ndeceiving\tdisgust\t0\ndeceiving\tfear\t0\ndeceiving\tjoy\t0\ndeceiving\tnegative\t1\ndeceiving\tpositive\t0\ndeceiving\tsadness\t0\ndeceiving\tsurprise\t0\ndeceiving\ttrust\t1\ndecency\tanger\t0\ndecency\tanticipation\t0\ndecency\tdisgust\t0\ndecency\tfear\t0\ndecency\tjoy\t0\ndecency\tnegative\t0\ndecency\tpositive\t1\ndecency\tsadness\t0\ndecency\tsurprise\t0\ndecency\ttrust\t0\ndecent\tanger\t0\ndecent\tanticipation\t0\ndecent\tdisgust\t0\ndecent\tfear\t0\ndecent\tjoy\t0\ndecent\tnegative\t0\ndecent\tpositive\t1\ndecent\tsadness\t0\ndecent\tsurprise\t0\ndecent\ttrust\t0\ndeception\tanger\t0\ndeception\tanticipation\t0\ndeception\tdisgust\t0\ndeception\tfear\t0\ndeception\tjoy\t0\ndeception\tnegative\t1\ndeception\tpositive\t0\ndeception\tsadness\t0\ndeception\tsurprise\t0\ndeception\ttrust\t0\ndeceptive\tanger\t0\ndeceptive\tanticipation\t0\ndeceptive\tdisgust\t0\ndeceptive\tfear\t0\ndeceptive\tjoy\t0\ndeceptive\tnegative\t1\ndeceptive\tpositive\t0\ndeceptive\tsadness\t0\ndeceptive\tsurprise\t0\ndeceptive\ttrust\t0\ndecidedly\tanger\t0\ndecidedly\tanticipation\t0\ndecidedly\tdisgust\t0\ndecidedly\tfear\t0\ndecidedly\tjoy\t0\ndecidedly\tnegative\t0\ndecidedly\tpositive\t0\ndecidedly\tsadness\t0\ndecidedly\tsurprise\t0\ndecidedly\ttrust\t0\ndeciduous\tanger\t0\ndeciduous\tanticipation\t0\ndeciduous\tdisgust\t0\ndeciduous\tfear\t0\ndeciduous\tjoy\t0\ndeciduous\tnegative\t0\ndeciduous\tpositive\t0\ndeciduous\tsadness\t0\ndeciduous\tsurprise\t0\ndeciduous\ttrust\t0\ndecimal\tanger\t0\ndecimal\tanticipation\t0\ndecimal\tdisgust\t0\ndecimal\tfear\t0\ndecimal\tjoy\t0\ndecimal\tnegative\t0\ndecimal\tpositive\t0\ndecimal\tsadness\t0\ndecimal\tsurprise\t0\ndecimal\ttrust\t0\ndecipher\tanger\t0\ndecipher\tanticipation\t0\ndecipher\tdisgust\t0\ndecipher\tfear\t0\ndecipher\tjoy\t0\ndecipher\tnegative\t0\ndecipher\tpositive\t0\ndecipher\tsadness\t0\ndecipher\tsurprise\t0\ndecipher\ttrust\t0\ndecision\tanger\t0\ndecision\tanticipation\t0\ndecision\tdisgust\t0\ndecision\tfear\t0\ndecision\tjoy\t0\ndecision\tnegative\t0\ndecision\tpositive\t0\ndecision\tsadness\t0\ndecision\tsurprise\t0\ndecision\ttrust\t0\ndecisive\tanger\t0\ndecisive\tanticipation\t0\ndecisive\tdisgust\t0\ndecisive\tfear\t0\ndecisive\tjoy\t0\ndecisive\tnegative\t0\ndecisive\tpositive\t0\ndecisive\tsadness\t0\ndecisive\tsurprise\t0\ndecisive\ttrust\t0\ndeck\tanger\t0\ndeck\tanticipation\t0\ndeck\tdisgust\t0\ndeck\tfear\t0\ndeck\tjoy\t0\ndeck\tnegative\t0\ndeck\tpositive\t0\ndeck\tsadness\t0\ndeck\tsurprise\t0\ndeck\ttrust\t0\ndeclaration\tanger\t0\ndeclaration\tanticipation\t0\ndeclaration\tdisgust\t0\ndeclaration\tfear\t0\ndeclaration\tjoy\t0\ndeclaration\tnegative\t0\ndeclaration\tpositive\t0\ndeclaration\tsadness\t0\ndeclaration\tsurprise\t0\ndeclaration\ttrust\t0\ndeclaratory\tanger\t0\ndeclaratory\tanticipation\t0\ndeclaratory\tdisgust\t0\ndeclaratory\tfear\t0\ndeclaratory\tjoy\t0\ndeclaratory\tnegative\t0\ndeclaratory\tpositive\t1\ndeclaratory\tsadness\t0\ndeclaratory\tsurprise\t0\ndeclaratory\ttrust\t0\ndeclare\tanger\t0\ndeclare\tanticipation\t0\ndeclare\tdisgust\t0\ndeclare\tfear\t0\ndeclare\tjoy\t0\ndeclare\tnegative\t0\ndeclare\tpositive\t0\ndeclare\tsadness\t0\ndeclare\tsurprise\t0\ndeclare\ttrust\t0\ndeclination\tanger\t0\ndeclination\tanticipation\t0\ndeclination\tdisgust\t0\ndeclination\tfear\t0\ndeclination\tjoy\t0\ndeclination\tnegative\t1\ndeclination\tpositive\t0\ndeclination\tsadness\t0\ndeclination\tsurprise\t0\ndeclination\ttrust\t0\ndecline\tanger\t0\ndecline\tanticipation\t0\ndecline\tdisgust\t0\ndecline\tfear\t0\ndecline\tjoy\t0\ndecline\tnegative\t1\ndecline\tpositive\t0\ndecline\tsadness\t0\ndecline\tsurprise\t0\ndecline\ttrust\t0\ndeclining\tanger\t0\ndeclining\tanticipation\t0\ndeclining\tdisgust\t0\ndeclining\tfear\t0\ndeclining\tjoy\t0\ndeclining\tnegative\t1\ndeclining\tpositive\t0\ndeclining\tsadness\t0\ndeclining\tsurprise\t0\ndeclining\ttrust\t0\ndecompose\tanger\t0\ndecompose\tanticipation\t0\ndecompose\tdisgust\t1\ndecompose\tfear\t0\ndecompose\tjoy\t0\ndecompose\tnegative\t0\ndecompose\tpositive\t0\ndecompose\tsadness\t0\ndecompose\tsurprise\t0\ndecompose\ttrust\t0\ndecomposed\tanger\t0\ndecomposed\tanticipation\t0\ndecomposed\tdisgust\t0\ndecomposed\tfear\t0\ndecomposed\tjoy\t0\ndecomposed\tnegative\t0\ndecomposed\tpositive\t0\ndecomposed\tsadness\t1\ndecomposed\tsurprise\t0\ndecomposed\ttrust\t0\ndecomposition\tanger\t0\ndecomposition\tanticipation\t0\ndecomposition\tdisgust\t1\ndecomposition\tfear\t1\ndecomposition\tjoy\t0\ndecomposition\tnegative\t1\ndecomposition\tpositive\t0\ndecomposition\tsadness\t1\ndecomposition\tsurprise\t0\ndecomposition\ttrust\t0\ndecorate\tanger\t0\ndecorate\tanticipation\t0\ndecorate\tdisgust\t0\ndecorate\tfear\t0\ndecorate\tjoy\t0\ndecorate\tnegative\t0\ndecorate\tpositive\t0\ndecorate\tsadness\t0\ndecorate\tsurprise\t0\ndecorate\ttrust\t0\ndecoration\tanger\t0\ndecoration\tanticipation\t0\ndecoration\tdisgust\t0\ndecoration\tfear\t0\ndecoration\tjoy\t0\ndecoration\tnegative\t0\ndecoration\tpositive\t0\ndecoration\tsadness\t0\ndecoration\tsurprise\t0\ndecoration\ttrust\t0\ndecorum\tanger\t0\ndecorum\tanticipation\t0\ndecorum\tdisgust\t0\ndecorum\tfear\t0\ndecorum\tjoy\t0\ndecorum\tnegative\t0\ndecorum\tpositive\t0\ndecorum\tsadness\t0\ndecorum\tsurprise\t0\ndecorum\ttrust\t0\ndecoy\tanger\t0\ndecoy\tanticipation\t0\ndecoy\tdisgust\t0\ndecoy\tfear\t0\ndecoy\tjoy\t0\ndecoy\tnegative\t0\ndecoy\tpositive\t0\ndecoy\tsadness\t0\ndecoy\tsurprise\t1\ndecoy\ttrust\t0\ndecrease\tanger\t0\ndecrease\tanticipation\t0\ndecrease\tdisgust\t0\ndecrease\tfear\t0\ndecrease\tjoy\t0\ndecrease\tnegative\t1\ndecrease\tpositive\t0\ndecrease\tsadness\t0\ndecrease\tsurprise\t0\ndecrease\ttrust\t0\ndecreased\tanger\t0\ndecreased\tanticipation\t0\ndecreased\tdisgust\t0\ndecreased\tfear\t0\ndecreased\tjoy\t0\ndecreased\tnegative\t0\ndecreased\tpositive\t0\ndecreased\tsadness\t0\ndecreased\tsurprise\t0\ndecreased\ttrust\t0\ndecreasing\tanger\t0\ndecreasing\tanticipation\t0\ndecreasing\tdisgust\t0\ndecreasing\tfear\t0\ndecreasing\tjoy\t0\ndecreasing\tnegative\t0\ndecreasing\tpositive\t0\ndecreasing\tsadness\t0\ndecreasing\tsurprise\t0\ndecreasing\ttrust\t0\ndecree\tanger\t0\ndecree\tanticipation\t0\ndecree\tdisgust\t0\ndecree\tfear\t0\ndecree\tjoy\t0\ndecree\tnegative\t0\ndecree\tpositive\t0\ndecree\tsadness\t0\ndecree\tsurprise\t0\ndecree\ttrust\t0\ndecrement\tanger\t0\ndecrement\tanticipation\t0\ndecrement\tdisgust\t0\ndecrement\tfear\t0\ndecrement\tjoy\t0\ndecrement\tnegative\t1\ndecrement\tpositive\t0\ndecrement\tsadness\t0\ndecrement\tsurprise\t0\ndecrement\ttrust\t0\ndecrepit\tanger\t0\ndecrepit\tanticipation\t0\ndecrepit\tdisgust\t0\ndecrepit\tfear\t0\ndecrepit\tjoy\t0\ndecrepit\tnegative\t1\ndecrepit\tpositive\t0\ndecrepit\tsadness\t0\ndecrepit\tsurprise\t0\ndecrepit\ttrust\t0\ndecry\tanger\t1\ndecry\tanticipation\t0\ndecry\tdisgust\t0\ndecry\tfear\t0\ndecry\tjoy\t0\ndecry\tnegative\t1\ndecry\tpositive\t0\ndecry\tsadness\t0\ndecry\tsurprise\t0\ndecry\ttrust\t0\ndedication\tanger\t0\ndedication\tanticipation\t0\ndedication\tdisgust\t0\ndedication\tfear\t0\ndedication\tjoy\t0\ndedication\tnegative\t0\ndedication\tpositive\t1\ndedication\tsadness\t0\ndedication\tsurprise\t0\ndedication\ttrust\t0\ndeduce\tanger\t0\ndeduce\tanticipation\t0\ndeduce\tdisgust\t0\ndeduce\tfear\t0\ndeduce\tjoy\t0\ndeduce\tnegative\t0\ndeduce\tpositive\t0\ndeduce\tsadness\t0\ndeduce\tsurprise\t0\ndeduce\ttrust\t0\ndeduct\tanger\t0\ndeduct\tanticipation\t0\ndeduct\tdisgust\t0\ndeduct\tfear\t0\ndeduct\tjoy\t0\ndeduct\tnegative\t1\ndeduct\tpositive\t0\ndeduct\tsadness\t0\ndeduct\tsurprise\t0\ndeduct\ttrust\t0\ndeduction\tanger\t0\ndeduction\tanticipation\t0\ndeduction\tdisgust\t0\ndeduction\tfear\t0\ndeduction\tjoy\t0\ndeduction\tnegative\t0\ndeduction\tpositive\t0\ndeduction\tsadness\t0\ndeduction\tsurprise\t0\ndeduction\ttrust\t0\ndeed\tanger\t0\ndeed\tanticipation\t0\ndeed\tdisgust\t0\ndeed\tfear\t0\ndeed\tjoy\t0\ndeed\tnegative\t0\ndeed\tpositive\t0\ndeed\tsadness\t0\ndeed\tsurprise\t0\ndeed\ttrust\t1\ndeepen\tanger\t0\ndeepen\tanticipation\t0\ndeepen\tdisgust\t0\ndeepen\tfear\t0\ndeepen\tjoy\t0\ndeepen\tnegative\t0\ndeepen\tpositive\t0\ndeepen\tsadness\t0\ndeepen\tsurprise\t0\ndeepen\ttrust\t0\ndeer\tanger\t0\ndeer\tanticipation\t0\ndeer\tdisgust\t0\ndeer\tfear\t0\ndeer\tjoy\t0\ndeer\tnegative\t0\ndeer\tpositive\t0\ndeer\tsadness\t0\ndeer\tsurprise\t0\ndeer\ttrust\t0\ndefamation\tanger\t0\ndefamation\tanticipation\t0\ndefamation\tdisgust\t1\ndefamation\tfear\t1\ndefamation\tjoy\t0\ndefamation\tnegative\t1\ndefamation\tpositive\t0\ndefamation\tsadness\t0\ndefamation\tsurprise\t0\ndefamation\ttrust\t0\ndefamatory\tanger\t1\ndefamatory\tanticipation\t0\ndefamatory\tdisgust\t0\ndefamatory\tfear\t0\ndefamatory\tjoy\t0\ndefamatory\tnegative\t1\ndefamatory\tpositive\t0\ndefamatory\tsadness\t0\ndefamatory\tsurprise\t0\ndefamatory\ttrust\t0\ndefault\tanger\t0\ndefault\tanticipation\t0\ndefault\tdisgust\t1\ndefault\tfear\t1\ndefault\tjoy\t0\ndefault\tnegative\t1\ndefault\tpositive\t0\ndefault\tsadness\t1\ndefault\tsurprise\t0\ndefault\ttrust\t0\ndefeat\tanger\t0\ndefeat\tanticipation\t0\ndefeat\tdisgust\t0\ndefeat\tfear\t0\ndefeat\tjoy\t0\ndefeat\tnegative\t1\ndefeat\tpositive\t0\ndefeat\tsadness\t0\ndefeat\tsurprise\t0\ndefeat\ttrust\t0\ndefeated\tanger\t0\ndefeated\tanticipation\t0\ndefeated\tdisgust\t0\ndefeated\tfear\t0\ndefeated\tjoy\t0\ndefeated\tnegative\t1\ndefeated\tpositive\t0\ndefeated\tsadness\t1\ndefeated\tsurprise\t0\ndefeated\ttrust\t0\ndefect\tanger\t1\ndefect\tanticipation\t0\ndefect\tdisgust\t0\ndefect\tfear\t0\ndefect\tjoy\t0\ndefect\tnegative\t1\ndefect\tpositive\t0\ndefect\tsadness\t0\ndefect\tsurprise\t0\ndefect\ttrust\t0\ndefection\tanger\t0\ndefection\tanticipation\t0\ndefection\tdisgust\t0\ndefection\tfear\t1\ndefection\tjoy\t0\ndefection\tnegative\t1\ndefection\tpositive\t0\ndefection\tsadness\t0\ndefection\tsurprise\t0\ndefection\ttrust\t0\ndefective\tanger\t0\ndefective\tanticipation\t0\ndefective\tdisgust\t1\ndefective\tfear\t0\ndefective\tjoy\t0\ndefective\tnegative\t1\ndefective\tpositive\t0\ndefective\tsadness\t0\ndefective\tsurprise\t0\ndefective\ttrust\t0\ndefend\tanger\t0\ndefend\tanticipation\t0\ndefend\tdisgust\t0\ndefend\tfear\t1\ndefend\tjoy\t0\ndefend\tnegative\t0\ndefend\tpositive\t1\ndefend\tsadness\t0\ndefend\tsurprise\t0\ndefend\ttrust\t0\ndefendant\tanger\t1\ndefendant\tanticipation\t0\ndefendant\tdisgust\t0\ndefendant\tfear\t1\ndefendant\tjoy\t0\ndefendant\tnegative\t0\ndefendant\tpositive\t0\ndefendant\tsadness\t1\ndefendant\tsurprise\t0\ndefendant\ttrust\t0\ndefended\tanger\t0\ndefended\tanticipation\t0\ndefended\tdisgust\t0\ndefended\tfear\t0\ndefended\tjoy\t0\ndefended\tnegative\t0\ndefended\tpositive\t1\ndefended\tsadness\t0\ndefended\tsurprise\t0\ndefended\ttrust\t1\ndefender\tanger\t0\ndefender\tanticipation\t0\ndefender\tdisgust\t0\ndefender\tfear\t0\ndefender\tjoy\t0\ndefender\tnegative\t0\ndefender\tpositive\t1\ndefender\tsadness\t0\ndefender\tsurprise\t0\ndefender\ttrust\t1\ndefending\tanger\t0\ndefending\tanticipation\t0\ndefending\tdisgust\t0\ndefending\tfear\t0\ndefending\tjoy\t0\ndefending\tnegative\t0\ndefending\tpositive\t1\ndefending\tsadness\t0\ndefending\tsurprise\t0\ndefending\ttrust\t0\ndefense\tanger\t1\ndefense\tanticipation\t1\ndefense\tdisgust\t0\ndefense\tfear\t1\ndefense\tjoy\t0\ndefense\tnegative\t0\ndefense\tpositive\t1\ndefense\tsadness\t0\ndefense\tsurprise\t0\ndefense\ttrust\t0\ndefenseless\tanger\t0\ndefenseless\tanticipation\t0\ndefenseless\tdisgust\t0\ndefenseless\tfear\t1\ndefenseless\tjoy\t0\ndefenseless\tnegative\t1\ndefenseless\tpositive\t0\ndefenseless\tsadness\t1\ndefenseless\tsurprise\t0\ndefenseless\ttrust\t0\ndefensible\tanger\t0\ndefensible\tanticipation\t0\ndefensible\tdisgust\t0\ndefensible\tfear\t0\ndefensible\tjoy\t0\ndefensible\tnegative\t0\ndefensible\tpositive\t0\ndefensible\tsadness\t0\ndefensible\tsurprise\t0\ndefensible\ttrust\t0\ndefensive\tanger\t0\ndefensive\tanticipation\t0\ndefensive\tdisgust\t0\ndefensive\tfear\t0\ndefensive\tjoy\t0\ndefensive\tnegative\t0\ndefensive\tpositive\t0\ndefensive\tsadness\t0\ndefensive\tsurprise\t0\ndefensive\ttrust\t0\ndefer\tanger\t0\ndefer\tanticipation\t0\ndefer\tdisgust\t0\ndefer\tfear\t0\ndefer\tjoy\t0\ndefer\tnegative\t0\ndefer\tpositive\t0\ndefer\tsadness\t0\ndefer\tsurprise\t0\ndefer\ttrust\t0\ndeference\tanger\t0\ndeference\tanticipation\t0\ndeference\tdisgust\t0\ndeference\tfear\t0\ndeference\tjoy\t0\ndeference\tnegative\t0\ndeference\tpositive\t1\ndeference\tsadness\t0\ndeference\tsurprise\t0\ndeference\ttrust\t1\ndeferral\tanger\t0\ndeferral\tanticipation\t0\ndeferral\tdisgust\t0\ndeferral\tfear\t0\ndeferral\tjoy\t0\ndeferral\tnegative\t1\ndeferral\tpositive\t0\ndeferral\tsadness\t0\ndeferral\tsurprise\t0\ndeferral\ttrust\t0\ndeferring\tanger\t0\ndeferring\tanticipation\t0\ndeferring\tdisgust\t0\ndeferring\tfear\t0\ndeferring\tjoy\t0\ndeferring\tnegative\t0\ndeferring\tpositive\t0\ndeferring\tsadness\t0\ndeferring\tsurprise\t0\ndeferring\ttrust\t0\ndefiance\tanger\t1\ndefiance\tanticipation\t0\ndefiance\tdisgust\t1\ndefiance\tfear\t1\ndefiance\tjoy\t0\ndefiance\tnegative\t1\ndefiance\tpositive\t0\ndefiance\tsadness\t0\ndefiance\tsurprise\t0\ndefiance\ttrust\t0\ndefiant\tanger\t1\ndefiant\tanticipation\t0\ndefiant\tdisgust\t0\ndefiant\tfear\t0\ndefiant\tjoy\t0\ndefiant\tnegative\t1\ndefiant\tpositive\t0\ndefiant\tsadness\t0\ndefiant\tsurprise\t0\ndefiant\ttrust\t0\ndeficiency\tanger\t0\ndeficiency\tanticipation\t0\ndeficiency\tdisgust\t0\ndeficiency\tfear\t0\ndeficiency\tjoy\t0\ndeficiency\tnegative\t1\ndeficiency\tpositive\t0\ndeficiency\tsadness\t0\ndeficiency\tsurprise\t0\ndeficiency\ttrust\t0\ndeficit\tanger\t0\ndeficit\tanticipation\t0\ndeficit\tdisgust\t0\ndeficit\tfear\t0\ndeficit\tjoy\t0\ndeficit\tnegative\t1\ndeficit\tpositive\t0\ndeficit\tsadness\t0\ndeficit\tsurprise\t0\ndeficit\ttrust\t0\ndefine\tanger\t0\ndefine\tanticipation\t0\ndefine\tdisgust\t0\ndefine\tfear\t0\ndefine\tjoy\t0\ndefine\tnegative\t0\ndefine\tpositive\t0\ndefine\tsadness\t0\ndefine\tsurprise\t0\ndefine\ttrust\t0\ndefined\tanger\t0\ndefined\tanticipation\t0\ndefined\tdisgust\t0\ndefined\tfear\t0\ndefined\tjoy\t0\ndefined\tnegative\t0\ndefined\tpositive\t0\ndefined\tsadness\t0\ndefined\tsurprise\t0\ndefined\ttrust\t0\ndefinition\tanger\t0\ndefinition\tanticipation\t0\ndefinition\tdisgust\t0\ndefinition\tfear\t0\ndefinition\tjoy\t0\ndefinition\tnegative\t0\ndefinition\tpositive\t0\ndefinition\tsadness\t0\ndefinition\tsurprise\t0\ndefinition\ttrust\t0\ndefinitive\tanger\t0\ndefinitive\tanticipation\t0\ndefinitive\tdisgust\t0\ndefinitive\tfear\t0\ndefinitive\tjoy\t0\ndefinitive\tnegative\t0\ndefinitive\tpositive\t1\ndefinitive\tsadness\t0\ndefinitive\tsurprise\t0\ndefinitive\ttrust\t1\ndeflate\tanger\t1\ndeflate\tanticipation\t0\ndeflate\tdisgust\t0\ndeflate\tfear\t0\ndeflate\tjoy\t0\ndeflate\tnegative\t1\ndeflate\tpositive\t0\ndeflate\tsadness\t1\ndeflate\tsurprise\t0\ndeflate\ttrust\t0\ndeflation\tanger\t0\ndeflation\tanticipation\t0\ndeflation\tdisgust\t0\ndeflation\tfear\t1\ndeflation\tjoy\t0\ndeflation\tnegative\t1\ndeflation\tpositive\t0\ndeflation\tsadness\t0\ndeflation\tsurprise\t0\ndeflation\ttrust\t0\ndeflect\tanger\t0\ndeflect\tanticipation\t0\ndeflect\tdisgust\t0\ndeflect\tfear\t0\ndeflect\tjoy\t0\ndeflect\tnegative\t0\ndeflect\tpositive\t0\ndeflect\tsadness\t0\ndeflect\tsurprise\t0\ndeflect\ttrust\t0\ndeflection\tanger\t0\ndeflection\tanticipation\t0\ndeflection\tdisgust\t0\ndeflection\tfear\t0\ndeflection\tjoy\t0\ndeflection\tnegative\t0\ndeflection\tpositive\t0\ndeflection\tsadness\t0\ndeflection\tsurprise\t0\ndeflection\ttrust\t0\ndefloration\tanger\t0\ndefloration\tanticipation\t0\ndefloration\tdisgust\t0\ndefloration\tfear\t0\ndefloration\tjoy\t0\ndefloration\tnegative\t0\ndefloration\tpositive\t0\ndefloration\tsadness\t0\ndefloration\tsurprise\t0\ndefloration\ttrust\t0\ndeform\tanger\t0\ndeform\tanticipation\t0\ndeform\tdisgust\t1\ndeform\tfear\t0\ndeform\tjoy\t0\ndeform\tnegative\t1\ndeform\tpositive\t0\ndeform\tsadness\t0\ndeform\tsurprise\t0\ndeform\ttrust\t0\ndeformed\tanger\t0\ndeformed\tanticipation\t0\ndeformed\tdisgust\t1\ndeformed\tfear\t0\ndeformed\tjoy\t0\ndeformed\tnegative\t1\ndeformed\tpositive\t0\ndeformed\tsadness\t1\ndeformed\tsurprise\t0\ndeformed\ttrust\t0\ndeformity\tanger\t0\ndeformity\tanticipation\t0\ndeformity\tdisgust\t1\ndeformity\tfear\t1\ndeformity\tjoy\t0\ndeformity\tnegative\t1\ndeformity\tpositive\t0\ndeformity\tsadness\t1\ndeformity\tsurprise\t0\ndeformity\ttrust\t0\ndefraud\tanger\t1\ndefraud\tanticipation\t0\ndefraud\tdisgust\t1\ndefraud\tfear\t0\ndefraud\tjoy\t0\ndefraud\tnegative\t1\ndefraud\tpositive\t0\ndefraud\tsadness\t0\ndefraud\tsurprise\t0\ndefraud\ttrust\t0\ndefray\tanger\t0\ndefray\tanticipation\t0\ndefray\tdisgust\t0\ndefray\tfear\t0\ndefray\tjoy\t0\ndefray\tnegative\t0\ndefray\tpositive\t0\ndefray\tsadness\t0\ndefray\tsurprise\t0\ndefray\ttrust\t0\ndeft\tanger\t0\ndeft\tanticipation\t0\ndeft\tdisgust\t0\ndeft\tfear\t0\ndeft\tjoy\t0\ndeft\tnegative\t0\ndeft\tpositive\t0\ndeft\tsadness\t0\ndeft\tsurprise\t0\ndeft\ttrust\t0\ndefunct\tanger\t0\ndefunct\tanticipation\t0\ndefunct\tdisgust\t0\ndefunct\tfear\t0\ndefunct\tjoy\t0\ndefunct\tnegative\t1\ndefunct\tpositive\t0\ndefunct\tsadness\t1\ndefunct\tsurprise\t0\ndefunct\ttrust\t0\ndefy\tanger\t1\ndefy\tanticipation\t0\ndefy\tdisgust\t0\ndefy\tfear\t1\ndefy\tjoy\t0\ndefy\tnegative\t1\ndefy\tpositive\t0\ndefy\tsadness\t1\ndefy\tsurprise\t1\ndefy\ttrust\t0\ndegeneracy\tanger\t1\ndegeneracy\tanticipation\t0\ndegeneracy\tdisgust\t1\ndegeneracy\tfear\t0\ndegeneracy\tjoy\t0\ndegeneracy\tnegative\t1\ndegeneracy\tpositive\t0\ndegeneracy\tsadness\t1\ndegeneracy\tsurprise\t0\ndegeneracy\ttrust\t0\ndegenerate\tanger\t0\ndegenerate\tanticipation\t0\ndegenerate\tdisgust\t0\ndegenerate\tfear\t0\ndegenerate\tjoy\t0\ndegenerate\tnegative\t1\ndegenerate\tpositive\t0\ndegenerate\tsadness\t0\ndegenerate\tsurprise\t0\ndegenerate\ttrust\t0\ndegeneration\tanger\t0\ndegeneration\tanticipation\t0\ndegeneration\tdisgust\t0\ndegeneration\tfear\t0\ndegeneration\tjoy\t0\ndegeneration\tnegative\t0\ndegeneration\tpositive\t0\ndegeneration\tsadness\t0\ndegeneration\tsurprise\t0\ndegeneration\ttrust\t0\ndegradation\tanger\t0\ndegradation\tanticipation\t0\ndegradation\tdisgust\t0\ndegradation\tfear\t0\ndegradation\tjoy\t0\ndegradation\tnegative\t1\ndegradation\tpositive\t0\ndegradation\tsadness\t0\ndegradation\tsurprise\t0\ndegradation\ttrust\t0\ndegrade\tanger\t0\ndegrade\tanticipation\t0\ndegrade\tdisgust\t1\ndegrade\tfear\t0\ndegrade\tjoy\t0\ndegrade\tnegative\t1\ndegrade\tpositive\t0\ndegrade\tsadness\t0\ndegrade\tsurprise\t0\ndegrade\ttrust\t0\ndegrading\tanger\t0\ndegrading\tanticipation\t0\ndegrading\tdisgust\t1\ndegrading\tfear\t1\ndegrading\tjoy\t0\ndegrading\tnegative\t1\ndegrading\tpositive\t0\ndegrading\tsadness\t1\ndegrading\tsurprise\t0\ndegrading\ttrust\t0\ndegree\tanger\t0\ndegree\tanticipation\t0\ndegree\tdisgust\t0\ndegree\tfear\t0\ndegree\tjoy\t0\ndegree\tnegative\t0\ndegree\tpositive\t1\ndegree\tsadness\t0\ndegree\tsurprise\t0\ndegree\ttrust\t0\ndehydrated\tanger\t0\ndehydrated\tanticipation\t0\ndehydrated\tdisgust\t0\ndehydrated\tfear\t0\ndehydrated\tjoy\t0\ndehydrated\tnegative\t0\ndehydrated\tpositive\t0\ndehydrated\tsadness\t0\ndehydrated\tsurprise\t0\ndehydrated\ttrust\t0\ndelay\tanger\t1\ndelay\tanticipation\t0\ndelay\tdisgust\t1\ndelay\tfear\t1\ndelay\tjoy\t0\ndelay\tnegative\t1\ndelay\tpositive\t0\ndelay\tsadness\t1\ndelay\tsurprise\t0\ndelay\ttrust\t0\ndelayed\tanger\t0\ndelayed\tanticipation\t0\ndelayed\tdisgust\t0\ndelayed\tfear\t0\ndelayed\tjoy\t0\ndelayed\tnegative\t1\ndelayed\tpositive\t0\ndelayed\tsadness\t0\ndelayed\tsurprise\t0\ndelayed\ttrust\t0\ndelectable\tanger\t0\ndelectable\tanticipation\t0\ndelectable\tdisgust\t0\ndelectable\tfear\t0\ndelectable\tjoy\t0\ndelectable\tnegative\t0\ndelectable\tpositive\t1\ndelectable\tsadness\t0\ndelectable\tsurprise\t0\ndelectable\ttrust\t0\ndelegate\tanger\t0\ndelegate\tanticipation\t0\ndelegate\tdisgust\t0\ndelegate\tfear\t0\ndelegate\tjoy\t0\ndelegate\tnegative\t0\ndelegate\tpositive\t1\ndelegate\tsadness\t0\ndelegate\tsurprise\t0\ndelegate\ttrust\t1\ndelegation\tanger\t0\ndelegation\tanticipation\t0\ndelegation\tdisgust\t0\ndelegation\tfear\t0\ndelegation\tjoy\t0\ndelegation\tnegative\t0\ndelegation\tpositive\t0\ndelegation\tsadness\t0\ndelegation\tsurprise\t0\ndelegation\ttrust\t0\ndeleterious\tanger\t1\ndeleterious\tanticipation\t0\ndeleterious\tdisgust\t1\ndeleterious\tfear\t1\ndeleterious\tjoy\t0\ndeleterious\tnegative\t1\ndeleterious\tpositive\t0\ndeleterious\tsadness\t0\ndeleterious\tsurprise\t0\ndeleterious\ttrust\t0\ndeletion\tanger\t0\ndeletion\tanticipation\t0\ndeletion\tdisgust\t0\ndeletion\tfear\t0\ndeletion\tjoy\t0\ndeletion\tnegative\t1\ndeletion\tpositive\t0\ndeletion\tsadness\t0\ndeletion\tsurprise\t0\ndeletion\ttrust\t0\ndeliberate\tanger\t0\ndeliberate\tanticipation\t0\ndeliberate\tdisgust\t0\ndeliberate\tfear\t0\ndeliberate\tjoy\t0\ndeliberate\tnegative\t0\ndeliberate\tpositive\t1\ndeliberate\tsadness\t0\ndeliberate\tsurprise\t0\ndeliberate\ttrust\t0\ndeliberation\tanger\t0\ndeliberation\tanticipation\t0\ndeliberation\tdisgust\t0\ndeliberation\tfear\t0\ndeliberation\tjoy\t0\ndeliberation\tnegative\t0\ndeliberation\tpositive\t0\ndeliberation\tsadness\t0\ndeliberation\tsurprise\t0\ndeliberation\ttrust\t0\ndeliberative\tanger\t0\ndeliberative\tanticipation\t0\ndeliberative\tdisgust\t0\ndeliberative\tfear\t0\ndeliberative\tjoy\t0\ndeliberative\tnegative\t0\ndeliberative\tpositive\t0\ndeliberative\tsadness\t0\ndeliberative\tsurprise\t0\ndeliberative\ttrust\t0\ndelicacy\tanger\t0\ndelicacy\tanticipation\t0\ndelicacy\tdisgust\t0\ndelicacy\tfear\t0\ndelicacy\tjoy\t0\ndelicacy\tnegative\t0\ndelicacy\tpositive\t0\ndelicacy\tsadness\t0\ndelicacy\tsurprise\t0\ndelicacy\ttrust\t0\ndelicious\tanger\t0\ndelicious\tanticipation\t0\ndelicious\tdisgust\t0\ndelicious\tfear\t0\ndelicious\tjoy\t1\ndelicious\tnegative\t0\ndelicious\tpositive\t1\ndelicious\tsadness\t0\ndelicious\tsurprise\t0\ndelicious\ttrust\t0\ndelight\tanger\t0\ndelight\tanticipation\t1\ndelight\tdisgust\t0\ndelight\tfear\t0\ndelight\tjoy\t1\ndelight\tnegative\t0\ndelight\tpositive\t1\ndelight\tsadness\t0\ndelight\tsurprise\t0\ndelight\ttrust\t0\ndelighted\tanger\t0\ndelighted\tanticipation\t1\ndelighted\tdisgust\t0\ndelighted\tfear\t0\ndelighted\tjoy\t1\ndelighted\tnegative\t0\ndelighted\tpositive\t1\ndelighted\tsadness\t0\ndelighted\tsurprise\t1\ndelighted\ttrust\t0\ndelightful\tanger\t0\ndelightful\tanticipation\t1\ndelightful\tdisgust\t0\ndelightful\tfear\t0\ndelightful\tjoy\t1\ndelightful\tnegative\t0\ndelightful\tpositive\t1\ndelightful\tsadness\t0\ndelightful\tsurprise\t0\ndelightful\ttrust\t1\ndelineate\tanger\t0\ndelineate\tanticipation\t0\ndelineate\tdisgust\t0\ndelineate\tfear\t0\ndelineate\tjoy\t0\ndelineate\tnegative\t0\ndelineate\tpositive\t0\ndelineate\tsadness\t0\ndelineate\tsurprise\t0\ndelineate\ttrust\t0\ndelineation\tanger\t0\ndelineation\tanticipation\t0\ndelineation\tdisgust\t0\ndelineation\tfear\t0\ndelineation\tjoy\t0\ndelineation\tnegative\t0\ndelineation\tpositive\t0\ndelineation\tsadness\t0\ndelineation\tsurprise\t0\ndelineation\ttrust\t0\ndelinquency\tanger\t0\ndelinquency\tanticipation\t0\ndelinquency\tdisgust\t0\ndelinquency\tfear\t0\ndelinquency\tjoy\t0\ndelinquency\tnegative\t1\ndelinquency\tpositive\t0\ndelinquency\tsadness\t0\ndelinquency\tsurprise\t0\ndelinquency\ttrust\t0\ndelinquent\tanger\t1\ndelinquent\tanticipation\t0\ndeli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ivine\tanger\t0\ndivine\tanticipation\t0\ndivine\tdisgust\t0\ndivine\tfear\t0\ndivine\tjoy\t0\ndivine\tnegative\t0\ndivine\tpositive\t0\ndivine\tsadness\t0\ndivine\tsurprise\t0\ndivine\ttrust\t0\ndivinity\tanger\t0\ndivinity\tanticipation\t0\ndivinity\tdisgust\t0\ndivinity\tfear\t0\ndivinity\tjoy\t0\ndivinity\tnegative\t0\ndivinity\tpositive\t1\ndivinity\tsadness\t0\ndivinity\tsurprise\t0\ndivinity\ttrust\t0\ndivisible\tanger\t0\ndivisible\tanticipation\t0\ndivisible\tdisgust\t0\ndivisible\tfear\t0\ndivisible\tjoy\t0\ndivisible\tnegative\t0\ndivisible\tpositive\t0\ndivisible\tsadness\t0\ndivisible\tsurprise\t0\ndivisible\ttrust\t0\ndivision\tanger\t0\ndivision\tanticipation\t0\ndivision\tdisgust\t0\ndivision\tfear\t0\ndivision\tjoy\t0\ndivision\tnegative\t0\ndivision\tpositive\t0\ndivision\tsadness\t0\ndivision\tsurprise\t0\ndivision\ttrust\t0\ndivisor\tanger\t0\ndivisor\tanticipation\t0\ndivisor\tdisgust\t0\ndivisor\tfear\t0\ndivisor\tjoy\t0\ndivisor\tnegative\t0\ndivisor\tpositive\t0\ndivisor\tsadness\t0\ndivisor\tsurprise\t0\ndivisor\ttrust\t0\ndivorce\tanger\t1\ndivorce\tanticipation\t0\ndivorce\tdisgust\t1\ndivorce\tfear\t1\ndivorce\tjoy\t0\ndivorce\tnegative\t1\ndivorce\tpositive\t0\ndivorce\tsadness\t1\ndivorce\tsurprise\t1\ndivorce\ttrust\t1\ndivulge\tanger\t0\ndivulge\tanticipation\t0\ndivulge\tdisgust\t0\ndivulge\tfear\t0\ndivulge\tjoy\t0\ndivulge\tnegative\t0\ndivulge\tpositive\t0\ndivulge\tsadness\t0\ndivulge\tsurprise\t0\ndivulge\ttrust\t0\ndizziness\tanger\t0\ndizziness\tanticipation\t0\ndizziness\tdisgust\t0\ndizziness\tfear\t0\ndizziness\tjoy\t0\ndizziness\tnegative\t1\ndizziness\tpositive\t0\ndizziness\tsadness\t0\ndizziness\tsurprise\t0\ndizziness\ttrust\t0\ndizzy\tanger\t0\ndizzy\tanticipation\t0\ndizzy\tdisgust\t0\ndizzy\tfear\t0\ndizzy\tjoy\t0\ndizzy\tnegative\t1\ndizzy\tpositive\t0\ndizzy\tsadness\t0\ndizzy\tsurprise\t0\ndizzy\ttrust\t0\ndocile\tanger\t0\ndocile\tanticipation\t0\ndocile\tdisgust\t0\ndocile\tfear\t0\ndocile\tjoy\t0\ndocile\tnegative\t0\ndocile\tpositive\t0\ndocile\tsadness\t0\ndocile\tsurprise\t0\ndocile\ttrust\t0\ndock\tanger\t0\ndock\tanticipation\t0\ndock\tdisgust\t0\ndock\tfear\t0\ndock\tjoy\t0\ndock\tnegative\t0\ndock\tpositive\t0\ndock\tsadness\t0\ndock\tsurprise\t0\ndock\ttrust\t0\ndocked\tanger\t0\ndocked\tanticipation\t0\ndocked\tdisgust\t0\ndocked\tfear\t0\ndocked\tjoy\t0\ndocked\tnegative\t1\ndocked\tpositive\t0\ndocked\tsadness\t0\ndocked\tsurprise\t0\ndocked\ttrust\t0\ndocket\tanger\t0\ndocket\tanticipation\t0\ndocket\tdisgust\t0\ndocket\tfear\t0\ndocket\tjoy\t0\ndocket\tnegative\t0\ndocket\tpositive\t0\ndocket\tsadness\t0\ndocket\tsurprise\t0\ndocket\ttrust\t0\ndoctor\tanger\t0\ndoctor\tanticipation\t0\ndoctor\tdisgust\t0\ndoctor\tfear\t0\ndoctor\tjoy\t0\ndoctor\tnegative\t0\ndoctor\tpositive\t1\ndoctor\tsadness\t0\ndoctor\tsurprise\t0\ndoctor\ttrust\t1\ndoctrinal\tanger\t0\ndoctrinal\tanticipation\t0\ndoctrinal\tdisgust\t0\ndoctrinal\tfear\t0\ndoctrinal\tjoy\t0\ndoctrinal\tnegative\t0\ndoctrinal\tpositive\t0\ndoctrinal\tsadness\t0\ndoctrinal\tsurprise\t0\ndoctrinal\ttrust\t0\ndoctrine\tanger\t0\ndoctrine\tanticipation\t0\ndoctrine\tdisgust\t0\ndoctrine\tfear\t0\ndoctrine\tjoy\t0\ndoctrine\tnegative\t0\ndoctrine\tpositive\t0\ndoctrine\tsadness\t0\ndoctrine\tsurprise\t0\ndoctrine\ttrust\t1\ndocument\tanger\t0\ndocument\tanticipation\t0\ndocument\tdisgust\t0\ndocument\tfear\t0\ndocument\tjoy\t0\ndocument\tnegative\t0\ndocument\tpositive\t0\ndocument\tsadness\t0\ndocument\tsurprise\t0\ndocument\ttrust\t0\ndocumentary\tanger\t0\ndocumentary\tanticipation\t0\ndocumentary\tdisgust\t0\ndocumentary\tfear\t0\ndocumentary\tjoy\t0\ndocumentary\tnegative\t0\ndocumentary\tpositive\t0\ndocumentary\tsadness\t0\ndocumentary\tsurprise\t0\ndocumentary\ttrust\t0\ndodge\tanger\t0\ndodge\tanticipation\t0\ndodge\tdisgust\t0\ndodge\tfear\t0\ndodge\tjoy\t0\ndodge\tnegative\t0\ndodge\tpositive\t0\ndodge\tsadness\t0\ndodge\tsurprise\t0\ndodge\ttrust\t0\ndodging\tanger\t0\ndodging\tanticipation\t0\ndodging\tdisgust\t0\ndodging\tfear\t0\ndodging\tjoy\t0\ndodging\tnegative\t0\ndodging\tpositive\t0\ndodging\tsadness\t0\ndodging\tsurprise\t0\ndodging\ttrust\t0\ndoe\tanger\t0\ndoe\tanticipation\t0\ndoe\tdisgust\t0\ndoe\tfear\t0\ndoe\tjoy\t0\ndoe\tnegative\t0\ndoe\tpositive\t0\ndoe\tsadness\t0\ndoe\tsurprise\t0\ndoe\ttrust\t0\ndoer\tanger\t0\ndoer\tanticipation\t0\ndoer\tdisgust\t0\ndoer\tfear\t0\ndoer\tjoy\t0\ndoer\tnegative\t0\ndoer\tpositive\t1\ndoer\tsadness\t0\ndoer\tsurprise\t0\ndoer\ttrust\t0\ndog\tanger\t0\ndog\tanticipation\t0\ndog\tdisgust\t0\ndog\tfear\t0\ndog\tjoy\t0\ndog\tnegative\t0\ndog\tpositive\t0\ndog\tsadness\t0\ndog\tsurprise\t0\ndog\ttrust\t0\ndogged\tanger\t0\ndogged\tanticipation\t0\ndogged\tdisgust\t0\ndogged\tfear\t0\ndogged\tjoy\t0\ndogged\tnegative\t0\ndogged\tpositive\t1\ndogged\tsadness\t0\ndogged\tsurprise\t0\ndogged\ttrust\t0\ndogma\tanger\t0\ndogma\tanticipation\t0\ndogma\tdisgust\t0\ndogma\tfear\t0\ndogma\tjoy\t0\ndogma\tnegative\t0\ndogma\tpositive\t0\ndo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abric\tanticipation\t0\nfabric\tdisgust\t0\nfabric\tfear\t0\nfabric\tjoy\t0\nfabric\tnegative\t0\nfabric\tpositive\t0\nfabric\tsadness\t0\nfabric\tsurprise\t0\nfabric\ttrust\t0\nfabricate\tanger\t0\nfabricate\tanticipation\t0\nfabricate\tdisgust\t0\nfabricate\tfear\t0\nfabricate\tjoy\t0\nfabricate\tnegative\t1\nfabricate\tpositive\t0\nfabricate\tsadness\t0\nfabricate\tsurprise\t0\nfabricate\ttrust\t0\nfabricated\tanger\t0\nfabricated\tanticipation\t0\nfabricated\tdisgust\t0\nfabricated\tfear\t0\nfabricated\tjoy\t0\nfabricated\tnegative\t0\nfabricated\tpositive\t0\nfabricated\tsadness\t0\nfabricated\tsurprise\t0\nfabricated\ttrust\t0\nfabrication\tanger\t0\nfabrication\tanticipation\t0\nfabrication\tdisgust\t0\nfabrication\tfear\t0\nfabrication\tjoy\t0\nfabrication\tnegative\t1\nfabrication\tpositive\t0\nfabrication\tsadness\t0\nfabrication\tsurprise\t0\nfabrication\ttrust\t1\nfacade\tanger\t0\nfacade\tanticipation\t0\nfacade\tdisgust\t0\nfacade\tfear\t0\nfacade\tjoy\t0\nfacade\tnegative\t0\nfacade\tpositive\t0\nfacade\tsadness\t0\nfacade\tsurprise\t0\nfacade\ttrust\t0\nface\tanger\t0\nface\tanticipation\t0\nface\tdisgust\t0\nface\tfear\t0\nface\tjoy\t0\nface\tnegative\t0\nface\tpositive\t0\nface\tsadness\t0\nface\tsurprise\t0\nface\ttrust\t0\nfacet\tanger\t0\nfacet\tanticipation\t0\nfacet\tdisgust\t0\nfacet\tfear\t0\nfacet\tjoy\t0\nfacet\tnegative\t0\nfacet\tpositive\t0\nfacet\tsadness\t0\nfacet\tsurprise\t0\nfacet\ttrust\t0\nfacile\tanger\t0\nfacile\tanticipation\t0\nfacile\tdisgust\t0\nfacile\tfear\t0\nfacile\tjoy\t0\nfacile\tnegative\t0\nfacile\tpositive\t0\nfacile\tsadness\t0\nfacile\tsurprise\t0\nfacile\ttrust\t0\nfacilitate\tanger\t0\nfacilitate\tanticipation\t0\nfacilitate\tdisgust\t0\nfacilitate\tfear\t0\nfacilitate\tjoy\t0\nfacilitate\tnegative\t0\nfacilitate\tpositive\t1\nfacilitate\tsadness\t0\nfacilitate\tsurprise\t0\nfacilitate\ttrust\t0\nfacility\tanger\t0\nfacility\tanticipation\t0\nfacility\tdisgust\t0\nfacility\tfear\t0\nfacility\tjoy\t0\nfacility\tnegative\t0\nfacility\tpositive\t0\nfacility\tsadness\t0\nfacility\tsurprise\t0\nfacility\ttrust\t0\nfacing\tanger\t0\nfacing\tanticipation\t0\nfacing\tdisgust\t0\nfacing\tfear\t0\nfacing\tjoy\t0\nfacing\tnegative\t0\nfacing\tpositive\t0\nfacing\tsadness\t0\nfacing\tsurprise\t0\nfacing\ttrust\t0\nfacsimile\tanger\t0\nfacsimile\tanticipation\t0\nfacsimile\tdisgust\t0\nfacsimile\tfear\t0\nfacsimile\tjoy\t0\nfacsimile\tnegative\t0\nfacsimile\tpositive\t0\nfacsimile\tsadness\t0\nfacsimile\tsurprise\t0\nfacsimile\ttrust\t0\nfact\tanger\t0\nfact\tanticipation\t0\nfact\tdisgust\t0\nfact\tfear\t0\nfact\tjoy\t0\nfact\tnegative\t0\nfact\tpositive\t0\nfact\tsadness\t0\nfact\tsurprise\t0\nfact\ttrust\t1\nfaction\tanger\t0\nfaction\tanticipation\t0\nfaction\tdisgust\t0\nfaction\tfear\t0\nfaction\tjoy\t0\nfaction\tnegative\t0\nfaction\tpositive\t0\nfaction\tsadness\t0\nfaction\tsurprise\t0\nfaction\ttrust\t0\nfactor\tanger\t0\nfactor\tanticipation\t0\nfactor\tdisgust\t0\nfactor\tfear\t0\nfactor\tjoy\t0\nfactor\tnegative\t0\nfactor\tpositive\t0\nfactor\tsadness\t0\nfactor\tsurprise\t0\nfactor\ttrust\t0\nfactory\tanger\t0\nfactory\tanticipation\t0\nfactory\tdisgust\t0\nfactory\tfear\t0\nfactory\tjoy\t0\nfactory\tnegative\t0\nfactory\tpositive\t0\nfactory\tsadness\t0\nfactory\tsurprise\t0\nfactory\ttrust\t0\nfacts\tanger\t0\nfacts\tanticipation\t0\nfacts\tdisgust\t0\nfacts\tfear\t0\nfacts\tjoy\t0\nfacts\tnegative\t0\nfacts\tpositive\t1\nfacts\tsadness\t0\nfacts\tsurprise\t0\nfacts\ttrust\t1\nfaculties\tanger\t0\nfaculties\tanticipation\t0\nfaculties\tdisgust\t0\nfaculties\tfear\t0\nfaculties\tjoy\t0\nfaculties\tnegative\t0\nfaculties\tpositive\t0\nfaculties\tsadness\t0\nfaculties\tsurprise\t0\nfaculties\ttrust\t0\nfaculty\tanger\t0\nfaculty\tanticipation\t0\nfaculty\tdisgust\t0\nfaculty\tfear\t0\nfaculty\tjoy\t0\nfaculty\tnegative\t0\nfaculty\tpositive\t1\nfaculty\tsadness\t0\nfaculty\tsurprise\t0\nfaculty\ttrust\t1\nfad\tanger\t0\nfad\tanticipation\t0\nfad\tdisgust\t0\nfad\tfear\t0\nfad\tjoy\t0\nfad\tnegative\t0\nfad\tpositive\t0\nfad\tsadness\t0\nfad\tsurprise\t0\nfad\ttrust\t0\nfade\tanger\t0\nfade\tanticipation\t0\nfade\tdisgust\t0\nfade\tfear\t0\nfade\tjoy\t0\nfade\tnegative\t1\nfade\tpositive\t0\nfade\tsadness\t0\nfade\tsurprise\t0\nfade\ttrust\t0\nfaded\tanger\t0\nfaded\tanticipation\t0\nfaded\tdisgust\t0\nfaded\tfear\t0\nfaded\tjoy\t0\nfaded\tnegative\t0\nfaded\tpositive\t0\nfaded\tsadness\t0\nfaded\tsurprise\t0\nfaded\ttrust\t0\nfaeces\tanger\t0\nfaeces\tanticipation\t0\nfaeces\tdisgust\t1\nfaeces\tfear\t0\nfaeces\tjoy\t0\nfaeces\tnegative\t1\nfaeces\tpositive\t0\nfaeces\tsadness\t0\nfaeces\tsurprise\t0\nfaeces\ttrust\t0\nfailing\tanger\t1\nfailing\tanticipation\t1\nfailing\tdisgust\t0\nfailing\tfear\t1\nfailing\tjoy\t0\nfailing\tnegative\t1\nfailing\tpositive\t0\nfailing\tsadness\t1\nfailing\tsurprise\t0\nfailing\ttrust\t0\nfailure\tanger\t0\nfailure\tanticipation\t0\nfailure\tdisgust\t1\nfailure\tfear\t1\nfailure\tjoy\t0\nfailure\tnegative\t1\nfailure\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ust\t0\nfoiled\tanger\t0\nfoiled\tanticipation\t0\nfoiled\tdisgust\t0\nfoiled\tfear\t0\nfoiled\tjoy\t0\nfoiled\tnegative\t1\nfoiled\tpositive\t0\nfoiled\tsadness\t0\nfoiled\tsurprise\t0\nfoiled\ttrust\t0\nfold\tanger\t0\nfold\tanticipation\t0\nfold\tdisgust\t0\nfold\tfear\t0\nfold\tjoy\t0\nfold\tnegative\t0\nfold\tpositive\t0\nfold\tsadness\t0\nfold\tsurprise\t0\nfold\ttrust\t0\nfolded\tanger\t0\nfolded\tanticipation\t0\nfolded\tdisgust\t0\nfolded\tfear\t0\nfolded\tjoy\t0\nfolded\tnegative\t0\nfolded\tpositive\t0\nfolded\tsadness\t0\nfolded\tsurprise\t0\nfolded\ttrust\t0\nfoliage\tanger\t0\nfoliage\tanticipation\t0\nfoliage\tdisgust\t0\nfoliage\tfear\t0\nfoliage\tjoy\t0\nfoliage\tnegative\t0\nfoliage\tpositive\t0\nfoliage\tsadness\t0\nfoliage\tsurprise\t0\nfoliage\ttrust\t0\nfolio\tanger\t0\nfolio\tanticipation\t0\nfolio\tdisgust\t0\nfolio\tfear\t0\nfolio\tjoy\t0\nfolio\tnegative\t0\nfolio\tpositive\t0\nfolio\tsadness\t0\nfolio\tsurprise\t0\nfolio\ttrust\t0\nfolk\tanger\t0\nfolk\tanticipation\t0\nfolk\tdisgust\t0\nfolk\tfear\t0\nfolk\tjoy\t0\nfolk\tnegative\t0\nfolk\tpositive\t0\nfolk\tsadness\t0\nfolk\tsurprise\t0\nfolk\ttrust\t0\nfolklore\tanger\t0\nfolklore\tanticipation\t0\nfolklore\tdisgust\t0\nfolklore\tfear\t0\nfolklore\tjoy\t0\nfolklore\tnegative\t0\nfolklore\tpositive\t0\nfolklore\tsadness\t0\nfolklore\tsurprise\t0\nfolklore\ttrust\t0\nfollicle\tanger\t0\nfollicle\tanticipation\t0\nfollicle\tdisgust\t0\nfollicle\tfear\t0\nfollicle\tjoy\t0\nfollicle\tnegative\t0\nfollicle\tpositive\t0\nfollicle\tsadness\t0\nfollicle\tsurprise\t0\nfollicle\ttrust\t0\nfollicular\tanger\t0\nfollicular\tanticipation\t0\nfollicular\tdisgust\t0\nfollicular\tfear\t0\nfollicular\tjoy\t0\nfollicular\tnegative\t0\nfollicular\tpositive\t0\nfollicular\tsadness\t0\nfollicular\tsurprise\t0\nfollicular\ttrust\t0\nfollow\tanger\t0\nfollow\tanticipation\t0\nfollow\tdisgust\t0\nfollow\tfear\t0\nfollow\tjoy\t0\nfollow\tnegative\t0\nfollow\tpositive\t0\nfollow\tsadness\t0\nfollow\tsurprise\t0\nfollow\ttrust\t0\nfollower\tanger\t0\nfollower\tanticipation\t0\nfollower\tdisgust\t0\nfollower\tfear\t0\nfollower\tjoy\t0\nfollower\tnegative\t0\nfollower\tpositive\t0\nfollower\tsadness\t0\nfollower\tsurprise\t0\nfollower\ttrust\t1\nfolly\tanger\t0\nfolly\tanticipation\t0\nfolly\tdisgust\t0\nfolly\tfear\t0\nfolly\tjoy\t0\nfolly\tnegative\t1\nfolly\tpositive\t0\nfolly\tsadness\t0\nfolly\tsurprise\t0\nfolly\ttrust\t0\nfondling\tanger\t0\nfondling\tanticipation\t0\nfondling\tdisgust\t0\nfondling\tfear\t0\nfondling\tjoy\t0\nfondling\tnegative\t0\nfondling\tpositive\t0\nfondling\tsadness\t0\nfondling\tsurprise\t0\nfondling\ttrust\t0\nfondness\tanger\t0\nfondness\tanticipation\t0\nfondness\tdisgust\t0\nfondness\tfear\t0\nfondness\tjoy\t1\nfondness\tnegative\t0\nfondness\tpositive\t1\nfondness\tsadness\t0\nfondness\tsurprise\t0\nfondness\ttrust\t0\nfont\tanger\t0\nfont\tanticipation\t0\nfont\tdisgust\t0\nfont\tfear\t0\nfont\tjoy\t0\nfont\tnegative\t0\nfont\tpositive\t0\nfont\tsadness\t0\nfont\tsurprise\t0\nfont\ttrust\t0\nfood\tanger\t0\nfood\tanticipation\t0\nfood\tdisgust\t0\nfood\tfear\t0\nfood\tjoy\t1\nfood\tnegative\t0\nfood\tpositive\t1\nfood\tsadness\t0\nfood\tsurprise\t0\nfood\ttrust\t1\nfool\tanger\t0\nfool\tanticipation\t0\nfool\tdisgust\t1\nfool\tfear\t0\nfool\tjoy\t0\nfool\tnegative\t1\nfool\tpositive\t0\nfool\tsadness\t0\nfool\tsurprise\t0\nfool\ttrust\t0\nfooling\tanger\t0\nfooling\tanticipation\t0\nfooling\tdisgust\t0\nfooling\tfear\t0\nfooling\tjoy\t0\nfooling\tnegative\t0\nfooling\tpositive\t0\nfooling\tsadness\t0\nfooling\tsurprise\t0\nfooling\ttrust\t0\nfoolish\tanger\t0\nfoolish\tanticipation\t0\nfoolish\tdisgust\t0\nfoolish\tfear\t0\nfoolish\tjoy\t0\nfoolish\tnegative\t1\nfoolish\tpositive\t0\nfoolish\tsadness\t0\nfoolish\tsurprise\t0\nfoolish\ttrust\t0\nfoolishness\tanger\t0\nfoolishness\tanticipation\t0\nfoolishness\tdisgust\t0\nfoolishness\tfear\t0\nfoolishness\tjoy\t0\nfoolishness\tnegative\t1\nfoolishness\tpositive\t0\nfoolishness\tsadness\t0\nfoolishness\tsurprise\t0\nfoolishness\ttrust\t0\nfoot\tanger\t0\nfoot\tanticipation\t0\nfoot\tdisgust\t0\nfoot\tfear\t0\nfoot\tjoy\t0\nfoot\tnegative\t0\nfoot\tpositive\t0\nfoot\tsadness\t0\nfoot\tsurprise\t0\nfoot\ttrust\t0\nfootball\tanger\t0\nfootball\tanticipation\t1\nfootball\tdisgust\t0\nfootball\tfear\t0\nfootball\tjoy\t1\nfootball\tnegative\t0\nfootball\tpositive\t1\nfootball\tsadness\t0\nfootball\tsurprise\t0\nfootball\ttrust\t0\nfootbridge\tanger\t0\nfootbridge\tanticipation\t0\nfootbridge\tdisgust\t0\nfootbridge\tfear\t0\nfootbridge\tjoy\t0\nfootbridge\tnegative\t0\nfootbridge\tpositive\t0\nfootbridge\tsadness\t0\nfootbridge\tsurprise\t0\nfootbridge\ttrust\t0\nfooting\tanger\t0\nfooting\tanticipation\t0\nfooting\tdisgust\t0\nfooting\tfear\t0\nfooting\tjoy\t0\nfooting\tnegative\t0\nfooting\tpositive\t0\nfooting\tsadness\t0\nfooting\tsurprise\t0\nfooting\ttrust\t1\nfootpath\tanger\t0\nfootpath\tanticipation\t0\nfootpath\tdisgust\t0\nfootpath\tfear\t0\nfootpath\tjoy\t0\nfootpath\tnegative\t0\nfootpath\tpositive\t0\nfootpath\tsadness\t0\nfootpath\tsurprise\t0\nfootpath\ttrust\t0\nfootprint\tanger\t0\nfootprint\tanticipation\t0\nfootprint\tdisgust\t0\nfootprint\tfear\t0\nfootprint\tjoy\t0\nfootprint\tnegative\t0\nfootprint\tpositive\t0\nfootprint\tsadness\t0\nfootprint\tsurprise\t0\nfootprint\ttrust\t0\nfop\tanger\t0\nfop\tanticipation\t0\nfop\tdisgust\t0\nfop\tfear\t0\nfop\tjoy\t0\nfop\tnegative\t0\nfop\tpositive\t0\nfop\tsadness\t0\nfop\tsurprise\t0\nfop\ttrust\t0\nforage\tanger\t0\nforage\tanticipation\t0\nforage\tdisgust\t0\nforage\tfear\t0\nforage\tjoy\t0\nforage\tnegative\t1\nforage\tpositive\t0\nforage\tsadness\t0\nforage\tsurprise\t0\nforage\ttrust\t0\nforay\tanger\t1\nforay\tanticipation\t0\nforay\tdisgust\t0\nforay\tfear\t0\nforay\tjoy\t0\nforay\tnegative\t1\nforay\tpositive\t0\nforay\tsadness\t0\nforay\tsurprise\t0\nforay\ttrust\t0\nforbearance\tanger\t0\nforbearance\tanticipation\t0\nforbearance\tdisgust\t0\nforbearance\tfear\t0\nforbearance\tjoy\t0\nforbearance\tnegative\t0\nforbearance\tpositive\t1\nforbearance\tsadness\t0\nforbearance\tsurprise\t0\nforbearance\ttrust\t0\nforbid\tanger\t0\nforbid\tanticipation\t0\nforbid\tdisgust\t0\nforbid\tfear\t0\nforbid\tjoy\t0\nforbid\tnegative\t1\nforbid\tpositive\t0\nforbid\tsadness\t1\nforbid\tsurprise\t0\nforbid\ttrust\t0\nforbidding\tanger\t1\nforbidding\tanticipation\t0\nforbidding\tdisgust\t0\nforbidding\tfear\t1\nforbidding\tjoy\t0\nforbidding\tnegative\t1\nforbidding\tpositive\t0\nforbidding\tsadness\t0\nforbidding\tsurprise\t0\nforbidding\ttrust\t0\nforce\tanger\t1\nforce\tanticipation\t0\nforce\tdisgust\t0\nforce\tfear\t1\nforce\tjoy\t0\nforce\tnegative\t1\nforce\tpositive\t0\nforce\tsadness\t0\nforce\tsurprise\t0\nforce\ttrust\t0\nforced\tanger\t0\nforced\tanticipation\t0\nforced\tdisgust\t0\nforced\tfear\t1\nforced\tjoy\t0\nforced\tnegative\t1\nforced\tpositive\t0\nforced\tsadness\t0\nforced\tsurprise\t0\nforced\ttrust\t0\nforceps\tanger\t0\nforceps\tanticipation\t0\nforceps\tdisgust\t0\nforceps\tfear\t0\nforceps\tjoy\t0\nforceps\tnegative\t0\nforceps\tpositive\t0\nforceps\tsadness\t0\nforceps\tsurprise\t0\nforceps\ttrust\t0\nforcibly\tanger\t1\nforcibly\tanticipation\t0\nforcibly\tdisgust\t0\nforcibly\tfear\t1\nforcibly\tjoy\t0\nforcibly\tnegative\t1\nforcibly\tpositive\t0\nforcibly\tsadness\t0\nforcibly\tsurprise\t0\nforcibly\ttrust\t0\nford\tanger\t0\nford\tanticipation\t0\nford\tdisgust\t0\nford\tfear\t0\nford\tjoy\t0\nford\tnegative\t0\nford\tpositive\t0\nford\tsadness\t0\nford\tsurprise\t0\nford\ttrust\t0\nfore\tanger\t0\nfore\tanticipation\t0\nfore\tdisgust\t0\nfore\tfear\t0\nfore\tjoy\t0\nfore\tnegative\t0\nfore\tpositive\t1\nfore\tsadness\t0\nfore\tsurprise\t0\nfore\ttrust\t0\nforearm\tanger\t1\nforearm\tanticipation\t1\nforearm\tdisgust\t0\nforearm\tfear\t0\nforearm\tjoy\t0\nforearm\tnegative\t0\nforearm\tpositive\t0\nforearm\tsadness\t0\nforearm\tsurprise\t0\nforearm\ttrust\t0\nforeboding\tanger\t0\nforeboding\tanticipation\t1\nforeboding\tdisgust\t0\nforeboding\tfear\t1\nforeboding\tjoy\t0\nforeboding\tnegative\t1\nforeboding\tpositive\t0\nforeboding\tsadness\t0\nforeboding\tsurprise\t0\nforeboding\ttrust\t0\nforecast\tanger\t0\nforecast\tanticipation\t1\nforecast\tdisgust\t0\nforecast\tfear\t0\nforecast\tjoy\t0\nforecast\tnegative\t0\nforecast\tpositive\t0\nforecast\tsadness\t0\nforecast\tsurprise\t0\nforecast\ttrust\t1\nforecaster\tanger\t0\nforecaster\tanticipation\t0\nforecaster\tdisgust\t0\nforecaster\tfear\t0\nforecaster\tjoy\t0\nforecaster\tnegative\t0\nforecaster\tpositive\t0\nforecaster\tsadness\t0\nforecaster\tsurprise\t0\nforecaster\ttrust\t0\nforeclose\tanger\t0\nforeclose\tanticipation\t0\nforeclose\tdisgust\t0\nforeclose\tfear\t1\nforeclose\tjoy\t0\nforeclose\tnegative\t1\nforeclose\tpositive\t0\nforeclose\tsadness\t1\nforeclose\tsurprise\t0\nforeclose\ttrust\t0\nforefathers\tanger\t0\nforefathers\tanticipation\t0\nforefathers\tdisgust\t0\nforefathers\tfear\t0\nforefathers\tjoy\t1\nforefathers\tnegative\t0\nforefathers\tpositive\t1\nforefathers\tsadness\t0\nforefathers\tsurprise\t0\nforefathers\ttrust\t1\nforefinger\tanger\t0\nforefinger\tanticipation\t0\nforefinger\tdisgust\t0\nforefinger\tfear\t0\nforefinger\tjoy\t0\nforefinger\tnegative\t0\nforefinger\tpositive\t0\nforefinger\tsadness\t0\nforefinger\tsurprise\t0\nforefinger\ttrust\t0\nforego\tanger\t0\nforego\tanticipation\t0\nforego\tdisgust\t0\nforego\tfear\t0\nforego\tjoy\t0\nforego\tnegative\t1\nforego\tpositive\t0\nforego\tsadness\t0\nforego\tsurprise\t0\nforego\ttrust\t0\nforegoing\tanger\t0\nforegoing\tanticipation\t0\nforegoing\tdisgust\t0\nforegoing\tfear\t0\nforegoing\tjoy\t0\nforegoing\tnegative\t0\nforegoing\tpositive\t1\nforegoing\tsadness\t0\nforegoing\tsurprise\t0\nforegoing\ttrust\t0\nforegone\tanger\t0\nforegone\tanticipation\t0\nforegone\tdisgust\t0\nforegone\tfear\t0\nforegone\tjoy\t0\nforegone\tnegative\t0\nforegone\tpositive\t0\nforegone\tsadness\t0\nforegone\tsurprise\t0\nforegone\ttrust\t0\nforeground\tanger\t0\nforeground\tanticipation\t0\nforeground\tdisgust\t0\nforeground\tfear\t0\nforeground\tjoy\t0\nforeground\tnegative\t0\nforeground\tpositive\t0\nforeground\tsadness\t0\nforeground\tsurprise\t0\nforeground\ttrust\t0\nforehead\tanger\t0\nforehead\tanticipation\t0\nforehead\tdisgust\t0\nforehead\tfear\t0\nforehead\tjoy\t0\nforehead\tnegative\t0\nforehead\tpositive\t0\nforehead\tsadness\t0\nforehead\tsurprise\t0\nforehead\ttrust\t0\nforeign\tanger\t0\nforeign\tanticipation\t0\nforeign\tdisgust\t0\nforeign\tfear\t0\nforeign\tjoy\t0\nforeign\tnegative\t1\nforeign\tpositive\t0\nforeign\tsadness\t0\nforeign\tsurprise\t0\nforeign\ttrust\t0\nforeigner\tanger\t0\nforeigner\tanticipation\t0\nforeigner\tdisgust\t0\nforeigner\tfear\t1\nforeigner\tjoy\t0\nforeigner\tnegative\t1\nforeigner\tpositive\t0\nforeigner\tsadness\t0\nforeigner\tsurprise\t0\nforeigner\ttrust\t0\nforeman\tanger\t0\nforeman\tanticipation\t0\nforeman\tdisgust\t0\nforeman\tfear\t0\nforeman\tjoy\t0\nforeman\tnegative\t0\nforeman\tpositive\t1\nforeman\tsadness\t0\nforeman\tsurprise\t0\nforeman\ttrust\t0\nforensic\tanger\t0\nforensic\tanticipation\t0\nforensic\tdisgust\t0\nforensic\tfear\t0\nforensic\tjoy\t0\nforensic\tnegative\t0\nforensic\tpositive\t0\nforensic\tsadness\t0\nforensic\tsurprise\t0\nforensic\ttrust\t0\nforerunner\tanger\t0\nforerunner\tanticipation\t0\nforerunner\tdisgust\t0\nforerunner\tfear\t0\nforerunner\tjoy\t0\nforerunner\tnegative\t0\nforerunner\tpositive\t1\nforerunner\tsadness\t0\nforerunner\tsurprise\t0\nforerunner\ttrust\t0\nforesee\tanger\t0\nforesee\tanticipation\t1\nforesee\tdisgust\t0\nforesee\tfear\t0\nforesee\tjoy\t0\nforesee\tnegative\t0\nforesee\tpositive\t1\nforesee\tsadness\t0\nforesee\tsurprise\t1\nforesee\ttrust\t1\nforeseen\tanger\t0\nforeseen\tanticipation\t1\nforeseen\tdisgust\t0\nforeseen\tfear\t0\nforeseen\tjoy\t0\nforeseen\tnegative\t0\nforeseen\tpositive\t1\nforeseen\tsadness\t0\nforeseen\tsurprise\t0\nforeseen\ttrust\t0\nforesight\tanger\t0\nforesight\tanticipation\t1\nforesight\tdisgust\t0\nforesight\tfear\t0\nforesight\tjoy\t0\nforesight\tnegative\t0\nforesight\tpositive\t1\nforesight\tsadness\t0\nforesight\tsurprise\t0\nforesight\ttrust\t1\nforest\tanger\t0\nforest\tanticipation\t0\nforest\tdisgust\t0\nforest\tfear\t0\nforest\tjoy\t0\nforest\tnegative\t0\nforest\tpositive\t0\nforest\tsadness\t0\nforest\tsurprise\t0\nforest\ttrust\t0\nforethought\tanger\t0\nforethought\tanticipation\t0\nforethought\tdisgust\t0\nforethought\tfear\t0\nforethought\tjoy\t0\nforethought\tnegative\t0\nforethought\tpositive\t0\nforethought\tsadness\t0\nforethought\tsurprise\t0\nforethought\ttrust\t0\nforewarned\tanger\t0\nforewarned\tanticipation\t1\nforewarned\tdisgust\t0\nforewarned\tfear\t1\nforewarned\tjoy\t0\nforewarned\tnegative\t1\nforewarned\tpositive\t0\nforewarned\tsadness\t0\nforewarned\tsurprise\t0\nforewarned\ttrust\t0\nforeword\tanger\t0\nforeword\tanticipation\t0\nforeword\tdisgust\t0\nforeword\tfear\t0\nforeword\tjoy\t0\nforeword\tnegative\t0\nforeword\tpositive\t0\nforeword\tsadness\t0\nforeword\tsurprise\t0\nforeword\ttrust\t0\nforfeit\tanger\t1\nforfeit\tanticipation\t0\nforfeit\tdisgust\t0\nforfeit\tfear\t0\nforfeit\tjoy\t0\nforfeit\tnegative\t1\nforfeit\tpositive\t0\nforfeit\tsadness\t1\nforfeit\tsurprise\t0\nforfeit\ttrust\t0\nforfeited\tanger\t0\nforfeited\tanticipation\t0\nforfeited\tdisgust\t0\nforfeited\tfear\t0\nforfeited\tjoy\t0\nforfeited\tnegative\t1\nforfeited\tpositive\t0\nforfeited\tsadness\t0\nforfeited\tsurprise\t0\nforfeited\ttrust\t0\nforfeiture\tanger\t0\nforfeiture\tanticipation\t0\nforfeiture\tdisgust\t0\nforfeiture\tfear\t1\nforfeiture\tjoy\t0\nforfeiture\tnegative\t1\nforfeiture\tpositive\t0\nforfeiture\tsadness\t1\nforfeiture\tsurprise\t0\nforfeiture\ttrust\t0\nforge\tanger\t0\nforge\tanticipation\t0\nforge\tdisgust\t0\nforge\tfear\t0\nforge\tjoy\t0\nforge\tnegative\t0\nforge\tpositive\t1\nforge\tsadness\t0\nforge\tsurprise\t0\nforge\ttrust\t0\nforgery\tanger\t0\nforgery\tanticipation\t0\nforgery\tdisgust\t0\nforgery\tfear\t0\nforgery\tjoy\t0\nforgery\tnegative\t1\nforgery\tpositive\t0\nforgery\tsadness\t0\nforgery\tsurprise\t0\nforgery\ttrust\t0\nforget\tanger\t0\nforget\tanticipation\t0\nforget\tdisgust\t0\nforget\tfear\t0\nforget\tjoy\t0\nforget\tnegative\t1\nforget\tpositive\t0\nforget\tsadness\t0\nforget\tsurprise\t0\nforget\ttrust\t0\nforgetful\tanger\t0\nforgetful\tanticipation\t0\nforgetful\tdisgust\t0\nforgetful\tfear\t0\nforgetful\tjoy\t0\nforgetful\tnegative\t0\nforgetful\tpositive\t0\nforgetful\tsadness\t0\nforgetful\tsurprise\t0\nforgetful\ttrust\t0\nforgetfulness\tanger\t0\nforgetfulness\tanticipation\t0\nforgetfulness\tdisgust\t0\nforgetfulness\tfear\t0\nforgetfulness\tjoy\t0\nforgetfulness\tnegative\t0\nforgetfulness\tpositive\t0\nforgetfulness\tsadness\t0\nforgetfulness\tsurprise\t0\nforgetfulness\ttrust\t0\nforgive\tanger\t0\nforgive\tanticipation\t0\nforgive\tdisgust\t0\nforgive\tfear\t0\nforgive\tjoy\t0\nforgive\tnegative\t0\nforgive\tpositive\t1\nforgive\tsadness\t0\nforgiv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ht\tanger\t0\nfraught\tanticipation\t0\nfraught\tdisgust\t0\nfraught\tfear\t1\nfraught\tjoy\t0\nfraught\tnegative\t1\nfraught\tpositive\t0\nfraught\tsadness\t1\nfraught\tsurprise\t0\nfraught\ttrust\t0\nfray\tanger\t0\nfray\tanticipation\t0\nfray\tdisgust\t0\nfray\tfear\t0\nfray\tjoy\t0\nfray\tnegative\t1\nfray\tpositive\t0\nfray\tsadness\t0\nfray\tsurprise\t0\nfray\ttrust\t0\nfrayed\tanger\t0\nfrayed\tanticipation\t0\nfrayed\tdisgust\t0\nfrayed\tfear\t0\nfrayed\tjoy\t0\nfrayed\tnegative\t1\nfrayed\tpositive\t0\nfrayed\tsadness\t1\nfrayed\tsurprise\t0\nfrayed\ttrust\t0\nfreak\tanger\t0\nfreak\tanticipation\t0\nfreak\tdisgust\t0\nfreak\tfear\t0\nfreak\tjoy\t0\nfreak\tnegative\t0\nfreak\tpositive\t0\nfreak\tsadness\t0\nfreak\tsurprise\t0\nfreak\ttrust\t0\nfreakish\tanger\t0\nfreakish\tanticipation\t0\nfreakish\tdisgust\t1\nfreakish\tfear\t1\nfreakish\tjoy\t0\nfreakish\tnegative\t1\nfreakish\tpositive\t0\nfreakish\tsadness\t0\nfreakish\tsurprise\t1\nfreakish\ttrust\t0\nfreedom\tanger\t0\nfreedom\tanticipation\t0\nfreedom\tdisgust\t0\nfreedom\tfear\t0\nfreedom\tjoy\t1\nfreedom\tnegative\t0\nfreedom\tpositive\t1\nfreedom\tsadness\t0\nfreedom\tsurprise\t0\nfreedom\ttrust\t1\nfreehold\tanger\t0\nfreehold\tanticipation\t0\nfreehold\tdisgust\t0\nfreehold\tfear\t0\nfreehold\tjoy\t0\nfreehold\tnegative\t0\nfreehold\tpositive\t0\nfreehold\tsadness\t0\nfreehold\tsurprise\t0\nfreehold\ttrust\t0\nfreelance\tanger\t0\nfreelance\tanticipation\t0\nfreelance\tdisgust\t0\nfreelance\tfear\t0\nfreelance\tjoy\t0\nfreelance\tnegative\t0\nfreelance\tpositive\t0\nfreelance\tsadness\t0\nfreelance\tsurprise\t0\nfreelance\ttrust\t0\nfreely\tanger\t0\nfreely\tanticipation\t0\nfreely\tdisgust\t0\nfreely\tfear\t0\nfreely\tjoy\t1\nfreely\tnegative\t0\nfreely\tpositive\t1\nfreely\tsadness\t0\nfreely\tsurprise\t0\nfreely\ttrust\t1\nfreeway\tanger\t0\nfreeway\tanticipation\t0\nfreeway\tdisgust\t0\nfreeway\tfear\t0\nfreeway\tjoy\t0\nfreeway\tnegative\t0\nfreeway\tpositive\t0\nfreeway\tsadness\t0\nfreeway\tsurprise\t0\nfreeway\ttrust\t0\nfreeze\tanger\t0\nfreeze\tanticipation\t0\nfreeze\tdisgust\t0\nfreeze\tfear\t0\nfreeze\tjoy\t0\nfreeze\tnegative\t0\nfreeze\tpositive\t0\nfreeze\tsadness\t0\nfreeze\tsurprise\t0\nfreeze\ttrust\t0\nfreezer\tanger\t0\nfreezer\tanticipation\t0\nfreezer\tdisgust\t0\nfreezer\tfear\t0\nfreezer\tjoy\t0\nfreezer\tnegative\t0\nfreezer\tpositive\t0\nfreezer\tsadness\t0\nfreezer\tsurprise\t0\nfreezer\ttrust\t0\nfreezing\tanger\t0\nfreezing\tanticipation\t0\nfreezing\tdisgust\t0\nfreezing\tfear\t0\nfreezing\tjoy\t0\nfreezing\tnegative\t1\nfreezing\tpositive\t0\nfreezing\tsadness\t0\nfreezing\tsurprise\t0\nfreezing\ttrust\t0\nfreight\tanger\t0\nfreight\tanticipation\t0\nfreight\tdisgust\t0\nfreight\tfear\t0\nfreight\tjoy\t0\nfreight\tnegative\t0\nfreight\tpositive\t0\nfreight\tsadness\t0\nfreight\tsurprise\t0\nfreight\ttrust\t0\nfrenetic\tanger\t1\nfrenetic\tanticipation\t0\nfrenetic\tdisgust\t0\nfrenetic\tfear\t1\nfrenetic\tjoy\t0\nfrenetic\tnegative\t1\nfrenetic\tpositive\t0\nfrenetic\tsadness\t0\nfrenetic\tsurprise\t1\nfrenetic\ttrust\t0\nfrenzied\tanger\t1\nfrenzied\tanticipation\t0\nfrenzied\tdisgust\t0\nfrenzied\tfear\t1\nfrenzied\tjoy\t0\nfrenzied\tnegative\t1\nfrenzied\tpositive\t0\nfrenzied\tsadness\t0\nfrenzied\tsurprise\t0\nfrenzied\ttrust\t0\nfrenzy\tanger\t0\nfrenzy\tanticipation\t0\nfrenzy\tdisgust\t0\nfrenzy\tfear\t0\nfrenzy\tjoy\t0\nfrenzy\tnegative\t1\nfrenzy\tpositive\t0\nfrenzy\tsadness\t0\nfrenzy\tsurprise\t0\nfrenzy\ttrust\t0\nfrequency\tanger\t0\nfrequency\tanticipation\t0\nfrequency\tdisgust\t0\nfrequency\tfear\t0\nfrequency\tjoy\t0\nfrequency\tnegative\t0\nfrequency\tpositive\t0\nfrequency\tsadness\t0\nfrequency\tsurprise\t0\nfrequency\ttrust\t0\nfrequent\tanger\t0\nfrequent\tanticipation\t0\nfrequent\tdisgust\t0\nfrequent\tfear\t0\nfrequent\tjoy\t0\nfrequent\tnegative\t0\nfrequent\tpositive\t0\nfrequent\tsadness\t0\nfrequent\tsurprise\t0\nfrequent\ttrust\t0\nfrequently\tanger\t0\nfrequently\tanticipation\t0\nfrequently\tdisgust\t0\nfrequently\tfear\t0\nfrequently\tjoy\t0\nfrequently\tnegative\t0\nfrequently\tpositive\t0\nfrequently\tsadness\t0\nfrequently\tsurprise\t0\nfrequently\ttrust\t0\nfresco\tanger\t0\nfresco\tanticipation\t0\nfresco\tdisgust\t0\nfresco\tfear\t0\nfresco\tjoy\t0\nfresco\tnegative\t0\nfresco\tpositive\t0\nfresco\tsadness\t0\nfresco\tsurprise\t0\nfresco\ttrust\t0\nfreshman\tanger\t0\nfreshman\tanticipation\t0\nfreshman\tdisgust\t0\nfreshman\tfear\t0\nfreshman\tjoy\t0\nfreshman\tnegative\t0\nfreshman\tpositive\t0\nfreshman\tsadness\t0\nfreshman\tsurprise\t0\nfreshman\ttrust\t0\nfret\tanger\t0\nfret\tanticipation\t0\nfret\tdisgust\t0\nfret\tfear\t1\nfret\tjoy\t0\nfret\tnegative\t1\nfret\tpositive\t0\nfret\tsadness\t0\nfret\tsurprise\t0\nfret\ttrust\t0\nfriction\tanger\t1\nfriction\tanticipation\t0\nfriction\tdisgust\t0\nfriction\tfear\t0\nfriction\tjoy\t0\nfriction\tnegative\t0\nfriction\tpositive\t0\nfriction\tsadness\t0\nfriction\tsurprise\t0\nfriction\ttrust\t0\nfriend\tanger\t0\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rudent\tdisgust\t0\nimprudent\tfear\t0\nimprudent\tjoy\t0\nimprudent\tnegative\t1\nimprudent\tpositive\t0\nimprudent\tsadness\t1\nimprudent\tsurprise\t0\nimprudent\ttrust\t0\nimpulse\tanger\t0\nimpulse\tanticipation\t0\nimpulse\tdisgust\t0\nimpulse\tfear\t0\nimpulse\tjoy\t0\nimpulse\tnegative\t0\nimpulse\tpositive\t0\nimpulse\tsadness\t0\nimpulse\tsurprise\t0\nimpulse\ttrust\t0\nimpunity\tanger\t0\nimpunity\tanticipation\t0\nimpunity\tdisgust\t0\nimpunity\tfear\t0\nimpunity\tjoy\t0\nimpunity\tnegative\t0\nimpunity\tpositive\t0\nimpunity\tsadness\t0\nimpunity\tsurprise\t0\nimpunity\ttrust\t0\nimpure\tanger\t0\nimpure\tanticipation\t0\nimpure\tdisgust\t1\nimpure\tfear\t0\nimpure\tjoy\t0\nimpure\tnegative\t1\nimpure\tpositive\t0\nimpure\tsadness\t0\nimpure\tsurprise\t0\nimpure\ttrust\t0\nimpurity\tanger\t0\nimpurity\tanticipation\t0\nimpurity\tdisgust\t1\nimpurity\tfear\t0\nimpurity\tjoy\t0\nimpurity\tnegative\t1\nimpurity\tpositive\t0\nimpurity\tsadness\t0\nimpurity\tsurprise\t0\nimpurity\ttrust\t0\nimputation\tanger\t0\nimputation\tanticipation\t0\nimputation\tdisgust\t0\nimputation\tfear\t0\nimputation\tjoy\t0\nimputation\tnegative\t1\nimputation\tpositive\t0\nimputation\tsadness\t0\nimputation\tsurprise\t0\nimputation\ttrust\t0\ninability\tanger\t0\ninability\tanticipation\t0\ninability\tdisgust\t0\ninability\tfear\t0\ninability\tjoy\t0\ninability\tnegative\t1\ninability\tpositive\t0\ninability\tsadness\t1\ninability\tsurprise\t0\ninability\ttrust\t0\ninaccessible\tanger\t0\ninaccessible\tanticipation\t0\ninaccessible\tdisgust\t0\ninaccessible\tfear\t0\ninaccessible\tjoy\t0\ninaccessible\tnegative\t1\ninaccessible\tpositive\t0\ninaccessible\tsadness\t0\ninaccessible\tsurprise\t0\ninaccessible\ttrust\t0\ninaccurate\tanger\t0\ninaccurate\tanticipation\t0\ninaccurate\tdisgust\t0\ninaccurate\tfear\t0\ninaccurate\tjoy\t0\ninaccurate\tnegative\t1\ninaccurate\tpositive\t0\ninaccurate\tsadness\t0\ninaccurate\tsurprise\t0\ninaccurate\ttrust\t0\ninaction\tanger\t0\ninaction\tanticipation\t0\ninaction\tdisgust\t0\ninaction\tfear\t0\ninaction\tjoy\t0\ninaction\tnegative\t1\ninaction\tpositive\t0\ninaction\tsadness\t0\ninaction\tsurprise\t0\ninaction\ttrust\t0\ninactivate\tanger\t0\ninactivate\tanticipation\t0\ninactivate\tdisgust\t0\ninactivate\tfear\t0\ninactivate\tjoy\t0\ninactivate\tnegative\t0\ninactivate\tpositive\t0\ninactivate\tsadness\t0\ninactivate\tsurprise\t0\ninactivate\ttrust\t0\ninactivation\tanger\t0\ninactivation\tanticipation\t0\ninactivation\tdisgust\t0\ninactivation\tfear\t0\ninactivation\tjoy\t0\ninactivation\tnegative\t0\ninactivation\tpositive\t0\ninactivation\tsadness\t0\ninactivation\tsurprise\t0\ninactivation\ttrust\t0\ninactive\tanger\t0\ninactive\tanticipation\t0\ninactive\tdisgust\t0\ninactive\tfear\t0\ninactive\tjoy\t0\ninactive\tnegative\t0\ninactive\tpositive\t0\ninactive\tsadness\t0\ninactive\tsurprise\t0\ninactive\ttrust\t0\ninactivity\tanger\t0\ninactivity\tanticipation\t0\ninactivity\tdisgust\t0\ninactivity\tfear\t0\ninactivity\tjoy\t0\ninactivity\tnegative\t1\ninactivity\tpositive\t0\ninactivity\tsadness\t0\ninactivity\tsurprise\t0\ninactivity\ttrust\t0\ninadequacy\tanger\t0\ninadequacy\tanticipation\t0\ninadequacy\tdisgust\t0\ninadequacy\tfear\t0\ninadequacy\tjoy\t0\ninadequacy\tnegative\t1\ninadequacy\tpositive\t0\ninadequacy\tsadness\t0\ninadequacy\tsurprise\t0\ninadequacy\ttrust\t0\ninadequate\tanger\t0\ninadequate\tanticipation\t0\ninadequate\tdisgust\t0\ninadequate\tfear\t0\ninadequate\tjoy\t0\ninadequate\tnegative\t1\ninadequate\tpositive\t0\ninadequate\tsadness\t1\ninadequate\tsurprise\t0\ninadequate\ttrust\t0\ninadmissible\tanger\t1\ninadmissible\tanticipation\t0\ninadmissible\tdisgust\t1\ninadmissible\tfear\t0\ninadmissible\tjoy\t0\ninadmissible\tnegative\t1\ninadmissible\tpositive\t0\ninadmissible\tsadness\t0\ninadmissible\tsurprise\t0\ninadmissible\ttrust\t0\ninadvertent\tanger\t0\ninadvertent\tanticipation\t0\ninadvertent\tdisgust\t0\ninadvertent\tfear\t0\ninadvertent\tjoy\t0\ninadvertent\tnegative\t0\ninadvertent\tpositive\t0\ninadvertent\tsadness\t0\ninadvertent\tsurprise\t0\ninadvertent\ttrust\t0\ninadvertently\tanger\t0\ninadvertently\tanticipation\t0\ninadvertently\tdisgust\t0\ninadvertently\tfear\t0\ninadvertently\tjoy\t0\ninadvertently\tnegative\t0\ninadvertently\tpositive\t0\ninadvertently\tsadness\t0\ninadvertently\tsurprise\t0\ninadvertently\ttrust\t0\ninalienable\tanger\t0\ninalienable\tanticipation\t0\ninalienable\tdisgust\t0\ninalienable\tfear\t0\ninalienable\tjoy\t0\ninalienable\tnegative\t0\ninalienable\tpositive\t1\ninalienable\tsadness\t0\ninalienable\tsurprise\t0\ninalienable\ttrust\t0\ninane\tanger\t0\ninane\tanticipation\t0\ninane\tdisgust\t0\ninane\tfear\t0\ninane\tjoy\t0\ninane\tnegative\t1\ninane\tpositive\t0\ninane\tsadness\t0\ninane\tsurprise\t0\ninane\ttrust\t0\ninanimate\tanger\t0\ninanimate\tanticipation\t0\ninanimate\tdisgust\t0\ninanimate\tfear\t0\ninanimate\tjoy\t0\ninanimate\tnegative\t0\ninanimate\tpositive\t0\ninanimate\tsadness\t0\nina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ipation\t0\nincest\tdisgust\t1\nincest\tfear\t1\nincest\tjoy\t0\nincest\tnegative\t1\nincest\tpositive\t0\nincest\tsadness\t1\nincest\tsurprise\t0\nincest\ttrust\t0\nincestuous\tanger\t0\nincestuous\tanticipation\t0\nincestuous\tdisgust\t1\nincestuous\tfear\t0\nincestuous\tjoy\t0\nincestuous\tnegative\t1\nincestuous\tpositive\t0\nincestuous\tsadness\t0\nincestuous\tsurprise\t0\nincestuous\ttrust\t0\ninch\tanger\t0\ninch\tanticipation\t0\ninch\tdisgust\t0\ninch\tfear\t0\ninch\tjoy\t0\ninch\tnegative\t0\ninch\tpositive\t0\ninch\tsadness\t0\ninch\tsurprise\t0\ninch\ttrust\t0\nincidence\tanger\t0\nincidence\tanticipation\t0\nincidence\tdisgust\t0\nincidence\tfear\t0\nincidence\tjoy\t0\nincidence\tnegative\t0\nincidence\tpositive\t0\nincidence\tsadness\t0\nincidence\tsurprise\t0\nincidence\ttrust\t0\nincident\tanger\t0\nincident\tanticipation\t0\nincident\tdisgust\t0\nincident\tfear\t0\nincident\tjoy\t0\nincident\tnegative\t0\nincident\tpositive\t0\nincident\tsadness\t0\nincident\tsurprise\t1\nincident\ttrust\t0\nincidentally\tanger\t0\nincidentally\tanticipation\t0\nincidentally\tdisgust\t0\nincidentally\tfear\t0\nincidentally\tjoy\t0\nincidentally\tnegative\t0\nincidentally\tpositive\t0\nincidentally\tsadness\t0\nincidentally\tsurprise\t0\nincidentally\ttrust\t0\nincineration\tanger\t0\nincineration\tanticipation\t0\nincineration\tdisgust\t0\nincineration\tfear\t0\nincineration\tjoy\t0\nincineration\tnegative\t1\nincineration\tpositive\t0\nincineration\tsadness\t0\nincineration\tsurprise\t0\nincineration\ttrust\t0\nincipient\tanger\t0\nincipient\tanticipation\t0\nincipient\tdisgust\t0\nincipient\tfear\t0\nincipient\tjoy\t0\nincipient\tnegative\t0\nincipient\tpositive\t0\nincipient\tsadness\t0\nincipient\tsurprise\t0\nincipient\ttrust\t0\nincision\tanger\t0\nincision\tanticipation\t0\nincision\tdisgust\t0\nincision\tfear\t0\nincision\tjoy\t0\nincision\tnegative\t0\nincision\tpositive\t0\nincision\tsadness\t0\nincision\tsurprise\t0\nincision\ttrust\t0\nincisive\tanger\t0\nincisive\tanticipation\t0\nincisive\tdisgust\t0\nincisive\tfear\t0\nincisive\tjoy\t0\nincisive\tnegative\t0\nincisive\tpositive\t1\nincisive\tsadness\t0\nincisive\tsurprise\t0\nincisive\ttrust\t0\nincite\tanger\t1\nincite\tanticipation\t1\nincite\tdisgust\t0\nincite\tfear\t1\nincite\tjoy\t0\nincite\tnegative\t1\nincite\tpositive\t0\nincite\tsadness\t0\nincite\tsurprise\t0\nincite\ttrust\t0\nincitement\tanger\t0\nincitement\tanticipation\t0\nincitement\tdisgust\t0\nincitement\tfear\t0\nincitement\tjoy\t0\nincitement\tnegative\t0\nincitement\tpositive\t0\nincitement\tsadness\t0\nincitement\tsurprise\t0\nincitement\ttrust\t0\ninclement\tanger\t0\ninclement\tanticipation\t0\ninclement\tdisgust\t0\ninclement\tfear\t0\ninclement\tjoy\t0\ninclement\tnegative\t1\ninclement\tpositive\t0\ninclement\tsadness\t0\ninclement\tsurprise\t0\ninclement\ttrust\t0\ninclination\tanger\t0\ninclination\tanticipation\t0\ninclination\tdisgust\t0\ninclination\tfear\t0\ninclination\tjoy\t0\ninclination\tnegative\t0\ninclination\tpositive\t0\ninclination\tsadness\t0\ninclination\tsurprise\t0\ninclination\ttrust\t0\nincline\tanger\t0\nincline\tanticipation\t0\nincline\tdisgust\t0\nincline\tfear\t0\nincline\tjoy\t0\nincline\tnegative\t0\nincline\tpositive\t0\nincline\tsadness\t0\nincline\tsurprise\t0\nincline\ttrust\t1\ninclined\tanger\t0\ninclined\tanticipation\t0\ninclined\tdisgust\t0\ninclined\tfear\t0\ninclined\tjoy\t0\ninclined\tnegative\t0\ninclined\tpositive\t0\ninclined\tsadness\t0\ninclined\tsurprise\t0\ninclined\ttrust\t0\ninclude\tanger\t0\ninclude\tanticipation\t0\ninclude\tdisgust\t0\ninclude\tfear\t0\ninclude\tjoy\t0\ninclude\tnegative\t0\ninclude\tpositive\t1\ninclude\tsadness\t0\ninclude\tsurprise\t0\ninclude\ttrust\t0\nincluded\tanger\t0\nincluded\tanticipation\t0\nincluded\tdisgust\t0\nincluded\tfear\t0\nincluded\tjoy\t0\nincluded\tnegative\t0\nincluded\tpositive\t1\nincluded\tsadness\t0\nincluded\tsurprise\t0\nincluded\ttrust\t0\nincluding\tanger\t0\nincluding\tanticipation\t0\nincluding\tdisgust\t0\nincluding\tfear\t0\nincluding\tjoy\t0\nincluding\tnegative\t0\nincluding\tpositive\t1\nincluding\tsadness\t0\nincluding\tsurprise\t0\nincluding\ttrust\t0\ninclusion\tanger\t0\ninclusion\tanticipation\t0\ninclusion\tdisgust\t0\ninclusion\tfear\t0\ninclusion\tjoy\t0\ninclusion\tnegative\t0\ninclusion\tpositive\t0\ninclusion\tsadness\t0\ninclusion\tsurprise\t0\ninclusion\ttrust\t1\ninclusive\tanger\t0\ninclusive\tanticipation\t0\ninclusive\tdisgust\t0\ninclusive\tfear\t0\ninclusive\tjoy\t0\ninclusive\tnegative\t0\ninclusive\tpositive\t1\ninclusive\tsadness\t0\ninclusive\tsurprise\t0\ninclusive\ttrust\t0\nincognito\tanger\t0\nincognito\tanticipation\t0\nincognito\tdisgust\t0\nincognito\tfear\t0\nincognito\tjoy\t0\nincognito\tnegative\t0\nincognito\tpositive\t0\nincognito\tsadness\t0\nincognito\tsurprise\t0\nincognito\ttrust\t0\nincoherent\tanger\t0\nincoherent\tanticipation\t0\nincoherent\tdisgust\t0\nincoherent\tfear\t0\nincoherent\tjoy\t0\nincoherent\tnegative\t1\nincoherent\tpositive\t0\nincoherent\tsadness\t0\nincoherent\tsurprise\t0\nincoherent\ttrust\t0\nincome\tanger\t0\nincome\tanticipation\t1\nincome\tdisgust\t0\nincome\tfear\t0\nincome\tjoy\t1\nincome\tnegative\t1\nincome\tpositive\t1\nincome\tsadness\t1\nincome\tsurprise\t0\nincome\ttrust\t1\nincoming\tanger\t0\nincoming\tanticipation\t0\nincoming\tdisgust\t0\nincoming\tfear\t0\nincoming\tjoy\t0\nincoming\tnegative\t0\nincoming\tpositive\t0\nincoming\tsadness\t0\nincoming\tsurprise\t0\nincoming\ttrust\t0\nincompatible\tanger\t1\nincompatible\tanticipation\t0\nincompatible\tdisgust\t1\nincompatible\tfear\t0\nincompatible\tjoy\t0\nincompatible\tnegative\t1\nincompatible\tpositive\t0\nincompatible\tsadness\t1\nincompatible\tsurprise\t0\nincompatible\ttrust\t0\nincompetence\tanger\t0\nincompetence\tanticipation\t0\nincompetence\tdisgust\t0\nincompetence\tfear\t0\nincompetence\tjoy\t0\nincompetence\tnegative\t1\nincompetence\tpositive\t0\nincompetence\tsadness\t0\nincompetence\tsurprise\t0\nincompetence\ttrust\t0\nincompetent\tanger\t1\nincompetent\tanticipation\t0\nincompetent\tdisgust\t0\nincompetent\tfear\t0\nincompetent\tjoy\t0\nincompetent\tnegative\t1\nincompetent\tpositive\t0\nincompetent\tsadness\t1\nincompetent\tsurprise\t0\nincompetent\ttrust\t0\nincompletely\tanger\t0\nincompletely\tanticipation\t0\nincompletely\tdisgust\t0\nincompletely\tfear\t0\nincompletely\tjoy\t0\nincompletely\tnegative\t0\nincompletely\tpositive\t0\nincompletely\tsadness\t0\nincompletely\tsurprise\t0\nincompletely\ttrust\t0\nincompleteness\tanger\t0\nincompleteness\tanticipation\t0\nincompleteness\tdisgust\t0\nincompleteness\tfear\t0\nincompleteness\tjoy\t0\nincompleteness\tnegative\t1\nincompleteness\tpositive\t0\nincompleteness\tsadness\t0\nincompleteness\tsurprise\t0\nincompleteness\ttrust\t0\nincomprehensible\tanger\t0\nincomprehensible\tanticipation\t0\nincomprehensible\tdisgust\t0\nincomprehensible\tfear\t0\nincomprehensible\tjoy\t0\nincomprehensible\tnegative\t1\nincomprehensible\tpositive\t0\nincomprehensible\tsadness\t0\nincomprehensible\tsurprise\t0\nincomprehensible\ttrust\t0\ninconclusive\tanger\t0\ninconclusive\tanticipation\t0\ninconclusive\tdisgust\t0\ninconclusive\tfear\t0\ninconclusive\tjoy\t0\ninconclusive\tnegative\t0\ninconclusive\tpositive\t0\ninconclusive\tsadness\t0\ninconclusive\tsurprise\t0\ninconclusive\ttrust\t0\nincongruous\tanger\t1\nincongruous\tanticipation\t0\nincongruous\tdisgust\t0\nincongruous\tfear\t0\nincongruous\tjoy\t0\nincongruous\tnegative\t1\nincongruous\tpositive\t0\nincongruous\tsadness\t0\nincongruous\tsurprise\t0\nincongruous\ttrust\t0\ninconsequential\tanger\t0\ninconsequential\tanticipation\t0\ninconsequential\tdisgust\t0\ninconsequential\tfear\t0\ninconsequential\tjoy\t0\ninconsequential\tnegative\t1\ninconsequential\tpositive\t0\ninconsequential\tsadness\t1\ninconsequential\tsurprise\t0\ninconsequential\ttrust\t0\ninconsiderate\tanger\t1\ninconsiderate\tanticipation\t0\ninconsiderate\tdisgust\t1\ninconsiderate\tfear\t0\ninconsiderate\tjoy\t0\ninconsiderate\tnegative\t1\ninconsiderate\tpositive\t0\ninconsiderate\tsadness\t1\ninconsiderate\tsurprise\t0\ninconsiderate\ttrust\t0\ninconsistency\tanger\t0\ninconsistency\tanticipation\t0\ninconsistency\tdisgust\t0\ninconsistency\tfear\t0\ninconsistency\tjoy\t0\ninconsistency\tnegative\t1\ninconsistency\tpositive\t0\ninconsistency\tsadness\t0\ninconsistency\tsurprise\t0\ninconsistency\ttrust\t0\ninconspicuous\tanger\t0\ninconspicuous\tanticipation\t0\ninconspicuous\tdisgust\t0\ninconspicuous\tfear\t0\ninconspicuous\tjoy\t0\ninconspicuous\tnegative\t0\ninconspicuous\tpositive\t0\ninconspicuous\tsadness\t0\ninconspicuous\tsurprise\t0\ninconspicuous\ttrust\t0\nincontinence\tanger\t0\nincontinence\tanticipation\t0\nincontinence\tdisgust\t0\nincontinence\tfear\t0\nincontinence\tjoy\t0\nincontinence\tnegative\t0\nincontinence\tpositive\t0\nincontinence\tsadness\t0\nincontinence\tsurprise\t1\nincontinence\ttrust\t0\ninconvenient\tanger\t1\ninconvenient\tanticipation\t0\ninconvenient\tdisgust\t1\ninconvenient\tfear\t0\ninconvenient\tjoy\t0\ninconvenient\tnegative\t1\ninconvenient\tpositive\t0\ninconvenient\tsadness\t1\ninconvenient\tsurprise\t0\ninconvenient\ttrust\t0\nincorporate\tanger\t0\nincorporate\tanticipation\t0\nincorporate\tdisgust\t0\nincorporate\tfear\t0\nincorporate\tjoy\t0\nincorporate\tnegative\t0\nincorporate\tpositive\t0\nincorporate\tsadness\t0\nincorporate\tsurprise\t0\nincorporate\ttrust\t0\nincorporation\tanger\t0\nincorporation\tanticipation\t0\nincorporation\tdisgust\t0\nincorporation\tfear\t0\nincorporation\tjoy\t0\nincorporation\tnegative\t0\nincorporation\tpositive\t0\nincorporation\tsadness\t0\nincorporation\tsurprise\t0\nincorporation\ttrust\t0\nincorrect\tanger\t0\nincorrect\tanticipation\t0\nincorrect\tdisgust\t0\nincorrect\tfear\t0\nincorrect\tjoy\t0\nincorrect\tnegative\t1\nincorrect\tpositive\t0\nincorrect\tsadness\t0\nincorrect\tsurprise\t0\nincorrect\ttrust\t0\nincrease\tanger\t0\nincrease\tanticipation\t0\nincrease\tdisgust\t0\nincrease\tfear\t0\nincrease\tjoy\t0\nincrease\tnegative\t0\nincrease\tpositive\t1\nincrease\tsadness\t0\nincrease\tsurprise\t0\nincrease\ttrust\t0\nincreased\tanger\t0\nincreased\tanticipation\t0\nincreased\tdisgust\t0\nincreased\tfear\t0\nincreased\tjoy\t0\nincreased\tnegative\t0\nincreased\tpositive\t0\nincreased\tsadness\t0\nincreased\tsurprise\t0\nincreased\ttrust\t0\nincredulous\tanger\t1\nincredulous\tanticipation\t0\nincredulous\tdisgust\t1\nincredulous\tfear\t0\nincredulous\tjoy\t0\nincredulous\tnegative\t1\nincredulous\tpositive\t0\nincredulous\tsadness\t0\nincredulous\tsurprise\t0\nincredulous\ttrust\t0\nincrement\tanger\t0\nincrement\tanticipation\t0\nincrement\tdisgust\t0\nincrement\tfear\t0\nincrement\tjoy\t0\nincrement\tnegative\t0\nincrement\tpositive\t0\nincrement\tsadness\t0\nincrement\tsurprise\t0\nincrement\ttrust\t0\nincrimination\tanger\t0\nincrimination\tanticipation\t0\nincrimination\tdisgust\t0\nincrimination\tfear\t1\nincrimination\tjoy\t0\nincrimination\tnegative\t1\nincrimination\tpositive\t0\nincrimination\tsadness\t1\nincrimination\tsurprise\t0\nincrimination\ttrust\t0\nincubation\tanger\t0\nincubation\tanticipation\t0\nincubation\tdisgust\t0\nincubation\tfear\t0\nincubation\tjoy\t0\nincubation\tnegative\t0\nincubation\tpositive\t0\nincubation\tsadness\t0\nincubation\tsurprise\t0\nincubation\ttrust\t0\nincubus\tanger\t0\nincubus\tanticipation\t0\nincubus\tdisgust\t1\nincubus\tfear\t1\nincubus\tjoy\t0\nincubus\tnegative\t1\nincubus\tpositive\t0\nincubus\tsadness\t0\nincubus\tsurprise\t0\nincubus\ttrust\t0\nincur\tanger\t0\nincur\tanticipation\t0\nincur\tdisgust\t0\nincur\tfear\t0\nincur\tjoy\t0\nincur\tnegative\t1\nincur\tpositive\t0\nincur\tsadness\t0\nincur\tsurprise\t0\nincur\ttrust\t0\nincurable\tanger\t1\nincurable\tanticipation\t0\nincurable\tdisgust\t1\nincurable\tfear\t1\nincurable\tjoy\t0\nincurable\tnegative\t1\nincurable\tpositive\t0\nincurable\tsadness\t1\nincurable\tsurprise\t0\nincurable\ttrust\t0\nincursion\tanger\t0\nincursion\tanticipation\t0\nincursion\tdisgust\t0\nincursion\tfear\t1\nincursion\tjoy\t0\nincursion\tnegative\t1\nincursion\tpositive\t0\nincursion\tsadness\t0\nincursion\tsurprise\t0\nincursion\ttrust\t0\nindebted\tanger\t0\nindebted\tanticipation\t0\nindebted\tdisgust\t0\nindebted\tfear\t0\nindebted\tjoy\t0\nindebted\tnegative\t0\nindebted\tpositive\t0\nindebted\tsadness\t0\nindebted\tsurprise\t0\nindebted\ttrust\t0\nindecency\tanger\t1\nindecency\tanticipation\t0\nindecency\tdisgust\t1\nindecency\tfear\t0\nindecency\tjoy\t0\nindecency\tnegative\t0\nindecency\tpositive\t0\nindecency\tsadness\t0\nindecency\tsurprise\t0\nindecency\ttrust\t0\nindecent\tanger\t0\nindecent\tanticipation\t0\nindecent\tdisgust\t1\nindecent\tfear\t0\nindecent\tjoy\t0\nindecent\tnegative\t1\nindecent\tpositive\t0\nindecent\tsadness\t0\nindecent\tsurprise\t0\nindecent\ttrust\t0\nindecision\tanger\t0\nindecision\tanticipation\t0\nindecision\tdisgust\t0\nindecision\tfear\t0\nindecision\tjoy\t0\nindecision\tnegative\t1\nindecision\tpositive\t0\nindecision\tsadness\t0\nindecision\tsurprise\t0\nindecision\ttrust\t0\nindecisive\tanger\t0\nindecisive\tanticipation\t0\nindecisive\tdisgust\t0\nindecisive\tfear\t0\nindecisive\tjoy\t0\nindecisive\tnegative\t1\nindecisive\tpositive\t0\nindecisive\tsadness\t0\nindecisive\tsurprise\t0\nindecisive\ttrust\t0\nindefensible\tanger\t0\nindefensible\tanticipation\t0\nindefensible\tdisgust\t0\nindefensible\tfear\t1\nindefensible\tjoy\t0\nindefensible\tnegative\t1\nindefensible\tpositive\t0\nindefensible\tsadness\t0\nindefensible\tsurprise\t0\nindefensible\ttrust\t0\nindelible\tanger\t0\nindelible\tanticipation\t0\nindelible\tdisgust\t0\nindelible\tfear\t0\nindelible\tjoy\t0\nindelible\tnegative\t0\nindelible\tpositive\t1\nindelible\tsadness\t0\nindelible\tsurprise\t0\nindelible\ttrust\t1\nindemnification\tanger\t0\nindemnification\tanticipation\t0\nindemnification\tdisgust\t0\nindemnification\tfear\t0\nindemnification\tjoy\t0\nindemnification\tnegative\t0\nindemnification\tpositive\t0\nindemnification\tsadness\t0\nindemnification\tsurprise\t0\nindemnification\ttrust\t0\nindemnify\tanger\t0\nindemnify\tanticipation\t0\nindemnify\tdisgust\t0\nindemnify\tfear\t0\nindemnify\tjoy\t0\nindemnify\tnegative\t1\nindemnify\tpositive\t0\nindemnify\tsadness\t0\nindemnify\tsurprise\t0\nindemnify\ttrust\t0\nindemnity\tanger\t0\nindemnity\tanticipation\t0\nindemnity\tdisgust\t0\nindemnity\tfear\t0\nindemnity\tjoy\t0\nindemnity\tnegative\t0\nindemnity\tpositive\t1\nindemnity\tsadness\t0\nindemnity\tsurprise\t0\nindemnity\ttrust\t1\nindent\tanger\t0\nindent\tanticipation\t0\nindent\tdisgust\t0\nindent\tfear\t0\nindent\tjoy\t0\nindent\tnegative\t0\nindent\tpositive\t0\nindent\tsadness\t0\nindent\tsurprise\t0\nindent\ttrust\t1\nindentation\tanger\t0\nindentation\tanticipation\t0\nindentation\tdisgust\t0\nindentation\tfear\t0\nindentation\tjoy\t0\nindentation\tnegative\t0\nindentation\tpositive\t0\nindentation\tsadness\t0\nindentation\tsurprise\t0\nindentation\ttrust\t0\nindenture\tanger\t1\nindenture\tanticipation\t0\nindenture\tdisgust\t0\nindenture\tfear\t0\nindenture\tjoy\t0\nindenture\tnegative\t1\nindenture\tpositive\t0\nindenture\tsadness\t0\nindenture\tsurprise\t0\nindenture\ttrust\t0\nindependence\tanger\t0\nindependence\tanticipation\t1\nindependence\tdisgust\t0\nindependence\tfear\t0\nindependence\tjoy\t1\nindependence\tnegative\t0\nindependence\tpositive\t1\nindependence\tsadness\t0\nindependence\tsurprise\t1\nindependence\ttrust\t1\nindependent\tanger\t0\nindependent\tanticipation\t0\nindependent\tdisgust\t0\nindependent\tfear\t0\nindependent\tjoy\t0\nindependent\tnegative\t0\nindependent\tpositive\t0\nindependent\tsadness\t0\nindependent\tsurprise\t0\nindependent\ttrust\t0\nindescribable\tanger\t0\nindescribable\tanticipation\t0\nindescribable\tdisgust\t0\nindescribable\tfear\t0\nindescribable\tjoy\t0\nindescribable\tnegative\t0\nindescribable\tpositive\t0\nindescribable\tsadness\t0\nindescribable\tsurprise\t0\nindescribable\ttrust\t0\nindestructible\tanger\t0\nindestructible\tanticipation\t0\nindestructible\tdisgust\t0\nindestructible\tfear\t0\nindestructible\tjoy\t0\nindestructible\tnegative\t0\nindestructible\tpositive\t1\nindestructible\tsadness\t0\nindestructible\tsurprise\t0\nindestructible\ttrust\t1\nindeterminate\tanger\t0\nindeterminate\tanticipation\t0\nindeterminate\tdisgust\t0\nindeterminate\tfear\t0\nindeterminate\tjoy\t0\nindeterminate\tnegative\t1\nindeterminate\tpositive\t0\nindeterminate\tsadness\t0\nindeterminate\tsurprise\t0\nindeterminate\ttrust\t0\nindex\tanger\t0\nindex\tanticipation\t0\nindex\tdisgust\t0\nindex\tfear\t0\nindex\tjoy\t0\nindex\tnegative\t0\nindex\tpositive\t0\nindex\tsadness\t0\nindex\tsurprise\t0\nindex\ttrust\t0\nindicating\tanger\t0\nindicating\tanticipation\t0\nindicating\tdisgust\t0\nindicating\tfear\t0\nindicating\tjoy\t0\nindicating\tnegative\t0\nindicating\tpositive\t0\nindicating\tsadness\t0\nindicating\tsurprise\t0\nindicating\ttrust\t0\nindication\tanger\t0\nindication\tanticipation\t0\nindication\tdisgust\t0\nindication\tfear\t0\nindication\tjoy\t0\nindication\tnegative\t0\nindication\tpositive\t0\nindication\tsadness\t0\nindication\tsurprise\t0\nindication\ttrust\t0\nindicative\tanger\t0\nindicative\tanticipation\t0\nindicative\tdisgust\t0\nindicative\tfear\t0\nindicative\tjoy\t0\nindicative\tnegative\t0\nindicative\tpositive\t0\nindicative\tsadness\t0\nindicative\tsurprise\t0\nindicative\ttrust\t0\nindicator\tanger\t0\nindicator\tanticipation\t0\nindicator\tdisgust\t0\nindicator\tfear\t0\nindicator\tjoy\t0\nindicator\tnegative\t0\nindicator\tpositive\t0\nindicator\tsadness\t0\nindicator\tsurprise\t0\nindicator\ttrust\t0\nindice\tanger\t0\nindice\tanticipation\t0\nindice\tdisgust\t0\nindice\tfear\t0\nindice\tjoy\t0\nindice\tnegative\t0\nindice\tpositive\t0\nindice\tsadness\t0\nindice\tsurprise\t0\nindice\ttrust\t0\nindict\tanger\t1\nindict\tanticipation\t0\nindict\tdisgust\t0\nindict\tfear\t1\nindict\tjoy\t0\nindict\tnegative\t1\nindict\tpositive\t0\nindict\tsadness\t0\nindict\tsurprise\t0\nindict\ttrust\t0\nindictment\tanger\t0\nindictment\tanticipation\t0\nindictment\tdisgust\t0\nindictment\tfear\t1\nindictment\tjoy\t0\nindictment\tnegative\t1\nindictment\tpositive\t0\nindictment\tsadness\t0\nindictment\tsurprise\t0\nindictment\ttrust\t0\nindifference\tanger\t1\nindifference\tanticipation\t0\nindifference\tdisgust\t1\nindifference\tfear\t1\nindifference\tjoy\t0\nindifference\tnegative\t1\nindifference\tpositive\t0\nindifference\tsadness\t1\nindifference\tsurprise\t0\nindifference\ttrust\t0\nindigenous\tanger\t0\nindigenous\tanticipation\t0\nindigenous\tdisgust\t0\nindigenous\tfear\t0\nindigenous\tjoy\t0\nindigenous\tnegative\t0\nindigenous\tpositive\t0\nindigenous\tsadness\t0\nindigenous\tsurprise\t0\nindigenous\ttrust\t0\nindigent\tanger\t0\nindigent\tanticipation\t0\nindigent\tdisgust\t0\nindigent\tfear\t0\nindigent\tjoy\t0\nindigent\tnegative\t1\nindigent\tpositive\t0\nindigent\tsadness\t1\nindigent\tsurprise\t0\nindigent\ttrust\t0\nindigestion\tanger\t0\nindigestion\tanticipation\t0\nindigestion\tdisgust\t0\nindigestion\tfear\t0\nindigestion\tjoy\t0\nindigestion\tnegative\t0\nindigestion\tpositive\t0\nindigestion\tsadness\t0\nindigestion\tsurprise\t0\nindigestion\ttrust\t0\nindignant\tanger\t1\nindignant\tanticipation\t0\nindignant\tdisgust\t0\nindignant\tfear\t0\nindignant\tjoy\t0\nindignant\tnegative\t1\nindignant\tpositive\t0\nindignant\tsadness\t0\nindignant\tsurprise\t0\nindignant\ttrust\t0\nindignation\tanger\t1\nindignation\tanticipation\t0\nindignation\tdisgust\t1\nindignation\tfear\t0\nindignation\tjoy\t0\nindignation\tnegative\t1\nindignation\tpositive\t0\nindignation\tsadness\t0\nindignation\tsurprise\t0\nindignation\ttrust\t0\nindigo\tanger\t0\nindigo\tanticipation\t0\nindigo\tdisgust\t0\nindigo\tfear\t0\nindigo\tjoy\t0\nindigo\tnegative\t0\nindigo\tpositive\t0\nindigo\tsadness\t0\nindigo\tsurprise\t0\nindigo\ttrust\t0\nindirect\tanger\t0\nindirect\tanticipation\t0\nindirect\tdisgust\t0\nindirect\tfear\t0\nindirect\tjoy\t0\nindirect\tnegative\t0\nindirect\tpositive\t0\nindirect\tsadness\t0\nindirect\tsurprise\t0\nindirect\ttrust\t0\nindispensable\tanger\t0\nindispensable\tanticipation\t0\nindispensable\tdisgust\t0\nindispensable\tfear\t0\nindispensable\tjoy\t0\nindispensable\tnegative\t0\nindispensable\tpositive\t0\nindispensable\tsadness\t0\nindispensable\tsurprise\t0\nindispensable\ttrust\t0\nindistinct\tanger\t0\nindistinct\tanticipation\t0\nindistinct\tdisgust\t0\nindistinct\tfear\t0\nindistinct\tjoy\t0\nindistinct\tnegative\t1\nindistinct\tpositive\t0\nindistinct\tsadness\t0\nindistinct\tsurprise\t0\nindistinct\ttrust\t0\nindistinguishable\tanger\t0\nindistinguishable\tanticipation\t0\nindistinguishable\tdisgust\t0\nindistinguishable\tfear\t0\nindistinguishable\tjoy\t0\nindistinguishable\tnegative\t0\nindistinguishable\tpositive\t0\nindistinguishable\tsadness\t0\nindistinguishable\tsurprise\t0\nindistinguishable\ttrust\t0\nindividuality\tanger\t0\nindividuality\tanticipation\t0\nindividuality\tdisgust\t0\nindividuality\tfear\t0\nindividuality\tjoy\t0\nindividuality\tnegative\t0\nindividuality\tpositive\t1\nindividuality\tsadness\t0\nindividuality\tsurprise\t0\nindividuality\ttrust\t0\nindivisible\tanger\t0\nindivisible\tanticipation\t0\nindivisible\tdisgust\t0\nindivisible\tfear\t0\nindivisible\tjoy\t0\nindivisible\tnegative\t0\nindivisible\tpositive\t0\nindivisible\tsadness\t0\nindivisible\tsurprise\t0\nindivisible\ttrust\t1\nindoctrination\tanger\t1\nindoctrination\tanticipation\t0\nindoctrination\tdisgust\t0\nindoctrination\tfear\t1\nindoctrination\tjoy\t0\nindoctrination\tnegative\t1\nindoctrination\tpositive\t0\nindoctrination\tsadness\t0\nindoctrination\tsurprise\t0\nindoctrination\ttrust\t0\nindolent\tanger\t0\nindolent\tanticipation\t0\nindolent\tdisgust\t0\nindolent\tfear\t0\nindolent\tjoy\t0\nindolent\tnegative\t1\nindolent\tpositive\t0\nindolent\tsadness\t0\nindolent\tsurprise\t0\nindolent\ttrust\t0\nindomitable\tanger\t0\nindomitable\tanticipation\t0\nindomitable\tdisgust\t0\nindomitable\tfear\t1\nindomitable\tjoy\t0\nindomitable\tnegative\t0\nindomitable\tpositive\t1\nindomitable\tsadness\t0\nindomitable\tsurprise\t0\nindomitable\ttrust\t0\nindoor\tanger\t0\nindoor\tanticipation\t0\nindoor\tdisgust\t0\nindoor\tfear\t0\nindoor\tjoy\t0\nindoor\tnegative\t0\nindoor\tpositive\t0\nindoor\tsadness\t0\nindoor\tsurprise\t0\nindoor\ttrust\t0\ninduce\tanger\t0\ninduce\tanticipation\t0\ninduce\tdisgust\t0\ninduce\tfear\t0\ninduce\tjoy\t0\ninduce\tnegative\t0\ninduce\tpositive\t0\ninduce\tsadness\t0\ninduce\tsurprise\t0\ninduce\ttrust\t0\ninduced\tanger\t0\ninduced\tanticipation\t0\ninduced\tdisgust\t0\ninduced\tfear\t0\ninduced\tjoy\t0\ninduced\tnegative\t0\ninduced\tpositive\t0\ninduced\tsadness\t0\ninduced\tsurprise\t0\ninduced\ttrust\t0\ninducement\tanger\t0\ninducement\tanticipation\t0\ninducement\tdisgust\t0\ninducement\tfear\t0\ninducement\tjoy\t0\ninducement\tnegative\t0\ninducement\tpositive\t0\ninducement\tsadness\t0\ninducement\tsurprise\t0\ninducement\ttrust\t0\ninduction\tanger\t0\ninduction\tanticipation\t0\ninduction\tdisgust\t0\ninduction\tfear\t0\ninduction\tjoy\t0\ninduction\tnegative\t0\ninduction\tpositive\t0\ninduction\tsadness\t0\ninduction\tsurprise\t0\ninduction\ttrust\t0\nindulge\tanger\t0\nindulge\tanticipation\t0\nindulge\tdisgust\t0\nindulge\tfear\t0\nindulge\tjoy\t0\nindulge\tnegative\t0\nindulge\tpositive\t0\nindulge\tsadness\t0\nindulge\tsurprise\t0\nindulge\ttrust\t0\nindulgence\tanger\t0\nindulgence\tanticipation\t0\nindulgence\tdisgust\t0\nindulgence\tfear\t0\nindulgence\tjoy\t0\nindulgence\tnegative\t0\nindulgence\tpositive\t0\nindulgence\tsadness\t0\nindulgence\tsurprise\t0\nindulgence\ttrust\t0\nindulgent\tanger\t0\nindulgent\tanticipation\t0\nindulgent\tdisgust\t0\nindulgent\tfear\t0\nindulgent\tjoy\t0\nindulgent\tnegative\t0\nindulgent\tpositive\t0\nindulgent\tsadness\t0\nindulgent\tsurprise\t0\nindulgent\ttrust\t0\nindustrious\tanger\t0\nindustrious\tanticipation\t0\nindustrious\tdisgust\t0\nindustrious\tfear\t0\nindustrious\tjoy\t0\nindustrious\tnegative\t0\nindustrious\tpositive\t0\nindustrious\tsadness\t0\nindustrious\tsurprise\t0\nindustrious\ttrust\t0\nindustry\tanger\t0\nindustry\tanticipation\t0\nindustry\tdisgust\t0\nindustry\tfear\t0\nindustry\tjoy\t0\nindustry\tnegative\t0\nindustry\tpositive\t0\nindustry\tsadness\t0\nindustry\tsurprise\t0\nindustry\ttrust\t0\nineffable\tanger\t0\nineffable\tanticipation\t0\nineffable\tdisgust\t0\nineffable\tfear\t0\nineffable\tjoy\t0\nineffable\tnegative\t0\nineffable\tpositive\t1\nineffable\tsadness\t0\nineffable\tsurprise\t0\nineffable\ttrust\t0\nineffective\tanger\t0\nineffective\tanticipation\t0\nineffective\tdisgust\t0\nineffective\tfear\t0\nineffective\tjoy\t0\nineffective\tnegative\t1\nineffective\tpositive\t0\nineffective\tsadness\t0\nineffective\tsurprise\t0\nineffective\ttrust\t0\nineffectual\tanger\t0\nineffectual\tanticipation\t0\nineffectual\tdisgust\t1\nineffectual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stantaneously\tdisgust\t0\ninstantaneously\tfear\t0\ninstantaneously\tjoy\t0\ninstantaneously\tnegative\t0\ninstantaneously\tpositive\t0\ninstantaneously\tsadness\t0\ninstantaneously\tsurprise\t0\ninstantaneously\ttrust\t0\ninstigate\tanger\t0\ninstigate\tanticipation\t0\ninstigate\tdisgust\t0\ninstigate\tfear\t0\ninstigate\tjoy\t0\ninstigate\tnegative\t1\ninstigate\tpositive\t0\ninstigate\tsadness\t0\ninstigate\tsurprise\t0\ninstigate\ttrust\t0\ninstigation\tanger\t0\ninstigation\tanticipation\t0\ninstigation\tdisgust\t0\ninstigation\tfear\t0\ninstigation\tjoy\t0\ninstigation\tnegative\t1\ninstigation\tpositive\t0\ninstigation\tsadness\t0\ninstigation\tsurprise\t0\ninstigation\ttrust\t0\ninstill\tanger\t0\ninstill\tanticipation\t0\ninstill\tdisgust\t0\ninstill\tfear\t0\ninstill\tjoy\t0\ninstill\tnegative\t0\ninstill\tpositive\t0\ninstill\tsadness\t0\ninstill\tsurprise\t0\ninstill\ttrust\t0\ninstinct\tanger\t0\ninstinct\tanticipation\t0\ninstinct\tdisgust\t0\ninstinct\tfear\t0\ninstinct\tjoy\t0\ninstinct\tnegative\t0\ninstinct\tpositive\t0\ninstinct\tsadness\t0\ninstinct\tsurprise\t0\ninstinct\ttrust\t0\ninstinctive\tanger\t1\ninstinctive\tanticipation\t0\ninstinctive\tdisgust\t1\ninstinctive\tfear\t1\ninstinctive\tjoy\t0\ninstinctive\tnegative\t0\ninstinctive\tpositive\t1\ninstinctive\tsadness\t0\ninstinctive\tsurprise\t0\ninstinctive\ttrust\t0\ninstitute\tanger\t0\ninstitute\tanticipation\t0\ninstitute\tdisgust\t0\ninstitute\tfear\t0\ninstitute\tjoy\t0\ninstitute\tnegative\t0\ninstitute\tpositive\t0\ninstitute\tsadness\t0\ninstitute\tsurprise\t0\ninstitute\ttrust\t1\ninstitution\tanger\t0\ninstitution\tanticipation\t0\ninstitution\tdisgust\t0\ninstitution\tfear\t0\ninstitution\tjoy\t0\ninstitution\tnegative\t0\ninstitution\tpositive\t0\ninstitution\tsadness\t0\ninstitution\tsurprise\t0\ninstitution\ttrust\t0\ninstruct\tanger\t0\ninstruct\tanticipation\t0\ninstruct\tdisgust\t0\ninstruct\tfear\t0\ninstruct\tjoy\t0\ninstruct\tnegative\t0\ninstruct\tpositive\t1\ninstruct\tsadness\t0\ninstruct\tsurprise\t0\ninstruct\ttrust\t1\ninstructed\tanger\t0\ninstructed\tanticipation\t0\ninstructed\tdisgust\t0\ninstructed\tfear\t0\ninstructed\tjoy\t0\ninstructed\tnegative\t0\ninstructed\tpositive\t0\ninstructed\tsadness\t0\ninstructed\tsurprise\t0\ninstructed\ttrust\t0\ninstruction\tanger\t0\ninstruction\tanticipation\t0\ninstruction\tdisgust\t0\ninstruction\tfear\t0\ninstruction\tjoy\t0\ninstruction\tnegative\t0\ninstruction\tpositive\t1\ninstruction\tsadness\t0\ninstruction\tsurprise\t0\ninstruction\ttrust\t1\ninstructional\tanger\t0\ninstructional\tanticipation\t0\ninstructional\tdisgust\t0\ninstructional\tfear\t0\ninstructional\tjoy\t0\ninstructional\tnegative\t0\ninstructional\tpositive\t0\ninstructional\tsadness\t0\ninstructional\tsurprise\t0\ninstructional\ttrust\t0\ninstructions\tanger\t0\ninstructions\tanticipation\t1\ninstructions\tdisgust\t0\ninstructions\tfear\t0\ninstructions\tjoy\t0\ninstructions\tnegative\t0\ninstructions\tpositive\t0\ninstructions\tsadness\t0\ninstructions\tsurprise\t0\ninstructions\ttrust\t1\ninstructive\tanger\t0\ninstructive\tanticipation\t0\ninstructive\tdisgust\t0\ninstructive\tfear\t0\ninstructive\tjoy\t0\ninstructive\tnegative\t0\ninstructive\tpositive\t0\ninstructive\tsadness\t0\ninstructive\tsurprise\t0\ninstructive\ttrust\t0\ninstructor\tanger\t0\ninstructor\tanticipation\t1\ninstructor\tdisgust\t0\ninstructor\tfear\t0\ninstructor\tjoy\t0\ninstructor\tnegative\t0\ninstructor\tpositive\t1\ninstructor\tsadness\t0\ninstructor\tsurprise\t0\ninstructor\ttrust\t1\ninstrument\tanger\t0\ninstrument\tanticipation\t0\ninstrument\tdisgust\t0\ninstrument\tfear\t0\ninstrument\tjoy\t0\ninstrument\tnegative\t0\ninstrument\tpositive\t0\ninstrument\tsadness\t0\ninstrument\tsurprise\t0\ninstrument\ttrust\t0\ninstrumental\tanger\t0\ninstrumental\tanticipation\t0\ninstrumental\tdisgust\t0\ninstrumental\tfear\t0\ninstrumental\tjoy\t0\ninstrumental\tnegative\t0\ninstrumental\tpositive\t1\ninstrumental\tsadness\t0\ninstrumental\tsurprise\t0\ninstrumental\ttrust\t0\ninstrumentalist\tanger\t0\ninstrumentalist\tanticipation\t0\ninstrumentalist\tdisgust\t0\ninstrumentalist\tfear\t0\ninstrumentalist\tjoy\t0\ninstrumentalist\tnegative\t0\ninstrumentalist\tpositive\t0\ninstrumentalist\tsadness\t0\ninstrumentalist\tsurprise\t0\ninstrumentalist\ttrust\t0\ninstrumentality\tanger\t0\ninstrumentality\tanticipation\t0\ninstrumentality\tdisgust\t0\ninstrumentality\tfear\t0\ninstrumentality\tjoy\t0\ninstrumentality\tnegative\t0\ninstrumentality\tpositive\t0\ninstrumentality\tsadness\t0\ninstrumentality\tsurprise\t0\ninstrumentality\ttrust\t0\ninsufficiency\tanger\t1\ninsufficiency\tanticipation\t0\ninsufficiency\tdisgust\t0\ninsufficiency\tfear\t0\ninsufficiency\tjoy\t0\ninsufficiency\tnegative\t1\ninsufficiency\tpositive\t0\ninsufficiency\tsadness\t0\ninsufficiency\tsurprise\t0\ninsufficiency\ttrust\t0\ninsufficient\tanger\t0\ninsufficient\tanticipation\t0\ninsufficient\tdisgust\t0\ninsufficient\tfear\t0\ninsufficient\tjoy\t0\ninsufficient\tnegative\t1\ninsufficient\tpositive\t0\ninsufficient\tsadness\t0\ninsufficient\tsurprise\t0\ninsufficient\ttrust\t0\ninsufficiently\tanger\t0\ninsufficiently\tanticipation\t0\ninsufficiently\tdisgust\t0\ninsufficiently\tfear\t0\ninsufficiently\tjoy\t0\ninsufficiently\tnegative\t1\ninsufficiently\tpositive\t0\ninsufficiently\tsadness\t0\ninsufficiently\tsurprise\t0\ninsufficiently\ttrust\t0\ninsular\tanger\t0\ninsular\tanticipation\t0\ninsular\tdisgust\t0\ninsular\tfear\t0\ninsular\tjoy\t0\ninsular\tnegative\t0\ninsular\tpositive\t0\ninsular\tsadness\t0\ninsular\tsurprise\t0\ninsular\ttrust\t0\ninsulate\tanger\t0\ninsulate\tanticipation\t0\ninsulate\tdisgust\t0\ninsulate\tfear\t0\ninsulate\tjoy\t0\ninsulate\tnegative\t0\ninsulate\tpositive\t0\ninsulate\tsadness\t0\ninsulate\tsurprise\t0\ninsulate\ttrust\t0\ninsulation\tanger\t0\ninsulation\tanticipation\t0\ninsulation\tdisgust\t0\ninsulation\tfear\t0\ninsulation\tjoy\t0\ninsulation\tnegative\t0\ninsulation\tpositive\t0\ninsulation\tsadness\t0\ninsulation\tsurprise\t0\ninsulation\ttrust\t1\ninsult\tanger\t1\ninsult\tanticipation\t0\ninsult\tdisgust\t1\ninsult\tfear\t0\ninsult\tjoy\t0\ninsult\tnegative\t1\ninsult\tpositive\t0\ninsult\tsadness\t1\ninsult\tsurprise\t1\ninsult\ttrust\t0\ninsulting\tanger\t1\ninsulting\tanticipation\t0\ninsulting\tdisgust\t1\ninsulting\tfear\t1\ninsulting\tjoy\t0\ninsulting\tnegative\t1\ninsulting\tpositive\t0\ninsulting\tsadness\t1\ninsulting\tsurprise\t0\ninsulting\ttrust\t0\ninsurance\tanger\t0\ninsurance\tanticipation\t0\ninsurance\tdisgust\t0\ninsurance\tfear\t0\ninsurance\tjoy\t0\ninsurance\tnegative\t0\ninsurance\tpositive\t0\ninsurance\tsadness\t0\ninsurance\tsurprise\t0\ninsurance\ttrust\t0\ninsure\tanger\t0\ninsure\tanticipation\t0\ninsure\tdisgust\t0\ninsure\tfear\t0\ninsure\tjoy\t0\ninsure\tnegative\t0\ninsure\tpositive\t1\ninsure\tsadness\t0\ninsure\tsurprise\t0\ninsure\ttrust\t1\ninsurgent\tanger\t0\ninsurgent\tanticipation\t0\ninsurgent\tdisgust\t0\ninsurgent\tfear\t0\ninsurgent\tjoy\t0\ninsurgent\tnegative\t1\ninsurgent\tpositive\t0\ninsurgent\tsadness\t0\ninsurgent\tsurprise\t0\ninsurgent\ttrust\t0\ninsurmountable\tanger\t0\ninsurmountable\tanticipation\t0\ninsurmountable\tdisgust\t0\ninsurmountable\tfear\t1\ninsurmountable\tjoy\t0\ninsurmountable\tnegative\t1\ninsurmountable\tpositive\t0\ninsurmountable\tsadness\t1\ninsurmountable\tsurprise\t0\ninsurmountable\ttrust\t0\ninsurrection\tanger\t1\ninsurrection\tanticipation\t0\ninsurrection\tdisgust\t0\ninsurrection\tfear\t0\ninsurrection\tjoy\t0\ninsurrection\tnegative\t1\ninsurrection\tpositive\t0\ninsurrection\tsadness\t0\ninsurrection\tsurprise\t0\ninsurrection\ttrust\t0\nintact\tanger\t0\nintact\tanticipation\t0\nintact\tdisgust\t0\nintact\tfear\t0\nintact\tjoy\t0\nintact\tnegative\t0\nintact\tpositive\t1\nintact\tsadness\t0\nintact\tsurprise\t0\nintact\ttrust\t1\nintangible\tanger\t0\nintangible\tanticipation\t0\nintangible\tdisgust\t0\nintangible\tfear\t0\nintangible\tjoy\t0\nintangible\tnegative\t0\nintangible\tpositive\t0\nintangible\tsadness\t0\nintangible\tsurprise\t0\nintangible\ttrust\t0\ninteger\tanger\t0\ninteger\tanticipation\t0\ninteger\tdisgust\t0\ninteger\tfear\t0\ninteger\tjoy\t0\ninteger\tnegative\t0\ninteger\tpositive\t0\ninteger\tsadness\t0\ninteger\tsurprise\t0\ninteger\ttrust\t0\nintegral\tanger\t0\nintegral\tanticipation\t0\nintegral\tdisgust\t0\nintegral\tfear\t0\nintegral\tjoy\t0\nintegral\tnegative\t0\nintegral\tpositive\t0\nintegral\tsadness\t0\nintegral\tsurprise\t0\nintegral\ttrust\t0\nintegrate\tanger\t0\nintegrate\tanticipation\t0\nintegrate\tdisgust\t0\nintegrate\tfear\t0\nintegrate\tjoy\t0\nintegrate\tnegative\t0\nintegrate\tpositive\t0\nintegrate\tsadness\t0\nintegrate\tsurprise\t0\nintegrate\ttrust\t0\nintegration\tanger\t0\nintegration\tanticipation\t0\nintegration\tdisgust\t0\nintegration\tfear\t0\nintegration\tjoy\t0\nintegration\tnegative\t0\nintegration\tpositive\t0\nintegration\tsadness\t0\nintegration\tsurprise\t0\nintegration\ttrust\t0\nintegrity\tanger\t0\nintegrity\tanticipation\t0\nintegrity\tdisgust\t0\nintegrity\tfear\t0\nintegrity\tjoy\t0\nintegrity\tnegative\t0\nintegrity\tpositive\t1\nintegrity\tsadness\t0\nintegrity\tsurprise\t0\nintegrity\ttrust\t1\nintellect\tanger\t0\nintellect\tanticipation\t0\nintellect\tdisgust\t0\nintellect\tfear\t0\nintellect\tjoy\t0\nintellect\tnegative\t0\nintellect\tpositive\t1\nintellect\tsadness\t0\nintellect\tsurprise\t0\nintellect\ttrust\t0\nintellectual\tanger\t0\nintellectual\tanticipation\t0\nintellectual\tdisgust\t0\nintellectual\tfear\t0\nintellectual\tjoy\t0\nintellectual\tnegative\t0\nintellectual\tpositive\t1\nintellectual\tsadness\t0\nintellectual\tsurprise\t0\nintellectual\ttrust\t0\nintelligence\tanger\t0\nintelligence\tanticipation\t0\nintelligence\tdisgust\t0\nintelligence\tfear\t1\nintelligence\tjoy\t1\nintelligence\tnegative\t0\nintelligence\tpositive\t1\nintelligence\tsadness\t0\nintelligence\tsurprise\t0\nintelligence\ttrust\t1\nintelligent\tanger\t0\nintelligent\tanticipation\t0\nintelligent\tdisgust\t0\nintelligent\tfear\t0\nintelligent\tjoy\t0\nintelligent\tnegative\t0\nintelligent\tpositive\t1\nintelligent\tsadness\t0\nintelligent\tsurprise\t0\nintelligent\ttrust\t1\nintelligibility\tanger\t0\nintelligibility\tanticipation\t0\nintelligibility\tdisgust\t0\nintelligibility\tfear\t0\nintelligibility\tjoy\t0\nintelligibility\tnegative\t0\nintelligibility\tpositive\t0\nintelligibility\tsadness\t0\nintelligibility\tsurprise\t0\nintelligibility\ttrust\t0\nintelligible\tanger\t0\nintelligible\tanticipation\t0\nintelligible\tdisgust\t0\nintelligible\tfear\t0\nintelligible\tjoy\t0\nintelligible\tnegative\t0\nintelligible\tpositive\t0\nintelligible\tsadness\t0\nintelligible\tsurprise\t0\nintelligible\ttrust\t0\nintend\tanger\t0\nintend\tanticipation\t0\nintend\tdisgust\t0\nintend\tfear\t0\nintend\tjoy\t0\nintend\tnegative\t0\nintend\tpositive\t0\nintend\tsadness\t0\nintend\tsurprise\t0\nintend\ttrust\t1\nintended\tanger\t0\nintended\tanticipation\t1\nintended\tdisgust\t0\nintended\tfear\t0\nintended\tjoy\t0\nintended\tnegative\t0\nintended\tpositive\t1\nintended\tsadness\t0\nintended\tsurprise\t0\nintended\ttrust\t0\nintending\tanger\t0\nintending\tanticipation\t0\nintending\tdisgust\t0\nintending\tfear\t0\nintending\tjoy\t0\nintending\tnegative\t0\nintending\tpositive\t0\nintending\tsadness\t0\nintending\tsurprise\t0\nintending\ttrust\t0\nintense\tanger\t1\nintense\tanticipation\t0\nintense\tdisgust\t1\nintense\tfear\t1\nintense\tjoy\t1\nintense\tnegative\t1\nintense\tpositive\t1\nintense\tsadness\t0\nintense\tsurprise\t1\nintense\ttrust\t1\nintensely\tanger\t0\nintensely\tanticipation\t0\nintensely\tdisgust\t0\nintensely\tfear\t0\nintensely\tjoy\t0\nintensely\tnegative\t0\nintensely\tpositive\t0\nintensely\tsadness\t0\nintensely\tsurprise\t0\nintensely\ttrust\t0\nintensify\tanger\t0\nintensify\tanticipation\t0\nintensify\tdisgust\t0\nintensify\tfear\t0\nintensify\tjoy\t0\nintensify\tnegative\t0\nintensify\tpositive\t0\nintensify\tsadness\t0\nintensify\tsurprise\t0\nintensify\ttrust\t0\nintensity\tanger\t0\nintensity\tanticipation\t0\nintensity\tdisgust\t0\nintensity\tfear\t0\nintensity\tjoy\t0\nintensity\tnegative\t0\nintensity\tpositive\t0\nintensity\tsadness\t0\nintensity\tsurprise\t0\nintensity\ttrust\t0\nintent\tanger\t0\nintent\tanticipation\t0\nintent\tdisgust\t0\nintent\tfear\t0\nintent\tjoy\t0\nintent\tnegative\t0\nintent\tpositive\t0\nintent\tsadness\t0\nintent\tsurprise\t0\nintent\ttrust\t0\nintention\tanger\t0\nintention\tanticipation\t0\nintention\tdisgust\t0\nintention\tfear\t0\nintention\tjoy\t0\nintention\tnegative\t0\nintention\tpositive\t0\nintention\tsadness\t0\nintention\tsurprise\t0\nintention\ttrust\t0\nintentional\tanger\t0\nintentional\tanticipation\t0\nintentional\tdisgust\t0\nintentional\tfear\t0\nintentional\tjoy\t0\nintentional\tnegative\t0\nintentional\tpositive\t0\nintentional\tsadness\t0\nintentional\tsurprise\t0\nintentional\ttrust\t0\nintentionally\tanger\t0\nintentionally\tanticipation\t0\nintentionally\tdisgust\t0\nintentionally\tfear\t0\nintentionally\tjoy\t0\nintentionally\tnegative\t0\nintentionally\tpositive\t0\nintentionally\tsadness\t0\nintentionally\tsurprise\t0\nintentionally\ttrust\t0\ninter\tanger\t0\ninter\tanticipation\t0\ninter\tdisgust\t0\ninter\tfear\t0\ninter\tjoy\t0\ninter\tnegative\t1\ninter\tpositive\t0\ninter\tsadness\t1\ninter\tsurprise\t0\ninter\ttrust\t0\ninteraction\tanger\t0\ninteraction\tanticipation\t0\ninteraction\tdisgust\t0\ninteraction\tfear\t0\ninteraction\tjoy\t0\ninteraction\tnegative\t0\ninteraction\tpositive\t0\ninteraction\tsadness\t0\ninteraction\tsurprise\t0\ninteraction\ttrust\t0\nintercede\tanger\t0\nintercede\tanticipation\t0\nintercede\tdisgust\t0\nintercede\tfear\t1\nintercede\tjoy\t0\nintercede\tnegative\t0\nintercede\tpositive\t0\nintercede\tsadness\t1\nintercede\tsurprise\t0\nintercede\ttrust\t0\nintercept\tanger\t0\nintercept\tanticipation\t0\nintercept\tdisgust\t0\nintercept\tfear\t0\nintercept\tjoy\t0\nintercept\tnegative\t0\nintercept\tpositive\t0\nintercept\tsadness\t0\nintercept\tsurprise\t0\nintercept\ttrust\t0\ninterception\tanger\t0\ninterception\tanticipation\t0\ninterception\tdisgust\t0\ninterception\tfear\t0\ninterception\tjoy\t0\ninterception\tnegative\t0\ninterception\tpositive\t0\ninterception\tsadness\t0\ninterception\tsurprise\t0\ninterception\ttrust\t0\nintercession\tanger\t0\nintercession\tanticipation\t0\nintercession\tdisgust\t0\nintercession\tfear\t0\nintercession\tjoy\t0\nintercession\tnegative\t0\nintercession\tpositive\t0\nintercession\tsadness\t0\nintercession\tsurprise\t0\nintercession\ttrust\t1\ninterchange\tanger\t0\ninterchange\tanticipation\t0\ninterchange\tdisgust\t0\ninterchange\tfear\t0\ninterchange\tjoy\t0\ninterchange\tnegative\t0\ninterchange\tpositive\t0\ninterchange\tsadness\t0\ninterchange\tsurprise\t0\ninterchange\ttrust\t0\ninterchangeable\tanger\t0\ninterchangeable\tanticipation\t0\ninterchangeable\tdisgust\t0\ninterchangeable\tfear\t0\ninterchangeable\tjoy\t0\ninterchangeable\tnegative\t0\ninterchangeable\tpositive\t0\ninterchangeable\tsadness\t0\ninterchangeable\tsurprise\t0\ninterchangeable\ttrust\t0\ninterchanged\tanger\t0\ninterchanged\tanticipation\t0\ninterchanged\tdisgust\t0\ninterchanged\tfear\t0\ninterchanged\tjoy\t0\ninterchanged\tnegative\t0\ninterchanged\tpositive\t0\ninterchanged\tsadness\t0\ninterchanged\tsurprise\t0\ninterchanged\ttrust\t0\nintercom\tanger\t0\nintercom\tanticipation\t0\nintercom\tdisgust\t0\nintercom\tfear\t0\nintercom\tjoy\t0\nintercom\tnegative\t0\nintercom\tpositive\t0\nintercom\tsadness\t0\nintercom\tsurprise\t0\nintercom\ttrust\t0\nintercourse\tanger\t0\nintercourse\tanticipation\t0\nintercourse\tdisgust\t0\nintercourse\tfear\t0\nintercourse\tjoy\t0\nintercourse\tnegative\t0\nintercourse\tpositive\t1\nintercourse\tsadness\t0\nintercourse\tsurprise\t0\nintercourse\ttrust\t0\ninterdependence\tanger\t0\ninterdependence\tanticipation\t0\ninterdependence\tdisgust\t0\ninterdependence\tfear\t0\ninterdependence\tjoy\t0\ninterdependence\tnegative\t0\ninterdependence\tpositive\t0\ninterdependence\tsadness\t0\ninterdependence\tsurprise\t0\ninterdependence\ttrust\t0\ninterdependent\tanger\t0\ninterdependent\tanticipation\t0\ninterdependent\tdisgust\t0\ninterdependent\tfear\t0\ninterdependent\tjoy\t0\ninterdependent\tnegative\t0\ninterdependent\tpositive\t0\ninterdependent\tsadness\t0\ninterdependent\tsurprise\t0\ninterdependent\ttrust\t0\ninterdiction\tanger\t0\ninterdiction\tanticipation\t0\ninterdiction\tdisgust\t0\ninterdiction\tfear\t0\ninterdiction\tjoy\t0\ninterdiction\tnegative\t1\ninterdiction\tpositive\t0\ninterdiction\tsadness\t0\ninterdiction\tsurprise\t0\ninterdiction\ttrust\t0\ninterest\tanger\t0\ninterest\tanticipation\t0\ninterest\tdisgust\t0\ninterest\tfear\t0\ninterest\tjoy\t0\ninterest\tnegative\t0\ninterest\tpositive\t1\ninterest\tsadness\t0\ninterest\tsurprise\t0\ninterest\ttrust\t0\ninterested\tanger\t0\ninterested\tanticipation\t0\ninterested\tdisgust\t1\ninterested\tfear\t0\ninterested\tjoy\t0\ninterested\tnegative\t0\ninterested\tpositive\t1\ninterested\tsadness\t1\ninterested\tsurprise\t0\ninterested\ttrust\t0\ninteresting\tanger\t0\ninteresting\tanticipation\t0\ninteresting\tdisgust\t0\ninteresting\tfear\t0\ninteresting\tjoy\t0\ninteresting\tnegative\t0\ninteresting\tpositive\t1\ninteresting\tsadness\t0\ninteresting\tsurprise\t0\ninteresting\ttrust\t0\ninterference\tanger\t0\ninterference\tanticipation\t0\ninterference\tdisgust\t0\ninterference\tfear\t0\ninterference\tjoy\t0\ninterference\tnegative\t1\ninterference\tpositive\t0\ninterference\tsadness\t0\ninterference\tsurprise\t0\ninterference\ttrust\t0\ninterferometer\tanger\t0\ninterferometer\tanticipation\t0\ninterferometer\tdisgust\t0\ninterferometer\tfear\t0\ninterferometer\tjoy\t0\ninterferometer\tnegative\t0\ninterferometer\tpositive\t0\ninterferometer\tsadness\t0\ninterferometer\tsurprise\t0\ninterferometer\ttrust\t0\ninterim\tanger\t0\ninterim\tanticipation\t1\ninterim\tdisgust\t0\ninterim\tfear\t0\ninterim\tjoy\t0\ninterim\tnegative\t0\ninterim\tpositive\t0\ninterim\tsadness\t0\ninterim\tsurprise\t0\ninterim\ttrust\t0\ninterior\tanger\t0\ninterior\tanticipation\t0\ninterior\tdisgust\t1\ninterior\tfear\t0\ninterior\tjoy\t0\ninterior\tnegative\t0\ninterior\tpositive\t1\ninterior\tsadness\t0\ninterior\tsurprise\t0\ninterior\ttrust\t1\ninterlocutory\tanger\t0\ninterlocutory\tanticipation\t0\ninterlocutory\tdisgust\t0\ninterlocutory\tfear\t0\ninterlocutory\tjoy\t0\ninterlocutory\tnegative\t0\ninterlocutory\tpositive\t1\ninterlocutory\tsadness\t0\ninterlocutory\tsurprise\t0\ninterlocutory\ttrust\t0\ninterlude\tanger\t0\ninterlude\tanticipation\t0\ninterlude\tdisgust\t0\ninterlude\tfear\t0\ninterlude\tjoy\t0\ninterlude\tnegative\t0\ninterlude\tpositive\t1\ninterlude\tsadness\t0\ninterlude\tsurprise\t0\ninterlude\ttrust\t0\nintermediary\tanger\t0\nintermediary\tanticipation\t0\nintermediary\tdisgust\t0\nintermediary\tfear\t0\nintermediary\tjoy\t0\nintermediary\tnegative\t0\nintermediary\tpositive\t0\nintermediary\tsadness\t0\nintermediary\tsurprise\t0\nintermediary\ttrust\t0\nintermediate\tanger\t0\nintermediate\tanticipation\t0\nintermediate\tdisgust\t0\nintermediate\tfear\t0\nintermediate\tjoy\t0\nintermediate\tnegative\t0\nintermediate\tpositive\t0\nintermediate\tsadness\t0\nintermediate\tsurprise\t0\nintermediate\ttrust\t0\ninterment\tanger\t0\ninterment\tanticipation\t0\ninterment\tdisgust\t0\ninterment\tfear\t0\ninterment\tjoy\t0\ninterment\tnegative\t1\ninterment\tpositive\t0\ninterment\tsadness\t1\ninterment\tsurprise\t0\ninterment\ttrust\t0\ninterminable\tanger\t1\ninterminable\tanticipation\t1\ninterminable\tdisgust\t0\ninterminable\tfear\t0\ninterminable\tjoy\t0\ninterminable\tnegative\t1\ninterminable\tpositive\t1\ninterminable\tsadness\t0\ninterminable\tsurprise\t0\ninterminable\ttrust\t0\nintermission\tanger\t0\nintermission\tanticipation\t1\nintermission\tdisgust\t0\nintermission\tfear\t0\nintermission\tjoy\t0\nintermission\tnegative\t0\nintermission\tpositive\t0\nintermission\tsadness\t0\nintermission\tsurprise\t0\nintermission\ttrust\t0\nintermittent\tanger\t0\nintermittent\tanticipation\t0\nintermittent\tdisgust\t0\nintermittent\tfear\t0\nintermittent\tjoy\t0\nintermittent\tnegative\t0\nintermittent\tpositive\t0\nintermittent\tsadness\t0\nintermittent\tsurprise\t0\nintermittent\ttrust\t0\nintern\tanger\t0\nintern\tanticipation\t0\nintern\tdisgust\t0\nintern\tfear\t0\nintern\tjoy\t0\nintern\tnegative\t0\nintern\tpositive\t0\nintern\tsadness\t0\nintern\tsurprise\t0\nintern\ttrust\t0\ninternal\tanger\t0\ninternal\tanticipation\t0\ninternal\tdisgust\t0\ninternal\tfear\t0\ninternal\tjoy\t0\ninternal\tnegative\t0\ninternal\tpositive\t0\ninternal\tsadness\t0\ninternal\tsurprise\t0\ninternal\ttrust\t0\ninternally\tanger\t0\ninternally\tanticipation\t0\ninternally\tdisgust\t0\ninternally\tfear\t0\ninternally\tjoy\t0\ninternally\tnegative\t0\ninternally\tpositive\t0\ninternally\tsadness\t0\ninternally\tsurprise\t0\ninternally\ttrust\t0\ninternational\tanger\t0\ninternational\tanticipation\t0\ninternational\tdisgust\t0\ninternational\tfear\t0\ninternational\tjoy\t0\ninternational\tnegative\t0\ninternational\tpositive\t0\ninternational\tsadness\t0\ninternational\tsurprise\t0\ninternational\ttrust\t0\ninterpolate\tanger\t0\ninterpolate\tanticipation\t0\ninterpolate\tdisgust\t0\ninterpolate\tfear\t0\ninterpolate\tjoy\t0\ninterpolate\tnegative\t0\ninterpolate\tpositive\t0\ninterpolate\tsadness\t0\ninterpolate\tsurprise\t0\ninterpolate\ttrust\t0\ninterpolation\tanger\t0\ninterpolation\tanticipation\t0\ninterpolation\tdisgust\t0\ninterpolation\tfear\t0\ninterpolation\tjoy\t0\ninterpolation\tnegative\t0\ninterpolation\tpositive\t0\ninterpolation\tsadness\t0\ninterpolation\tsurprise\t0\ninterpolation\ttrust\t0\ninterpret\tanger\t0\ninterpret\tanticipation\t0\ninterpret\tdisgust\t0\ninterpret\tfear\t0\ninterpret\tjoy\t0\ninterpret\tnegative\t0\ninterpret\tpositive\t0\ninterpret\tsadness\t0\ninterpret\tsurprise\t0\ninterpret\ttrust\t0\ninterpretation\tanger\t0\ninterpretation\tanticipation\t0\ninterpretation\tdisgust\t0\ninterpretation\tfear\t0\ninterpretation\tjoy\t0\ninterpretation\tnegative\t0\ninterpretation\tpositive\t0\ninterpretation\tsadness\t0\ninterpretation\tsurprise\t0\ninterpretation\ttrust\t0\ninterpreter\tanger\t0\ninterpreter\tanticipation\t0\ninterpreter\tdisgust\t0\ninterpreter\tfear\t0\ninterpreter\tjoy\t0\ninterpreter\tnegative\t0\ninterpreter\tpositive\t0\ninterpreter\tsadness\t0\ninterpreter\tsurprise\t0\ninterpreter\ttrust\t0\ninterrelated\tanger\t0\ninterrelated\tanticipation\t0\ninterrelated\tdisgust\t0\ninterrelated\tfear\t0\ninterrelated\tjoy\t0\ninterrelated\tnegative\t0\ninterrelated\tpositive\t0\ninterrelated\tsadness\t0\ninterrelated\tsurprise\t0\ninterrelated\ttrust\t0\ninterrogate\tanger\t0\ninterrogate\tanticipation\t0\ninterrogate\tdisgust\t0\ninterrogate\tfear\t1\ninterrogate\tjoy\t0\ninterrogate\tnegative\t0\ninterrogate\tpositive\t0\ninterrogate\tsadness\t0\ninterrogate\tsurprise\t0\ninterrogate\ttrust\t0\ninterrogation\tanger\t0\ninterrogation\tanticipation\t0\ninterrogation\tdisgust\t0\ninterrogation\tfear\t1\ninterrogation\tjoy\t0\ninterrogation\tnegative\t0\ninterrogation\tpositive\t0\ninterrogation\tsadness\t0\ninterrogation\tsurprise\t0\ninterrogation\ttrust\t0\ninterrupt\tanger\t1\ninterrupt\tanticipation\t0\ninterrupt\tdisgust\t0\ninterrupt\tfear\t0\ninterrupt\tjoy\t0\ninterrupt\tnegative\t1\ninterrupt\tpositive\t0\ninterrupt\tsadness\t0\ninterrupt\tsurprise\t1\ninterrupt\ttrust\t0\ninterrupted\tanger\t0\ninterrupted\tanticipation\t0\ninterrupted\tdisgust\t0\ninterrupted\tfear\t0\ninterrupted\tjoy\t0\ninterrupted\tnegative\t1\ninterrupted\tpositive\t0\ninterrupted\tsadness\t1\ninterrupted\tsurprise\t0\ninterrupted\ttrust\t0\ninterruption\tanger\t0\ninterruption\tanticipation\t0\ninterruption\tdisgust\t0\ninterruption\tfear\t0\ninterruption\tjoy\t0\ninterruption\tnegative\t0\ninterruption\tpositive\t0\ninterruption\tsadness\t0\ninterruption\tsurprise\t0\ninterruption\ttrust\t0\nintersect\tanger\t0\nintersect\tanticipation\t0\nintersect\tdisgust\t0\nintersect\tfear\t0\nintersect\tjoy\t0\nintersect\tnegative\t0\nintersect\tpositive\t0\nintersect\tsadness\t0\nintersect\tsurprise\t0\nintersect\ttrust\t0\nintersection\tanger\t0\nintersection\tanticipation\t0\nintersection\tdisgust\t0\nintersection\tfear\t0\nintersection\tjoy\t0\nintersection\tnegative\t0\nintersection\tpositive\t0\nintersection\tsadness\t0\nintersection\tsurprise\t0\nintersection\ttrust\t0\ninterstitial\tanger\t0\ninterstitial\tanticipation\t0\ninterstitial\tdisgust\t0\ninterstitial\tfear\t0\ninterstitial\tjoy\t0\ninterstitial\tnegative\t0\ninterstitial\tpositive\t0\ninterstitial\tsadness\t0\ninterstitial\tsurprise\t0\ninterstitial\ttrust\t0\ninterval\tanger\t0\ninterval\tanticipation\t0\ninterval\tdisgust\t0\ninterval\tfear\t0\ninterval\tjoy\t0\ninterval\tnegative\t0\ninterval\tpositive\t0\ninterval\tsadness\t0\ninterval\tsurprise\t0\ninterval\ttrust\t0\nintervening\tanger\t0\nintervening\tanticipation\t0\nintervening\tdisgust\t0\nintervening\tfear\t0\nintervening\tjoy\t0\nintervening\tnegative\t0\nintervening\tpositive\t0\nintervening\tsadness\t0\nintervening\tsurprise\t0\nintervening\ttrust\t0\nintervention\tanger\t0\nintervention\tanticipation\t0\nintervention\tdisgust\t0\nintervention\tfear\t0\nintervention\tjoy\t0\nintervention\tnegative\t1\nintervention\tpositive\t1\nintervention\tsadness\t1\nintervention\tsurprise\t0\nintervention\ttrust\t0\ninterview\tanger\t0\ninterview\tanticipation\t0\ninterview\tdisgust\t0\ninterview\tfear\t0\ninterview\tjoy\t0\ninterview\tnegative\t0\ninterview\tpositive\t0\ninterview\tsadness\t0\ninterview\tsurprise\t0\ninterview\ttrust\t0\ninterviewer\tanger\t0\ninterviewer\tanticipation\t0\ninterviewer\tdisgust\t0\ninterviewer\tfear\t1\ninterviewer\tjoy\t0\ninterviewer\tnegative\t0\ninterviewer\tpositive\t0\ninterviewer\tsadness\t0\ninterviewer\tsurprise\t0\ninterviewer\ttrust\t0\ninterworking\tanger\t0\ninterworking\tanticipation\t0\ninterworking\tdisgust\t0\ninterworking\tfear\t0\ninterworking\tjoy\t0\ninterworking\tnegative\t0\ninterworking\tpositive\t0\ninterworking\tsadness\t0\ninterworking\tsurprise\t0\ninterworking\ttrust\t0\nintestate\tanger\t0\nintestate\tanticipation\t0\nintestate\tdisgust\t0\nintestate\tfear\t0\nintestate\tjoy\t0\nintestate\tnegative\t1\nintestate\tpositive\t0\nintestate\tsadness\t0\nintestate\tsurprise\t0\nintestate\ttrust\t0\nintestinal\tanger\t0\nintestinal\tanticipation\t0\nintestinal\tdisgust\t1\nintestinal\tfear\t0\nintestinal\tjoy\t0\nintestinal\tnegative\t0\nintestinal\tpositive\t0\nintestinal\tsadness\t0\nintestinal\tsurprise\t0\nintestinal\ttrust\t0\nintestine\tanger\t0\nintestine\tanticipation\t0\nintestine\tdisgust\t0\nintestine\tfear\t0\nintestine\tjoy\t0\nintestine\tnegative\t0\nintestine\tpositive\t0\nintestine\tsadness\t0\nintestine\tsurprise\t0\nintestine\ttrust\t0\nintestines\tanger\t0\nintestines\tanticipation\t0\nintestines\tdisgust\t0\nintestines\tfear\t0\nintestines\tjoy\t0\nintestines\tnegative\t0\nintestines\tpositive\t0\nintestines\tsadness\t0\nintestines\tsurprise\t0\nintestines\ttrust\t0\nintimacy\tanger\t0\nintimacy\tanticipation\t0\nintimacy\tdisgust\t0\nintimacy\tfear\t0\nintimacy\tjoy\t0\nintimacy\tnegative\t0\nintimacy\tpositive\t0\nintimacy\tsadness\t0\nintimacy\tsurprise\t0\nintimacy\ttrust\t0\nintimate\tanger\t0\nintimate\tanticipation\t1\nintimate\tdisgust\t0\nintimate\tfear\t0\nintimate\tjoy\t1\nintimate\tnegative\t0\nintimate\tpositive\t1\nintimate\tsadness\t0\nintimate\tsurprise\t0\nintimate\ttrust\t1\nintimately\tanger\t0\nintimately\tanticipation\t1\nintimately\tdisgust\t0\nintimately\tfear\t1\nintimately\tjoy\t1\nintimately\tnegative\t0\nintimately\tpositive\t0\nintimately\tsadness\t0\nintimately\tsurprise\t0\nintimately\ttrust\t0\nintimation\tanger\t0\nintimation\tanticipation\t0\nintimation\tdisgust\t0\nintimation\tfear\t0\nintimation\tjoy\t0\nintimation\tnegative\t0\nintimation\tpositive\t0\nintimation\tsadness\t0\nintimation\tsurprise\t0\nintimation\ttrust\t0\nintimidate\tanger\t0\nintimidate\tanticipation\t0\nintimidate\tdisgust\t0\nintimidate\tfear\t1\nintimidate\tjoy\t0\nintimidate\tnegative\t1\nintimidate\tpositive\t0\nintimidate\tsadness\t0\nintimidate\tsurprise\t0\nintimidate\ttrust\t0\nintimidation\tanger\t1\nintimidation\tanticipation\t0\nintimidation\tdisgust\t0\nintimidation\tfear\t1\nintimidation\tjoy\t0\nintimidation\tnegative\t1\nintimidation\tpositive\t0\nintimidation\tsadness\t0\nintimidation\tsurprise\t0\nintimidation\ttrust\t0\nintolerable\tanger\t1\nintolerable\tanticipation\t0\nintolerable\tdisgust\t0\nintolerable\tfear\t0\nintolerable\tjoy\t0\nintolerable\tnegative\t1\nintolerable\tpositive\t0\nintolerable\tsadness\t0\nintolerable\tsurprise\t0\nintolerable\ttrust\t0\nintolerance\tanger\t1\nintolerance\tanticipation\t0\nintolerance\tdisgust\t1\nintolerance\tfear\t1\nintolerance\tjoy\t0\nintolerance\tnegative\t1\nintolerance\tpositive\t0\nintolerance\tsadness\t0\nintolerance\tsurprise\t0\nintolerance\ttrust\t0\nintolerant\tanger\t1\nintolerant\tanticipation\t0\nintolerant\tdisgust\t1\nintolerant\tfear\t1\nintolerant\tjoy\t0\nintolerant\tnegative\t1\nintolerant\tpositive\t0\nintolerant\tsadness\t1\nintolerant\tsurprise\t0\nintolerant\ttrust\t0\nintonation\tanger\t0\nintonation\tanticipation\t0\nintonation\tdisgust\t0\nintonation\tfear\t0\nintonation\tjoy\t0\nintonation\tnegative\t0\nintonation\tpositive\t1\nintonation\tsadness\t0\nintonation\tsurprise\t0\nintonation\ttrust\t0\nintoxicated\tanger\t0\nintoxicated\tanticipation\t0\nintoxicated\tdisgust\t1\nintoxicated\tfear\t0\nintoxicated\tjoy\t0\nintoxicated\tnegative\t1\nintoxicated\tpositive\t0\nintoxicated\tsadness\t0\nintoxicated\tsurprise\t0\nintoxicated\ttrust\t0\nintoxication\tanger\t0\nintoxication\tanticipation\t0\nintoxication\tdisgust\t0\nintoxication\tfear\t0\nintoxication\tjoy\t0\nintoxication\tnegative\t0\nintoxication\tpositive\t0\nintoxication\tsadness\t0\nintoxication\tsurprise\t0\nintoxication\ttrust\t0\nintractable\tanger\t1\nintractable\tanticipation\t0\nintractable\tdisgust\t0\nintractable\tfear\t0\nintractable\tjoy\t0\nintractable\tnegative\t1\nintractable\tpositive\t0\nintractable\tsadness\t0\nintractable\tsurprise\t0\nintractable\ttrust\t0\nintramural\tanger\t0\nintramural\tanticipation\t0\nintramural\tdisgust\t0\nintramural\tfear\t0\nintramural\tjoy\t0\nintramural\tnegative\t0\nintramural\tpositive\t0\nintramural\tsadness\t0\nintramural\tsurprise\t0\nintramural\ttrust\t0\nintrepid\tanger\t0\nintrepid\tanticipation\t0\nintrepid\tdisgust\t0\nintrepid\tfear\t0\nintrepid\tjoy\t0\nintrepid\tnegative\t0\nintrepid\tpositive\t1\nintrepid\tsadness\t0\nintrepid\tsurprise\t0\nintrepid\ttrust\t0\nintricate\tanger\t0\nintricate\tanticipation\t0\nintricate\tdisgust\t0\nintricate\tfear\t0\nintricate\tjoy\t0\nintricate\tnegative\t0\nintricate\tpositive\t0\nintricate\tsadness\t0\nintricate\tsurprise\t0\nintricate\ttrust\t0\nintrigue\tanger\t0\nintrigue\tanticipation\t1\nintrigue\tdisgust\t0\nintrigue\tfear\t1\nintrigue\tjoy\t0\nintrigue\tnegative\t1\nintrigue\tpositive\t0\nintrigue\tsadness\t0\nintrigue\tsurprise\t1\nintrigue\ttrust\t0\nintriguing\tanger\t0\nintriguing\tanticipation\t0\nintriguing\tdisgust\t0\nintriguing\tfear\t0\nintriguing\tjoy\t0\nintriguing\tnegative\t0\nintriguing\tpositive\t0\nintriguing\tsadness\t0\nintriguing\tsurprise\t0\nintriguing\ttrust\t0\nintrinsic\tanger\t0\nintrinsic\tanticipation\t0\nintrinsic\tdisgust\t0\nintrinsic\tfear\t0\nintrinsic\tjoy\t0\nintrinsic\tnegative\t0\nintrinsic\tpositive\t0\nintrinsic\tsadness\t0\nintrinsic\tsurprise\t0\nintrinsic\ttrust\t0\nintrinsically\tanger\t0\nintrinsically\tanticipation\t0\nintrinsically\tdisgust\t0\nintrinsically\tfear\t0\nintrinsically\tjoy\t0\nintrinsically\tnegative\t0\nintrinsically\tpositive\t0\nintrinsically\tsadness\t0\nintrinsically\tsurprise\t0\nintrinsically\ttrust\t0\nintroduction\tanger\t0\nintroduction\tanticipation\t0\nintroduction\tdisgust\t0\nintroduction\tfear\t0\nintroduction\tjoy\t0\nintroduction\tnegative\t0\nintroduction\tpositive\t0\nintroduction\tsadness\t0\nintroduction\tsurprise\t0\nintroduction\ttrust\t0\nintroductory\tanger\t0\nintroductory\tanticipation\t0\nintroductory\tdisgust\t0\nintroductory\tfear\t0\nintroductory\tjoy\t0\nintroductory\tnegative\t0\nintroductory\tpositive\t0\nintroductory\tsadness\t0\nintroductory\tsurprise\t0\nintroductory\ttrust\t0\nintrospection\tanger\t0\nintrospection\tanticipation\t0\nintrospection\tdisgust\t0\nintrospection\tfear\t0\nintrospection\tjoy\t0\nintrospection\tnegative\t0\nintrospection\tpositive\t0\nintrospection\tsadness\t0\nintrospection\tsurprise\t0\nintrospection\ttrust\t0\nintrospective\tanger\t0\nintrospective\tanticipation\t0\nintrospective\tdisgust\t0\nintrospective\tfear\t0\nintrospective\tjoy\t0\nintrospective\tnegative\t0\nintrospective\tpositive\t0\nintrospective\tsadness\t0\nintrospective\tsurprise\t0\nintrospective\ttrust\t0\nintruder\tanger\t1\nintruder\tanticipation\t0\nintruder\tdisgust\t0\nintruder\tfear\t1\nintruder\tjoy\t0\nintruder\tnegative\t1\nintruder\tpositive\t0\nintruder\tsadness\t0\nintruder\tsurprise\t1\nintruder\ttrust\t0\nintrusion\tanger\t0\nintrusion\tanticipation\t0\nintrusion\tdisgust\t0\nintrusion\tfear\t1\nintrusion\tjoy\t0\nintrusion\tnegative\t1\nintrusion\tpositive\t0\nintrusion\tsadness\t0\nintrusion\tsurprise\t0\nintrusion\ttrust\t0\nintrusive\tanger\t1\nintrusive\tanticipation\t0\nintrusive\tdisgust\t1\nintrusive\tfear\t1\nintrusive\tjoy\t0\nintrusive\tnegative\t1\nintrusive\tpositive\t0\nintrusive\tsadness\t0\nintrusive\tsurprise\t1\nintrusive\ttrust\t0\nintuition\tanger\t0\nintuition\tanticipation\t0\nintuition\tdisgust\t0\nintuition\tfear\t0\nintuition\tjoy\t0\nintuition\tnegative\t0\nintuition\tpositive\t1\nintuition\tsadness\t0\nintuition\tsurprise\t0\nintuition\ttrust\t1\nintuitive\tanger\t0\nintuitive\tanticipation\t0\nintuitive\tdisgust\t0\nintuitive\tfear\t0\nintuitive\tjoy\t0\nintuitive\tnegative\t0\nintuitive\tpositive\t1\nintuitive\tsadness\t0\nintuitive\tsurprise\t0\nintuitive\ttrust\t0\nintuitively\tanger\t0\nintuitively\tanticipation\t1\nintuitively\tdisgust\t0\nintuitively\tfear\t0\nintuitively\tjoy\t0\nintuitively\tnegative\t0\nintuitively\tpositive\t0\nintuitively\tsadness\t0\nintuitively\tsurprise\t0\nintuitively\ttrust\t0\ninundation\tanger\t0\ninundation\tanticipation\t0\ninundation\tdisgust\t0\ninundation\tfear\t0\ninundation\tjoy\t0\ninundation\tnegative\t0\ninundation\tpositive\t0\ninundation\tsadness\t0\ninundation\tsurprise\t0\ninundation\ttrust\t0\ninvade\tanger\t1\ninvade\tanticipation\t0\ninvade\tdisgust\t0\ninvade\tfear\t1\ninvade\tjoy\t0\ninvade\tnegative\t1\ninvade\tpositive\t0\ninvade\tsadness\t1\ninvade\tsurprise\t1\ninvade\ttrust\t0\ninvader\tanger\t1\ninvader\tanticipation\t0\ninvader\tdisgust\t0\ninvader\tfear\t1\ninvader\tjoy\t0\ninvader\tnegative\t1\ninvader\tpositive\t0\ninvader\tsadness\t1\ninvader\tsurprise\t0\ninvader\ttrust\t0\ninvalid\tanger\t0\ninvalid\tanticipation\t0\ninvalid\tdisgust\t0\ninvalid\tfear\t0\ninvalid\tjoy\t0\ninvalid\tnegative\t0\ninvalid\tpositive\t0\ninvalid\tsadness\t1\ninvalid\tsurprise\t0\ninvalid\ttrust\t0\ninvalidate\tanger\t0\ninvalidate\tanticipation\t0\ninvalidate\tdisgust\t0\ninvalidate\tfear\t0\ninvalidate\tjoy\t0\ninvalidate\tnegative\t1\ninvalidate\tpositive\t0\ninvalidate\tsadness\t0\ninvalidate\tsurprise\t0\ninvalidate\ttrust\t0\ninvalidation\tanger\t0\ninvalidation\tanticipation\t0\ninvalidation\tdisgust\t0\ninvalidation\tfear\t0\ninvalidation\tjoy\t0\ninvalidation\tnegative\t1\ninvalidation\tpositive\t0\ninvalidation\tsadness\t0\ninvalidation\tsurprise\t0\ninvalidation\ttrust\t0\ninvalidity\tanger\t0\ninvalidity\tanticipation\t0\ninvalidity\tdisgust\t0\ninvalidity\tfear\t0\ninvalidity\tjoy\t0\ninvalidity\tnegative\t1\ninvalidity\tpositive\t0\ninvalidity\tsadness\t0\ninvalidity\tsurprise\t0\ninvalidity\ttrust\t0\ninvaluable\tanger\t0\ninvaluable\tanticipation\t0\ninvaluable\tdisgust\t0\ninvaluable\tfear\t0\ninvaluable\tjoy\t0\ninvaluable\tnegative\t0\ninvaluable\tpositive\t0\ninvaluable\tsadness\t0\ninvaluable\tsurprise\t0\ninvaluable\ttrust\t0\ninvariably\tanger\t0\ninvariably\tanticipation\t0\ninvariably\tdisgust\t0\ninvariably\tfear\t0\ninvariably\tjoy\t0\ninvariably\tnegative\t0\ninvariably\tpositive\t1\ninvariably\tsadness\t0\ninvariably\tsurprise\t0\ninvariably\ttrust\t0\ninvasion\tanger\t1\ninvasion\tanticipation\t0\ninvasion\tdisgust\t0\ninvasion\tfear\t0\ninvasion\tjoy\t0\ninvasion\tnegative\t1\ninvasion\tpositive\t0\ninvasion\tsadness\t0\ninvasion\tsurprise\t0\ninvasion\ttrust\t0\ninvent\tanger\t0\ninvent\tanticipation\t0\ninvent\tdisgust\t0\ninvent\tfear\t0\ninvent\tjoy\t0\ninvent\tnegative\t0\ninvent\tpositive\t0\ninvent\tsadness\t0\ninvent\tsurprise\t0\ninvent\ttrust\t0\ninvention\tanger\t0\ninvention\tanticipation\t0\ninvention\tdisgust\t0\ninvention\tfear\t0\ninvention\tjoy\t0\ninvention\tnegative\t0\ninvention\tpositive\t0\ninvention\tsadness\t0\ninvention\tsurprise\t0\ninvention\ttrust\t0\ninventive\tanger\t0\ninventive\tanticipation\t0\ninventive\tdisgust\t0\ninventive\tfear\t0\ninventive\tjoy\t0\ninventive\tnegative\t0\ninventive\tpositive\t1\ninventive\tsadness\t0\ninventive\tsurprise\t0\ninventive\ttrust\t0\ninventor\tanger\t0\ninventor\tanticipation\t0\ninventor\tdisgust\t0\ninventor\tfear\t0\ninventor\tjoy\t0\ninventor\tnegative\t0\ninventor\tpositive\t1\ninventor\tsadness\t0\ninventor\tsurprise\t0\ninventor\ttrust\t0\ninventory\tanger\t0\ninventory\tanticipation\t0\ninventory\tdisgust\t0\ninventory\tfear\t0\ninventory\tjoy\t0\ninventory\tnegative\t0\ninventory\tpositive\t0\ninventory\tsadness\t0\ninventory\tsurprise\t0\ninventory\ttrust\t0\ninverse\tanger\t0\ninverse\tanticipation\t0\ninverse\tdisgust\t0\ninverse\tfear\t0\ninverse\tjoy\t0\ninverse\tnegative\t0\ninverse\tpositive\t0\ninverse\tsadness\t0\ninverse\tsurprise\t0\ninverse\ttrust\t0\ninversely\tanger\t0\ninversely\tanticipation\t0\ninversely\tdisgust\t0\ninversely\tfear\t0\ninversely\tjoy\t0\ninversely\tnegative\t0\ninversely\tpositive\t0\ninversely\tsadness\t0\ninversely\tsurprise\t0\ninversely\ttrust\t0\ninversion\tanger\t0\ninversion\tanticipation\t0\ninversion\tdisgust\t0\ninversion\tfear\t0\ninversion\tjoy\t0\ninversion\tnegative\t0\ninversion\tpositive\t0\ninversion\tsadness\t0\ninversion\tsurprise\t0\ninversion\ttrust\t0\ninvert\tanger\t0\ninvert\tanticipation\t0\ninvert\tdisgust\t0\ninvert\tfear\t0\ninvert\tjoy\t0\ninvert\tnegative\t0\ninvert\tpositive\t0\ninvert\tsadness\t0\ninvert\tsurprise\t0\ninvert\ttrust\t0\ninverted\tanger\t0\ninverted\tanticipation\t0\ninverted\tdisgust\t0\ninverted\tfear\t0\ninverted\tjoy\t0\ninverted\tnegative\t0\ninverted\tpositive\t0\ninverted\tsadness\t0\ninverted\tsurprise\t0\ninverted\ttrust\t0\ninvestigate\tanger\t0\ninvestigate\tanticipation\t0\ninvestigate\tdisgust\t0\ninvestigate\tfear\t0\ninvestigate\tjoy\t0\ninvestigate\tnegative\t0\ninvestigate\tpositive\t1\ninvestigate\tsadness\t0\ninvestigate\tsurprise\t0\ninvestigate\ttrust\t0\ninvestigation\tanger\t0\ninvestigation\tanticipation\t1\ninvestigation\tdisgust\t0\ninvestigation\tfear\t0\ninvestigation\tjoy\t0\ninvestigation\tnegative\t0\ninvestigation\tpositive\t0\ninvestigation\tsadness\t0\ninvestigation\tsurprise\t0\ninvestigation\ttrust\t0\ninvestigator\tanger\t0\ninvestigator\tanticipation\t0\ninvestigator\tdisgust\t0\ninvestigator\tfear\t0\ninvestigator\tjoy\t0\ninvestigator\tnegative\t0\ninvestigator\tpositive\t0\ninvestigator\tsadness\t0\ninvestigator\tsurprise\t0\ninvestigator\ttrust\t0\ninvestor\tanger\t0\ninvestor\tanticipation\t0\ninvestor\tdisgust\t0\ninvestor\tfear\t0\ninvestor\tjoy\t0\ninvestor\tnegative\t0\ninvestor\tpositive\t0\ninvestor\tsadness\t0\ninvestor\tsurprise\t0\ninvestor\ttrust\t0\ninvigorate\tanger\t0\ninvigorate\tanticipation\t0\ninvigorate\tdisgust\t0\ninvigorate\tfear\t0\ninvigorate\tjoy\t0\ninvigorate\tnegative\t0\ninvigorate\tpositive\t1\ninvigorate\tsadness\t0\ninvigorate\tsu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ness\t0\nliner\tsurprise\t0\nliner\ttrust\t0\nlines\tanger\t0\nlines\tanticipation\t0\nlines\tdisgust\t0\nlines\tfear\t1\nlines\tjoy\t0\nlines\tnegative\t0\nlines\tpositive\t0\nlines\tsadness\t0\nlines\tsurprise\t0\nlines\ttrust\t0\nlinger\tanger\t0\nlinger\tanticipation\t1\nlinger\tdisgust\t0\nlinger\tfear\t0\nlinger\tjoy\t0\nlinger\tnegative\t0\nlinger\tpositive\t0\nlinger\tsadness\t0\nlinger\tsurprise\t0\nlinger\ttrust\t0\nlingo\tanger\t0\nlingo\tanticipation\t0\nlingo\tdisgust\t0\nlingo\tfear\t0\nlingo\tjoy\t0\nlingo\tnegative\t0\nlingo\tpositive\t0\nlingo\tsadness\t0\nlingo\tsurprise\t0\nlingo\ttrust\t0\nlingual\tanger\t0\nlingual\tanticipation\t0\nlingual\tdisgust\t0\nlingual\tfear\t0\nlingual\tjoy\t0\nlingual\tnegative\t0\nlingual\tpositive\t0\nlingual\tsadness\t0\nlingual\tsurprise\t0\nlingual\ttrust\t0\nlinguist\tanger\t0\nlinguist\tanticipation\t0\nlinguist\tdisgust\t0\nlinguist\tfear\t0\nlinguist\tjoy\t0\nlinguist\tnegative\t0\nlinguist\tpositive\t1\nlinguist\tsadness\t0\nlinguist\tsurprise\t0\nlinguist\ttrust\t1\nlinguistic\tanger\t0\nlinguistic\tanticipation\t0\nlinguistic\tdisgust\t0\nlinguistic\tfear\t0\nlinguistic\tjoy\t0\nlinguistic\tnegative\t0\nlinguistic\tpositive\t0\nlinguistic\tsadness\t0\nlinguistic\tsurprise\t0\nlinguistic\ttrust\t0\nlinguistics\tanger\t0\nlinguistics\tanticipation\t0\nlinguistics\tdisgust\t0\nlinguistics\tfear\t0\nlinguistics\tjoy\t0\nlinguistics\tnegative\t0\nlinguistics\tpositive\t0\nlinguistics\tsadness\t0\nlinguistics\tsurprise\t0\nlinguistics\ttrust\t0\nlining\tanger\t0\nlining\tanticipation\t0\nlining\tdisgust\t0\nlining\tfear\t0\nlining\tjoy\t0\nlining\tnegative\t0\nlining\tpositive\t0\nlining\tsadness\t0\nlining\tsurprise\t0\nlining\ttrust\t0\nlink\tanger\t0\nlink\tanticipation\t0\nlink\tdisgust\t0\nlink\tfear\t0\nlink\tjoy\t0\nlink\tnegative\t0\nlink\tpositive\t0\nlink\tsadness\t0\nlink\tsurprise\t0\nlink\ttrust\t0\nlinoleum\tanger\t0\nlinoleum\tanticipation\t0\nlinoleum\tdisgust\t0\nlinoleum\tfear\t0\nlinoleum\tjoy\t0\nlinoleum\tnegative\t0\nlinoleum\tpositive\t0\nlinoleum\tsadness\t0\nlinoleum\tsurprise\t0\nlinoleum\ttrust\t0\nlint\tanger\t0\nlint\tanticipation\t0\nlint\tdisgust\t0\nlint\tfear\t0\nlint\tjoy\t0\nlint\tnegative\t1\nlint\tpositive\t0\nlint\tsadness\t0\nlint\tsurprise\t0\nlint\ttrust\t0\nlion\tanger\t0\nlion\tanticipation\t0\nlion\tdisgust\t0\nlion\tfear\t1\nlion\tjoy\t0\nlion\tnegative\t0\nlion\tpositive\t1\nlion\tsadness\t0\nlion\tsurprise\t0\nlion\ttrust\t0\nlip\tanger\t0\nlip\tanticipation\t0\nlip\tdisgust\t0\nlip\tfear\t0\nlip\tjoy\t0\nlip\tnegative\t0\nlip\tpositive\t0\nlip\tsadness\t0\nlip\tsurprise\t0\nlip\ttrust\t0\nlipstick\tanger\t0\nlipstick\tanticipation\t0\nlipstick\tdisgust\t0\nlipstick\tfear\t0\nlipstick\tjoy\t0\nlipstick\tnegative\t0\nlipstick\tpositive\t0\nlipstick\tsadness\t0\nlipstick\tsurprise\t0\nlipstick\ttrust\t0\nliquefaction\tanger\t0\nliquefaction\tanticipation\t0\nliquefaction\tdisgust\t0\nliquefaction\tfear\t0\nliquefaction\tjoy\t0\nliquefaction\tnegative\t0\nliquefaction\tpositive\t0\nliquefaction\tsadness\t0\nliquefaction\tsurprise\t0\nliquefaction\ttrust\t0\nliquefied\tanger\t0\nliquefied\tanticipation\t0\nliquefied\tdisgust\t0\nliquefied\tfear\t0\nliquefied\tjoy\t0\nliquefied\tnegative\t0\nliquefied\tpositive\t0\nliquefied\tsadness\t0\nliquefied\tsurprise\t0\nliquefied\ttrust\t0\nliqueur\tanger\t0\nliqueur\tanticipation\t0\nliqueur\tdisgust\t0\nliqueur\tfear\t0\nliqueur\tjoy\t0\nliqueur\tnegative\t0\nliqueur\tpositive\t0\nliqueur\tsadness\t0\nliqueur\tsurprise\t0\nliqueur\ttrust\t0\nliquid\tanger\t0\nliquid\tanticipation\t0\nliquid\tdisgust\t0\nliquid\tfear\t0\nliquid\tjoy\t0\nliquid\tnegative\t0\nliquid\tpositive\t0\nliquid\tsadness\t0\nliquid\tsurprise\t0\nliquid\ttrust\t0\nliquidate\tanger\t0\nliquidate\tanticipation\t0\nliquidate\tdisgust\t0\nliquidate\tfear\t0\nliquidate\tjoy\t0\nliquidate\tnegative\t0\nliquidate\tpositive\t0\nliquidate\tsadness\t0\nliquidate\tsurprise\t0\nliquidate\ttrust\t0\nliquidation\tanger\t0\nliquidation\tanticipation\t0\nliquidation\tdisgust\t0\nliquidation\tfear\t0\nliquidation\tjoy\t0\nliquidation\tnegative\t0\nliquidation\tpositive\t0\nliquidation\tsadness\t0\nliquidation\tsurprise\t0\nliquidation\ttrust\t0\nliquidator\tanger\t0\nliquidator\tanticipation\t0\nliquidator\tdisgust\t0\nliquidator\tfear\t0\nliquidator\tjoy\t0\nliquidator\tnegative\t0\nliquidator\tpositive\t0\nliquidator\tsadness\t0\nliquidator\tsurprise\t0\nliquidator\ttrust\t0\nliquidity\tanger\t0\nliquidity\tanticipation\t0\nliquidity\tdisgust\t0\nliquidity\tfear\t0\nliquidity\tjoy\t0\nliquidity\tnegative\t0\nliquidity\tpositive\t0\nliquidity\tsadness\t0\nliquidity\tsurprise\t0\nliquidity\ttrust\t0\nliquor\tanger\t1\nliquor\tanticipation\t0\nliquor\tdisgust\t0\nliquor\tfear\t0\nliquor\tjoy\t1\nliquor\tnegative\t1\nliquor\tpositive\t0\nliquor\tsadness\t1\nliquor\tsurprise\t0\nliquor\ttrust\t0\nlisp\tanger\t0\nlisp\tanticipation\t0\nlisp\tdisgust\t0\nlisp\tfear\t0\nlisp\tjoy\t0\nlisp\tnegative\t0\nlisp\tpositive\t0\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oss\tnegative\t1\nloss\tpositive\t0\nloss\tsadness\t1\nloss\tsurprise\t0\nloss\ttrust\t0\nlost\tanger\t0\nlost\tanticipation\t0\nlost\tdisgust\t0\nlost\tfear\t0\nlost\tjoy\t0\nlost\tnegative\t1\nlost\tpositive\t0\nlost\tsadness\t1\nlost\tsurprise\t0\nlost\ttrust\t0\nlot\tanger\t0\nlot\tanticipation\t0\nlot\tdisgust\t0\nlot\tfear\t0\nlot\tjoy\t0\nlot\tnegative\t0\nlot\tpositive\t0\nlot\tsadness\t0\nlot\tsurprise\t0\nlot\ttrust\t0\nlotion\tanger\t0\nlotion\tanticipation\t0\nlotion\tdisgust\t0\nlotion\tfear\t0\nlotion\tjoy\t0\nlotion\tnegative\t0\nlotion\tpositive\t0\nlotion\tsadness\t0\nlotion\tsurprise\t0\nlotion\ttrust\t0\nlots\tanger\t0\nlots\tanticipation\t0\nlots\tdisgust\t0\nlots\tfear\t0\nlots\tjoy\t0\nlots\tnegative\t0\nlots\tpositive\t0\nlots\tsadness\t0\nlots\tsurprise\t0\nlots\ttrust\t0\nlottery\tanger\t0\nlottery\tanticipation\t1\nlottery\tdisgust\t0\nlottery\tfear\t0\nlottery\tjoy\t0\nlottery\tnegative\t0\nlottery\tpositive\t0\nlottery\tsadness\t0\nlottery\tsurprise\t0\nlottery\ttrust\t0\nlotto\tanger\t0\nlotto\tanticipation\t0\nlotto\tdisgust\t0\nlotto\tfear\t0\nlotto\tjoy\t0\nlotto\tnegative\t0\nlotto\tpositive\t0\nlotto\tsadness\t0\nlotto\tsurprise\t0\nlotto\ttrust\t0\nloud\tanger\t0\nloud\tanticipation\t0\nloud\tdisgust\t0\nloud\tfear\t0\nloud\tjoy\t0\nloud\tnegative\t0\nloud\tpositive\t0\nloud\tsadness\t0\nloud\tsurprise\t0\nloud\ttrust\t0\nloudly\tanger\t0\nloudly\tanticipation\t0\nloudly\tdisgust\t0\nloudly\tfear\t0\nloudly\tjoy\t0\nloudly\tnegative\t0\nloudly\tpositive\t0\nloudly\tsadness\t0\nloudly\tsurprise\t0\nloudly\ttrust\t0\nloudness\tanger\t1\nloudness\tanticipation\t0\nloudness\tdisgust\t0\nloudness\tfear\t0\nloudness\tjoy\t0\nloudness\tnegative\t1\nloudness\tpositive\t0\nloudness\tsadness\t0\nloudness\tsurprise\t0\nloudness\ttrust\t0\nlounge\tanger\t0\nlounge\tanticipation\t0\nlounge\tdisgust\t0\nlounge\tfear\t0\nlounge\tjoy\t0\nlounge\tnegative\t1\nlounge\tpositive\t0\nlounge\tsadness\t0\nlounge\tsurprise\t0\nlounge\ttrust\t0\nlouse\tanger\t0\nlouse\tanticipation\t0\nlouse\tdisgust\t1\nlouse\tfear\t0\nlouse\tjoy\t0\nlouse\tnegative\t1\nlouse\tpositive\t0\nlouse\tsadness\t0\nlouse\tsurprise\t0\nlouse\ttrust\t0\nlovable\tanger\t0\nlovable\tanticipation\t0\nlovable\tdisgust\t0\nlovable\tfear\t0\nlovable\tjoy\t1\nlovable\tnegative\t0\nlovable\tpositive\t1\nlovable\tsadness\t0\nlovable\tsurprise\t0\nlovable\ttrust\t1\nlove\tanger\t0\nlove\tanticipation\t0\nlove\tdisgust\t0\nlove\tfear\t0\nlove\tjoy\t1\nlove\tnegative\t0\nlove\tpositive\t1\nlove\tsadness\t0\nlove\tsurprise\t0\nlove\ttrust\t0\nlovely\tanger\t0\nlovely\tanticipation\t1\nlovely\tdisgust\t0\nlovely\tfear\t0\nlovely\tjoy\t1\nlovely\tnegative\t0\nlovely\tpositive\t1\nlovely\tsadness\t1\nlovely\tsurprise\t1\nlovely\ttrust\t1\nlovemaking\tanger\t0\nlovemaking\tanticipation\t0\nlovemaking\tdisgust\t0\nlovemaking\tfear\t0\nlovemaking\tjoy\t1\nlovemaking\tnegative\t0\nlovemaking\tpositive\t1\nlovemaking\tsadness\t0\nlovemaking\tsurprise\t0\nlovemaking\ttrust\t1\nlover\tanger\t0\nlover\tanticipation\t1\nlover\tdisgust\t0\nlover\tfear\t0\nlover\tjoy\t1\nlover\tnegative\t0\nlover\tpositive\t1\nlover\tsadness\t0\nlover\tsurprise\t0\nlover\ttrust\t1\nloving\tanger\t0\nloving\tanticipation\t0\nloving\tdisgust\t0\nloving\tfear\t0\nloving\tjoy\t1\nloving\tnegative\t0\nloving\tpositive\t1\nloving\tsadness\t0\nloving\tsurprise\t0\nloving\ttrust\t1\nlower\tanger\t0\nlower\tanticipation\t0\nlower\tdisgust\t0\nlower\tfear\t0\nlower\tjoy\t0\nlower\tnegative\t1\nlower\tpositive\t0\nlower\tsadness\t1\nlower\tsurprise\t0\nlower\ttrust\t0\nlowering\tanger\t0\nlowering\tanticipation\t0\nlowering\tdisgust\t0\nlowering\tfear\t0\nlowering\tjoy\t0\nlowering\tnegative\t1\nlowering\tpositive\t0\nlowering\tsadness\t0\nlowering\tsurprise\t0\nlowering\ttrust\t0\nlowest\tanger\t0\nlowest\tanticipation\t0\nlowest\tdisgust\t0\nlowest\tfear\t0\nlowest\tjoy\t0\nlowest\tnegative\t1\nlowest\tpositive\t0\nlowest\tsadness\t1\nlowest\tsurprise\t0\nlowest\ttrust\t0\nlowlands\tanger\t0\nlowlands\tanticipation\t0\nlowlands\tdisgust\t0\nlowlands\tfear\t0\nlowlands\tjoy\t0\nlowlands\tnegative\t1\nlowlands\tpositive\t0\nlowlands\tsadness\t0\nlowlands\tsurprise\t0\nlowlands\ttrust\t0\nlowly\tanger\t0\nlowly\tanticipation\t0\nlowly\tdisgust\t0\nlowly\tfear\t0\nlowly\tjoy\t0\nlowly\tnegative\t1\nlowly\tpositive\t0\nlowly\tsadness\t1\nlowly\tsurprise\t0\nlowly\ttrust\t0\nloyal\tanger\t0\nloyal\tanticipation\t0\nloyal\tdisgust\t0\nloyal\tfear\t1\nloyal\tjoy\t1\nloyal\tnegative\t0\nloyal\tpositive\t1\nloyal\tsadness\t0\nloyal\tsurprise\t1\nloyal\ttrust\t1\nloyalty\tanger\t0\nloyalty\tanticipation\t0\nloyalty\tdisgust\t0\nloyalty\tfear\t0\nloyalty\tjoy\t0\nloyalty\tnegative\t0\nloyalty\tpositive\t1\nloyalty\tsadness\t0\nloyalty\tsurprise\t0\nloyalty\ttrust\t1\nlubricate\tanger\t0\nlubricate\tanticipation\t0\nlubricate\tdisgust\t0\nlubricate\tfear\t0\nlubricate\tjoy\t0\nlubricate\tnegative\t0\nlubricate\tpositive\t0\nlubricate\tsadness\t0\nlubricate\tsurprise\t0\nlubricate\ttrust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tdisgust\t0\nmaturation\tfear\t0\nmaturation\tjoy\t0\nmaturation\tnegative\t0\nmaturation\tpositive\t0\nmaturation\tsadness\t0\nmaturation\tsurprise\t0\nmaturation\ttrust\t0\nmaturity\tanger\t0\nmaturity\tanticipation\t0\nmaturity\tdisgust\t0\nmaturity\tfear\t0\nmaturity\tjoy\t0\nmaturity\tnegative\t0\nmaturity\tpositive\t0\nmaturity\tsadness\t0\nmaturity\tsurprise\t0\nmaturity\ttrust\t0\nmausoleum\tanger\t0\nmausoleum\tanticipation\t0\nmausoleum\tdisgust\t0\nmausoleum\tfear\t0\nmausoleum\tjoy\t0\nmausoleum\tnegative\t0\nmausoleum\tpositive\t0\nmausoleum\tsadness\t1\nmausoleum\tsurprise\t0\nmausoleum\ttrust\t0\nmauve\tanger\t0\nmauve\tanticipation\t0\nmauve\tdisgust\t0\nmauve\tfear\t0\nmauve\tjoy\t0\nmauve\tnegative\t0\nmauve\tpositive\t0\nmauve\tsadness\t0\nmauve\tsurprise\t0\nmauve\ttrust\t0\nmaxim\tanger\t0\nmaxim\tanticipation\t0\nmaxim\tdisgust\t0\nmaxim\tfear\t0\nmaxim\tjoy\t0\nmaxim\tnegative\t0\nmaxim\tpositive\t0\nmaxim\tsadness\t0\nmaxim\tsurprise\t0\nmaxim\ttrust\t1\nmaximum\tanger\t0\nmaximum\tanticipation\t0\nmaximum\tdisgust\t0\nmaximum\tfear\t0\nmaximum\tjoy\t0\nmaximum\tnegative\t0\nmaximum\tpositive\t1\nmaximum\tsadness\t0\nmaximum\tsurprise\t0\nmaximum\ttrust\t0\nmayor\tanger\t0\nmayor\tanticipation\t0\nmayor\tdisgust\t0\nmayor\tfear\t0\nmayor\tjoy\t0\nmayor\tnegative\t0\nmayor\tpositive\t1\nmayor\tsadness\t0\nmayor\tsurprise\t0\nmayor\ttrust\t0\nmaze\tanger\t0\nmaze\tanticipation\t0\nmaze\tdisgust\t0\nmaze\tfear\t0\nmaze\tjoy\t0\nmaze\tnegative\t0\nmaze\tpositive\t0\nmaze\tsadness\t0\nmaze\tsurprise\t0\nmaze\ttrust\t0\nmead\tanger\t0\nmead\tanticipation\t0\nmead\tdisgust\t0\nmead\tfear\t0\nmead\tjoy\t0\nmead\tnegative\t0\nmead\tpositive\t0\nmead\tsadness\t0\nmead\tsurprise\t0\nmead\ttrust\t0\nmeadow\tanger\t0\nmeadow\tanticipation\t0\nmeadow\tdisgust\t0\nmeadow\tfear\t0\nmeadow\tjoy\t0\nmeadow\tnegative\t0\nmeadow\tpositive\t1\nmeadow\tsadness\t0\nmeadow\tsurprise\t0\nmeadow\ttrust\t0\nmeal\tanger\t0\nmeal\tanticipation\t0\nmeal\tdisgust\t0\nmeal\tfear\t0\nmeal\tjoy\t0\nmeal\tnegative\t0\nmeal\tpositive\t0\nmeal\tsadness\t0\nmeal\tsurprise\t0\nmeal\ttrust\t0\nmeander\tanger\t0\nmeander\tanticipation\t0\nmeander\tdisgust\t0\nmeander\tfear\t0\nmeander\tjoy\t0\nmeander\tnegative\t0\nmeander\tpositive\t0\nmeander\tsadness\t0\nmeander\tsurprise\t0\nmeander\ttrust\t0\nmeandering\tanger\t0\nmeandering\tanticipation\t0\nmeandering\tdisgust\t0\nmeandering\tfear\t0\nmeandering\tjoy\t0\nmeandering\tnegative\t1\nmeandering\tpositive\t0\nmeandering\tsadness\t0\nmeandering\tsurprise\t0\nmeandering\ttrust\t0\nmeaning\tanger\t0\nmeaning\tanticipation\t0\nmeaning\tdisgust\t0\nmeaning\tfear\t0\nmeaning\tjoy\t0\nmeaning\tnegative\t0\nmeaning\tpositive\t0\nmeaning\tsadness\t0\nmeaning\tsurprise\t0\nmeaning\ttrust\t0\nmeaningless\tanger\t0\nmeaningless\tanticipation\t0\nmeaningless\tdisgust\t0\nmeaningless\tfear\t0\nmeaningless\tjoy\t0\nmeaningless\tnegative\t1\nmeaningless\tpositive\t0\nmeaningless\tsadness\t1\nmeaningless\tsurprise\t0\nmeaningless\ttrust\t0\nmeans\tanger\t0\nmeans\tanticipation\t0\nmeans\tdisgust\t0\nmeans\tfear\t0\nmeans\tjoy\t0\nmeans\tnegative\t0\nmeans\tpositive\t0\nmeans\tsadness\t0\nmeans\tsurprise\t0\nmeans\ttrust\t0\nmeantime\tanger\t0\nmeantime\tanticipation\t0\nmeantime\tdisgust\t0\nmeantime\tfear\t0\nmeantime\tjoy\t0\nmeantime\tnegative\t0\nmeantime\tpositive\t0\nmeantime\tsadness\t0\nmeantime\tsurprise\t0\nmeantime\ttrust\t0\nmeasles\tanger\t0\nmeasles\tanticipation\t0\nmeasles\tdisgust\t1\nmeasles\tfear\t1\nmeasles\tjoy\t0\nmeasles\tnegative\t1\nmeasles\tpositive\t0\nmeasles\tsadness\t1\nmeasles\tsurprise\t0\nmeasles\ttrust\t0\nmeasurable\tanger\t0\nmeasurable\tanticipation\t0\nmeasurable\tdisgust\t0\nmeasurable\tfear\t0\nmeasurable\tjoy\t0\nmeasurable\tnegative\t0\nmeasurable\tpositive\t0\nmeasurable\tsadness\t0\nmeasurable\tsurprise\t0\nmeasurable\ttrust\t0\nmeasure\tanger\t0\nmeasure\tanticipation\t0\nmeasure\tdisgust\t0\nmeasure\tfear\t0\nmeasure\tjoy\t0\nmeasure\tnegative\t0\nmeasure\tpositive\t0\nmeasure\tsadness\t0\nmeasure\tsurprise\t0\nmeasure\ttrust\t1\nmeasured\tanger\t0\nmeasured\tanticipation\t0\nmeasured\tdisgust\t0\nmeasured\tfear\t0\nmeasured\tjoy\t0\nmeasured\tnegative\t0\nmeasured\tpositive\t1\nmeasured\tsadness\t0\nmeasured\tsurprise\t0\nmeasured\ttrust\t1\nmeasurement\tanger\t0\nmeasurement\tanticipation\t0\nmeasurement\tdisgust\t0\nmeasurement\tfear\t0\nmeasurement\tjoy\t0\nmeasurement\tnegative\t0\nmeasurement\tpositive\t0\nmeasurement\tsadness\t0\nmeasurement\tsurprise\t0\nmeasurement\ttrust\t0\nmeasuring\tanger\t0\nmeasuring\tanticipation\t0\nmeasuring\tdisgust\t0\nmeasuring\tfear\t0\nmeasuring\tjoy\t0\nmeasuring\tnegative\t0\nmeasuring\tpositive\t0\nmeasuring\tsadness\t0\nmeasuring\tsurprise\t0\nmeasuring\ttrust\t0\nmeat\tanger\t0\nmeat\tanticipation\t0\nmeat\tdisgust\t0\nmeat\tfear\t0\nmeat\tjoy\t0\nmeat\tnegative\t0\nmeat\tpositive\t0\nmeat\tsadness\t0\nmeat\tsurprise\t0\nmeat\ttrust\t0\nmechanic\tanger\t0\nmechanic\tanticipation\t0\nmechanic\tdisgust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0\nmetaphor\tpositive\t0\nmetaphor\tsadness\t0\nmetaphor\tsurprise\t0\nmetaphor\ttrust\t0\nmetaphorical\tanger\t0\nmetaphorical\tanticipation\t0\nmetaphorical\tdisgust\t0\nmetaphorical\tfear\t0\nmetaphorical\tjoy\t0\nmetaphorical\tnegative\t0\nmetaphorical\tpositive\t0\nmetaphorical\tsadness\t0\nmetaphorical\tsurprise\t0\nmetaphorical\ttrust\t0\nmetaphysical\tanger\t0\nmetaphysical\tanticipation\t0\nmetaphysical\tdisgust\t0\nmetaphysical\tfear\t0\nmetaphysical\tjoy\t0\nmetaphysical\tnegative\t0\nmetaphysical\tpositive\t0\nmetaphysical\tsadness\t0\nmetaphysical\tsurprise\t0\nmetaphysical\ttrust\t0\nmetaphysics\tanger\t0\nmetaphysics\tanticipation\t0\nmetaphysics\tdisgust\t0\nmetaphysics\tfear\t0\nmetaphysics\tjoy\t0\nmetaphysics\tnegative\t0\nmetaphysics\tpositive\t0\nmetaphysics\tsadness\t0\nmetaphysics\tsurprise\t0\nmetaphysics\ttrust\t0\nmetastasis\tanger\t0\nmetastasis\tanticipation\t0\nmetastasis\tdisgust\t0\nmetastasis\tfear\t0\nmetastasis\tjoy\t0\nmetastasis\tnegative\t1\nmetastasis\tpositive\t0\nmetastasis\tsadness\t0\nmetastasis\tsurprise\t0\nmetastasis\ttrust\t0\nmeteor\tanger\t0\nmeteor\tanticipation\t0\nmeteor\tdisgust\t0\nmeteor\tfear\t0\nmeteor\tjoy\t0\nmeteor\tnegative\t0\nmeteor\tpositive\t0\nmeteor\tsadness\t0\nmeteor\tsurprise\t0\nmeteor\ttrust\t0\nmeteoric\tanger\t0\nmeteoric\tanticipation\t0\nmeteoric\tdisgust\t0\nmeteoric\tfear\t0\nmeteoric\tjoy\t0\nmeteoric\tnegative\t0\nmeteoric\tpositive\t0\nmeteoric\tsadness\t0\nmeteoric\tsurprise\t0\nmeteoric\ttrust\t0\nmeteorite\tanger\t0\nmeteorite\tanticipation\t0\nmeteorite\tdisgust\t0\nmeteorite\tfear\t0\nmeteorite\tjoy\t0\nmeteorite\tnegative\t0\nmeteorite\tpositive\t0\nmeteorite\tsadness\t0\nmeteorite\tsurprise\t0\nmeteorite\ttrust\t0\nmeteorological\tanger\t0\nmeteorological\tanticipation\t0\nmeteorological\tdisgust\t0\nmeteorological\tfear\t0\nmeteorological\tjoy\t0\nmeteorological\tnegative\t0\nmeteorological\tpositive\t0\nmeteorological\tsadness\t0\nmeteorological\tsurprise\t0\nmeteorological\ttrust\t0\nmeteorology\tanger\t0\nmeteorology\tanticipation\t0\nmeteorology\tdisgust\t0\nmeteorology\tfear\t0\nmeteorology\tjoy\t0\nmeteorology\tnegative\t0\nmeteorology\tpositive\t0\nmeteorology\tsadness\t0\nmeteorology\tsurprise\t0\nmeteorology\ttrust\t0\nmeter\tanger\t0\nmeter\tanticipation\t0\nmeter\tdisgust\t0\nmeter\tfear\t0\nmeter\tjoy\t0\nmeter\tnegative\t0\nmeter\tpositive\t0\nmeter\tsadness\t0\nmeter\tsurprise\t0\nmeter\ttrust\t0\nmethanol\tanger\t0\nmethanol\tanticipation\t0\nmethanol\tdisgust\t0\nmethanol\tfear\t0\nmethanol\tjoy\t0\nmethanol\tnegative\t1\nmethanol\tpositive\t0\nmethanol\tsadness\t0\nmethanol\tsurprise\t0\nmethanol\ttrust\t0\nmethod\tanger\t0\nmethod\tanticipation\t0\nmethod\tdisgust\t0\nmethod\tfear\t0\nmethod\tjoy\t0\nmethod\tnegative\t0\nmethod\tpositive\t0\nmethod\tsadness\t0\nmethod\tsurprise\t0\nmethod\ttrust\t0\nmethodical\tanger\t0\nmethodical\tanticipation\t0\nmethodical\tdisgust\t0\nmethodical\tfear\t0\nmethodical\tjoy\t0\nmethodical\tnegative\t0\nmethodical\tpositive\t0\nmethodical\tsadness\t0\nmethodical\tsurprise\t0\nmethodical\ttrust\t0\nmeticulous\tanger\t0\nmeticulous\tanticipation\t0\nmeticulous\tdisgust\t0\nmeticulous\tfear\t0\nmeticulous\tjoy\t0\nmeticulous\tnegative\t0\nmeticulous\tpositive\t0\nmeticulous\tsadness\t0\nmeticulous\tsurprise\t0\nmeticulous\ttrust\t0\nmetric\tanger\t0\nmetric\tanticipation\t0\nmetric\tdisgust\t0\nmetric\tfear\t0\nmetric\tjoy\t0\nmetric\tnegative\t0\nmetric\tpositive\t0\nmetric\tsadness\t0\nmetric\tsurprise\t0\nmetric\ttrust\t0\nmetrical\tanger\t0\nmetrical\tanticipation\t0\nmetrical\tdisgust\t0\nmetrical\tfear\t0\nmetrical\tjoy\t0\nmetrical\tnegative\t0\nmetrical\tpositive\t0\nmetrical\tsadness\t0\nmetrical\tsurprise\t0\nmetrical\ttrust\t0\nmetrology\tanger\t0\nmetrology\tanticipation\t0\nmetrology\tdisgust\t0\nmetrology\tfear\t0\nmetrology\tjoy\t0\nmetrology\tnegative\t0\nmetrology\tpositive\t0\nmetrology\tsadness\t0\nmetrology\tsurprise\t0\nmetrology\ttrust\t0\nmetropolis\tanger\t0\nmetropolis\tanticipation\t0\nmetropolis\tdisgust\t0\nmetropolis\tfear\t0\nmetropolis\tjoy\t0\nmetropolis\tnegative\t0\nmetropolis\tpositive\t0\nmetropolis\tsadness\t0\nmetropolis\tsurprise\t0\nmetropolis\ttrust\t0\nmetropolitan\tanger\t0\nmetropolitan\tanticipation\t0\nmetropolitan\tdisgust\t0\nmetropolitan\tfear\t0\nmetropolitan\tjoy\t0\nmetropolitan\tnegative\t0\nmetropolitan\tpositive\t1\nmetropolitan\tsadness\t0\nmetropolitan\tsurprise\t0\nmetropolitan\ttrust\t0\nmettle\tanger\t0\nmettle\tanticipation\t0\nmettle\tdisgust\t0\nmettle\tfear\t0\nmettle\tjoy\t0\nmettle\tnegative\t0\nmettle\tpositive\t1\nmettle\tsadness\t0\nmettle\tsurprise\t0\nmettle\ttrust\t0\nmew\tanger\t0\nmew\tanticipation\t0\nmew\tdisgust\t0\nmew\tfear\t0\nmew\tjoy\t0\nmew\tnegative\t0\nmew\tpositive\t0\nmew\tsadness\t0\nmew\tsurprise\t0\nmew\ttrust\t0\nmica\tanger\t0\nmica\tanticipation\t0\nmica\tdisgust\t0\nmica\tfear\t0\nmica\tjoy\t0\nmica\tnegative\t0\nmica\tpositive\t0\nmica\tsadness\t0\nmica\tsurprise\t0\nmica\ttrust\t0\nmick\tanger\t0\nmick\tanticipation\t0\nmick\tdisgust\t0\nmick\tfear\t0\nmick\tjoy\t0\nmick\tnegative\t0\nmick\tpositive\t0\nmick\tsadness\t0\nmick\tsurprise\t0\nmick\ttrust\t0\nmicrobe\tanger\t0\nmicrobe\tanticipation\t0\nmicrobe\tdisgust\t0\nmicrobe\tfear\t0\nmicrobe\tjoy\t0\nmicrobe\tnegative\t0\nmicrobe\tpositive\t0\nmicrobe\tsadness\t0\nmicrobe\tsurprise\t0\nmicrobe\ttrust\t0\nmicrobiology\tanger\t0\nmicrobiology\tanticipation\t0\nmicrobiology\tdisgust\t0\nmicrobiology\tfear\t0\nmicrobiology\tjoy\t0\nmicrobiology\tnegative\t0\nmicrobiology\tpositive\t0\nmicrobiology\tsadness\t0\nmicrobiology\tsurprise\t0\nmicrobiology\ttrust\t0\nmicrocosm\tanger\t0\nmicrocosm\tanticipation\t0\nmicrocosm\tdisgust\t0\nmicrocosm\tfear\t0\nmicrocosm\tjoy\t0\nmicrocosm\tnegative\t0\nmicrocosm\tpositive\t0\nmicrocosm\tsadness\t0\nmicrocosm\tsurprise\t0\nmicrocosm\ttrust\t0\nmicrogram\tanger\t0\nmicrogram\tanticipation\t0\nmicrogram\tdisgust\t0\nmicrogram\tfear\t0\nmicrogram\tjoy\t0\nmicrogram\tnegative\t0\nmicrogram\tpositive\t0\nmicrogram\tsadness\t0\nmicrogram\tsurprise\t0\nmicrogram\ttrust\t0\nmicrometer\tanger\t0\nmicrometer\tanticipation\t0\nmicrometer\tdisgust\t0\nmicrometer\tfear\t0\nmicrometer\tjoy\t0\nmicrometer\tnegative\t0\nmicrometer\tpositive\t0\nmicrometer\tsadness\t0\nmicrometer\tsurprise\t0\nmicrometer\ttrust\t0\nmicron\tanger\t0\nmicron\tanticipation\t0\nmicron\tdisgust\t0\nmicron\tfear\t0\nmicron\tjoy\t0\nmicron\tnegative\t0\nmicron\tpositive\t0\nmicron\tsadness\t0\nmicron\tsurprise\t0\nmicron\ttrust\t0\nmicrophone\tanger\t0\nmicrophone\tanticipation\t0\nmicrophone\tdisgust\t0\nmicrophone\tfear\t0\nmicrophone\tjoy\t0\nmicrophone\tnegative\t0\nmicrophone\tpositive\t0\nmicrophone\tsadness\t0\nmicrophone\tsurprise\t0\nmicrophone\ttrust\t0\nmicroscope\tanger\t0\nmicroscope\tanticipation\t0\nmicroscope\tdisgust\t0\nmicroscope\tfear\t0\nmicroscope\tjoy\t0\nmicroscope\tnegative\t0\nmicroscope\tpositive\t0\nmicroscope\tsadness\t0\nmicroscope\tsurprise\t0\nmicroscope\ttrust\t1\nmicroscopic\tanger\t0\nmicroscopic\tanticipation\t0\nmicroscopic\tdisgust\t0\nmicroscopic\tfear\t0\nmicroscopic\tjoy\t0\nmicroscopic\tnegative\t0\nmicroscopic\tpositive\t0\nmicroscopic\tsadness\t0\nmicroscopic\tsurprise\t0\nmicroscopic\ttrust\t0\nmicroscopically\tanger\t0\nmicroscopically\tanticipation\t0\nmicroscopically\tdisgust\t0\nmicroscopically\tfear\t0\nmicroscopically\tjoy\t0\nmicroscopically\tnegative\t0\nmicroscopically\tpositive\t0\nmicroscopically\tsadness\t0\nmicroscopically\tsurprise\t0\nmicroscopically\ttrust\t0\nmicroscopy\tanger\t0\nmicroscopy\tanticipation\t0\nmicroscopy\tdisgust\t0\nmicroscopy\tfear\t0\nmicroscopy\tjoy\t0\nmicroscopy\tnegative\t0\nmicroscopy\tpositive\t1\nmicroscopy\tsadness\t0\nmicroscopy\tsurprise\t0\nmicroscopy\ttrust\t0\nmid\tanger\t0\nmid\tanticipation\t0\nmid\tdisgust\t0\nmid\tfear\t0\nmid\tjoy\t0\nmid\tnegative\t0\nmid\tpositive\t0\nmid\tsadness\t0\nmid\tsurprise\t0\nmid\ttrust\t0\nmidday\tanger\t0\nmidday\tanticipation\t0\nmidday\tdisgust\t0\nmidday\tfear\t0\nmidday\tjoy\t0\nmidday\tnegative\t0\nmidday\tpositive\t0\nmidday\tsadness\t0\nmidday\tsurprise\t0\nmidday\ttrust\t0\nmiddle\tanger\t0\nmiddle\tanticipation\t0\nmiddle\tdisgust\t0\nmiddle\tfear\t0\nmiddle\tjoy\t0\nmiddle\tnegative\t0\nmiddle\tpositive\t0\nmiddle\tsadness\t0\nmiddle\tsurprise\t0\nmiddle\ttrust\t0\nmiddleman\tanger\t0\nmiddleman\tanticipation\t0\nmiddleman\tdisgust\t0\nmiddleman\tfear\t0\nmiddleman\tjoy\t0\nmiddleman\tnegative\t0\nmiddleman\tpositive\t0\nmiddleman\tsadness\t0\nmiddleman\tsurprise\t0\nmiddleman\ttrust\t0\nmidland\tanger\t0\nmidland\tanticipation\t0\nmidland\tdisgust\t0\nmidland\tfear\t0\nmidland\tjoy\t0\nmidland\tnegative\t0\nmidland\tpositive\t0\nmidland\tsadness\t0\nmidland\tsurprise\t0\nmidland\ttrust\t0\nmidnight\tanger\t0\nmidnight\tanticipation\t0\nmidnight\tdisgust\t0\nmidnight\tfear\t0\nmidnight\tjoy\t0\nmidnight\tnegative\t0\nmidnight\tpositive\t0\nmidnight\tsadness\t0\nmidnight\tsurprise\t0\nmidnight\ttrust\t0\nmidst\tanger\t0\nmidst\tanticipation\t0\nmidst\tdisgust\t0\nmidst\tfear\t0\nmidst\tjoy\t0\nmidst\tnegative\t0\nmidst\tpositive\t0\nmidst\tsadness\t0\nmidst\tsurprise\t0\nmidst\ttrust\t0\nmidsummer\tanger\t0\nmidsummer\tanticipation\t0\nmidsummer\tdisgust\t0\nmidsummer\tfear\t0\nmidsummer\tjoy\t0\nmidsummer\tnegative\t0\nmidsummer\tpositive\t0\nmidsummer\tsadness\t0\nmidsummer\tsurprise\t0\nmidsummer\ttrust\t0\nmidway\tanger\t0\nmidway\tanticipation\t0\nmidway\tdisgust\t0\nmidway\tfear\t0\nmidway\tjoy\t0\nmidway\tnegative\t0\nmidway\tpositive\t0\nmidway\tsadness\t0\nmidway\tsurprise\t0\nmidway\ttrust\t0\nmidwife\tanger\t0\nmidwife\tanticipation\t1\nmidwife\tdisgust\t0\nmidwife\tfear\t0\nmidwife\tjoy\t1\nmidwife\tnegative\t1\nmidwife\tpositive\t1\nmidwife\tsadness\t0\nmidwife\tsurprise\t0\nmidwife\ttrust\t1\nmidwifery\tanger\t0\nmidwifery\tanticipation\t0\nmidwifery\tdisgust\t0\nmidwifery\tfear\t0\nmidwifery\tjoy\t0\nmidwifery\tnegative\t0\nmidwifery\tpositive\t1\nmidwifery\tsadness\t0\nmidwifery\tsurprise\t0\nmidwifery\ttrust\t0\nmien\tanger\t0\nmien\tanticipation\t0\nmien\tdisgust\t0\nmien\tfear\t0\nmien\tjoy\t0\nmien\tnegative\t0\nmien\tpositive\t0\nmien\tsadness\t0\nmien\tsurprise\t0\nmien\ttrust\t0\nmighty\tanger\t1\nmighty\tanticipation\t0\nmighty\tdisgust\t0\nmighty\tfear\t1\nmighty\tjoy\t1\nmighty\tnegative\t0\nmighty\tpositive\t1\nmighty\tsadness\t0\nmighty\tsurprise\t0\nmighty\ttrust\t1\nmigrate\tanger\t0\nmigrate\tanticipation\t0\nmigrate\tdisgust\t0\nmigrate\tfear\t0\nmigrate\tjoy\t0\nmigrate\tnegative\t0\nmigrate\tpositive\t0\nmigrate\tsadness\t0\nmigrate\tsurprise\t0\nmigrate\ttrust\t0\nmigration\tanger\t0\nmigration\tanticipation\t0\nmigration\tdisgust\t0\nmigration\tfear\t0\nmigration\tjoy\t0\nmigration\tnegative\t0\nmigration\tpositive\t0\nmigration\tsadness\t0\nmigration\tsurprise\t0\nmigration\ttrust\t0\nmigratory\tanger\t0\nmigratory\tanticipation\t0\nmigratory\tdisgust\t0\nmigratory\tfear\t0\nmigratory\tjoy\t0\nmigratory\tnegative\t0\nmigratory\tpositive\t0\nmigratory\tsadness\t0\nmigratory\tsurprise\t0\nmigratory\ttrust\t0\nmike\tanger\t0\nmike\tanticipation\t0\nmike\tdisgust\t0\nmike\tfear\t0\nmike\tjoy\t0\nmike\tnegative\t0\nmike\tpositive\t0\nmike\tsadness\t0\nmike\tsurprise\t0\nmike\ttrust\t0\nmildew\tanger\t0\nmildew\tanticipation\t0\nmildew\tdisgust\t1\nmildew\tfear\t0\nmildew\tjoy\t0\nmildew\tnegative\t1\nmildew\tpositive\t0\nmildew\tsadness\t0\nmildew\tsurprise\t0\nmildew\ttrust\t0\nmile\tanger\t0\nmile\tanticipation\t0\nmile\tdisgust\t0\nmile\tfear\t0\nmile\tjoy\t0\nmile\tnegative\t0\nmile\tpositive\t0\nmile\tsadness\t0\nmile\tsurprise\t0\nmile\ttrust\t0\nmileage\tanger\t0\nmileage\tanticipation\t0\nmileage\tdisgust\t0\nmileage\tfear\t0\nmileage\tjoy\t0\nmileage\tnegative\t0\nmileage\tpositive\t0\nmileage\tsadness\t0\nmileage\tsurprise\t0\nmileage\ttrust\t0\nmilestone\tanger\t0\nmilestone\tanticipation\t0\nmilestone\tdisgust\t0\nmilestone\tfear\t0\nmilestone\tjoy\t0\nmilestone\tnegative\t0\nmilestone\tpositive\t0\nmilestone\tsadness\t0\nmilestone\tsurprise\t0\nmilestone\ttrust\t0\nmilitant\tanger\t0\nmilitant\tanticipation\t0\nmilitant\tdisgust\t0\nmilitant\tfear\t0\nmilitant\tjoy\t0\nmilitant\tnegative\t0\nmilitant\tpositive\t0\nmilitant\tsadness\t0\nmilitant\tsurprise\t0\nmilitant\ttrust\t0\nmilitary\tanger\t0\nmilitary\tanticipation\t0\nmilitary\tdisgust\t0\nmilitary\tfear\t1\nmilitary\tjoy\t0\nmilitary\tnegative\t0\nmilitary\tpositive\t0\nmilitary\tsadness\t0\nmilitary\tsurprise\t0\nmilitary\ttrust\t0\nmilitia\tanger\t1\nmilitia\tanticipation\t0\nmilitia\tdisgust\t0\nmilitia\tfear\t1\nmilitia\tjoy\t0\nmilitia\tnegative\t1\nmilitia\tpositive\t0\nmilitia\tsadness\t1\nmilitia\tsurprise\t0\nmilitia\ttrust\t0\nmilk\tanger\t0\nmilk\tanticipation\t0\nmilk\tdisgust\t0\nmilk\tfear\t0\nmilk\tjoy\t0\nmilk\tnegative\t0\nmilk\tpositive\t0\nmilk\tsadness\t0\nmilk\tsurprise\t0\nmilk\ttrust\t0\nmilky\tanger\t0\nmilky\tanticipation\t0\nmilky\tdisgust\t0\nmilky\tfear\t0\nmilky\tjoy\t0\nmilky\tnegative\t0\nmilky\tpositive\t0\nmilky\tsadness\t0\nmilky\tsurprise\t0\nmilky\ttrust\t0\nmill\tanger\t0\nmill\tanticipation\t1\nmill\tdisgust\t0\nmill\tfear\t0\nmill\tjoy\t0\nmill\tnegative\t0\nmill\tpositive\t0\nmill\tsadness\t0\nmill\tsurprise\t0\nmill\ttrust\t0\nmillennium\tanger\t0\nmillennium\tanticipation\t0\nmillennium\tdisgust\t0\nmillennium\tfear\t0\nmillennium\tjoy\t0\nmillennium\tnegative\t0\nmillennium\tpositive\t0\nmillennium\tsadness\t0\nmillennium\tsurprise\t0\nmillennium\ttrust\t0\nmilligram\tanger\t0\nmilligram\tanticipation\t0\nmilligram\tdisgust\t0\nmilligram\tfear\t0\nmilligram\tjoy\t0\nmilligram\tnegative\t0\nmilligram\tpositive\t0\nmilligram\tsadness\t0\nmilligram\tsurprise\t0\nmilligram\ttrust\t0\nmillimeter\tanger\t0\nmillimeter\tanticipation\t0\nmillimeter\tdisgust\t0\nmillimeter\tfear\t0\nmillimeter\tjoy\t0\nmillimeter\tnegative\t0\nmillimeter\tpositive\t0\nmillimeter\tsadness\t0\nmillimeter\tsurprise\t0\nmillimeter\ttrust\t0\nmillion\tanger\t0\nmillion\tanticipation\t0\nmillion\tdisgust\t0\nmillion\tfear\t0\nmillion\tjoy\t0\nmillion\tnegative\t0\nmillion\tpositive\t0\nmillion\tsadness\t0\nmillion\tsurprise\t0\nmillion\ttrust\t0\nmillionaire\tanger\t0\nmillionaire\tanticipation\t0\nmillionaire\tdisgust\t0\nmillionaire\tfear\t0\nmillionaire\tjoy\t0\nmillionaire\tnegative\t0\nmillionaire\tpositive\t0\nmillionaire\tsadness\t0\nmillionaire\tsurprise\t0\nmillionaire\ttrust\t0\nmime\tanger\t0\nmime\tanticipation\t0\nmime\tdisgust\t0\nmime\tfear\t0\nmime\tjoy\t0\nmime\tnegative\t0\nmime\tpositive\t1\nmime\tsadness\t0\nmime\tsurprise\t0\nmime\ttrust\t0\nmimic\tanger\t0\nmimic\tanticipation\t0\nmimic\tdisgust\t0\nmimic\tfear\t0\nmimic\tjoy\t0\nmimic\tnegative\t0\nmimic\tpositive\t0\nmimic\tsadness\t0\nmimic\tsurprise\t0\nmimic\ttrust\t0\nmimicking\tanger\t0\nmimicking\tanticipation\t0\nmimicking\tdisgust\t0\nmimicking\tfear\t0\nmimicking\tjoy\t0\nmimicking\tnegative\t0\nmimicking\tpositive\t0\nmimicking\tsadness\t0\nmimicking\tsurprise\t0\nmimicking\ttrust\t0\nmimicry\tanger\t0\nmimicry\tanticipation\t0\nmimicry\tdisgust\t0\nmimicry\tfear\t0\nmimicry\tjoy\t0\nmimicry\tnegative\t1\nmimicry\tpositive\t0\nmimicry\tsadness\t0\nmimicry\tsurprise\t1\nmimicry\ttrust\t0\nmind\tanger\t0\nmind\tanticipation\t0\nmind\tdisgust\t0\nmind\tfear\t0\nmind\tjoy\t0\nmind\tnegative\t0\nmind\tpositive\t0\nmind\tsadness\t0\nmind\tsurprise\t0\nmind\ttrust\t0\nminded\tanger\t0\nminded\tanticipation\t0\nminded\tdisgust\t0\nminded\tfear\t0\nminded\tjoy\t0\nminded\tnegative\t0\nminded\tpositive\t0\nminded\tsadness\t0\nminded\tsurprise\t0\nminded\ttrust\t0\nmindful\tanger\t0\nmindful\tanticipation\t0\nmindful\tdisgust\t0\nmindful\tfear\t0\nmindful\tjoy\t0\nmindful\tnegative\t0\nmindful\tpositive\t1\nmindful\tsadness\t0\nmindful\tsurprise\t0\nmindful\ttrust\t0\nmindfulness\tanger\t0\nmindfulness\tanticipation\t0\nmindfulness\tdisgust\t0\nmindfulness\tfear\t0\nmindfulness\tjoy\t0\nmindfulness\tnegative\t0\nmindfulness\tpositive\t1\nmindfulness\tsadness\t0\nmindfulness\tsurprise\t0\nmindfulness\ttrust\t0\nmine\tanger\t0\nmine\tanticipation\t0\nmine\tdisgust\t0\nmine\tfear\t0\nmine\tjoy\t0\nmine\tnegative\t0\nmine\tpositive\t0\nmine\tsadness\t0\nmine\tsurprise\t0\nmine\ttrust\t0\nminer\tanger\t0\nminer\tanticipation\t0\nminer\tdisgust\t0\nminer\tfear\t0\nminer\tjoy\t0\nminer\tnegative\t0\nminer\tpositive\t0\nminer\tsadness\t0\nminer\tsurprise\t0\nminer\ttrust\t0\nmineral\tanger\t0\nmineral\tanticipation\t0\nmineral\tdisgust\t0\nmineral\tfear\t0\nmineral\tjoy\t0\nmineral\tnegative\t0\nmineral\tpositive\t0\nmineral\tsadness\t0\nmineral\tsurprise\t0\nmineral\ttrust\t0\nmineralogy\tanger\t0\nmineralogy\tanticipation\t0\nmineralogy\tdisgust\t0\nmineralogy\tfear\t0\nmineralogy\tjoy\t0\nmineralogy\tnegative\t0\nmineralogy\tpositive\t0\nmineralogy\tsadness\t0\nmineralogy\tsurprise\t0\nmineralogy\ttrust\t0\nmingle\tanger\t0\nmingle\tanticipation\t0\nmingle\tdisgust\t0\nmingle\tfear\t0\nmingle\tjoy\t0\nmingle\tnegative\t0\nmingle\tpositive\t0\nmingle\tsadness\t0\nmingle\tsurprise\t0\nmingle\ttrust\t0\nmingled\tanger\t0\nmingled\tanticipation\t0\nmingled\tdisgust\t0\nmingled\tfear\t0\nmingled\tjoy\t0\nmingled\tnegative\t0\nmingled\tpositive\t0\nmingled\tsadness\t0\nmingled\tsurprise\t0\nmingled\ttrust\t0\nminiature\tanger\t0\nminiature\tanticipation\t0\nminiature\tdisgust\t0\nminiature\tfear\t0\nminiature\tjoy\t0\nminiature\tnegative\t0\nminiature\tpositive\t0\nminiature\tsadness\t0\nminiature\tsurprise\t0\nminiature\ttrust\t0\nminibus\tanger\t0\nminibus\tanticipation\t0\nminibus\tdisgust\t0\nminibus\tfear\t0\nminibus\tjoy\t0\nminibus\tnegative\t0\nminibus\tpositive\t0\nminibus\tsadness\t0\nminibus\tsurprise\t0\nminibus\ttrust\t0\nminim\tanger\t0\nminim\tanticipation\t0\nminim\tdisgust\t0\nminim\tfear\t0\nminim\tjoy\t0\nminim\tnegative\t0\nminim\tpositive\t0\nminim\tsadness\t0\nminim\tsurprise\t0\nminim\ttrust\t0\nminimize\tanger\t0\nminimize\tanticipation\t0\nminimize\tdisgust\t0\nminimize\tfear\t0\nminimize\tjoy\t0\nminimize\tnegative\t1\nminimize\tpositive\t0\nminimize\tsadness\t0\nminimize\tsurprise\t0\nminimize\ttrust\t0\nminimum\tanger\t0\nminimum\tanticipation\t0\nminimum\tdisgust\t0\nminimum\tfear\t0\nminimum\tjoy\t0\nminimum\tnegative\t1\nminimum\tpositive\t0\nminimum\tsadness\t0\nminimum\tsurprise\t0\nminimum\ttrust\t0\nminister\tanger\t0\nminister\tanticipation\t0\nminister\tdisgust\t0\nminister\tfear\t0\nminister\tjoy\t0\nminister\tnegative\t0\nminister\tpositive\t0\nminister\tsadness\t0\nminister\tsurprise\t0\nminister\ttrust\t0\nministerial\tanger\t0\nministerial\tanticipation\t0\nministerial\tdisgust\t0\nministerial\tfear\t0\nministerial\tjoy\t0\nministerial\tnegative\t0\nministerial\tpositive\t0\nministerial\tsadness\t0\nministerial\tsurprise\t0\nministerial\ttrust\t0\nministry\tanger\t0\nministry\tanticipation\t0\nministry\tdisgust\t0\nministry\tfear\t0\nministry\tjoy\t1\nministry\tnegative\t0\nministry\tpositive\t1\nministry\tsadness\t0\nministry\tsurprise\t0\nministry\ttrust\t1\nminivan\tanger\t0\nminivan\tanticipation\t0\nminivan\tdisgust\t0\nminivan\tfear\t0\nminivan\tjoy\t0\nminivan\tnegative\t0\nminivan\tpositive\t0\nminivan\tsadness\t0\nminivan\tsurprise\t0\nminivan\ttrust\t0\nminnow\tanger\t0\nminnow\tanticipation\t0\nminnow\tdisgust\t0\nminnow\tfear\t0\nminnow\tjoy\t0\nminnow\tnegative\t0\nminnow\tpositive\t0\nminnow\tsadness\t0\nminnow\tsurprise\t0\nminnow\ttrust\t0\nminor\tanger\t0\nminor\tanticipation\t0\nminor\tdisgust\t0\nminor\tfear\t0\nminor\tjoy\t0\nminor\tnegative\t0\nminor\tpositive\t0\nminor\tsadness\t0\nminor\tsurprise\t0\nminor\ttrust\t0\nminority\tanger\t0\nminority\tanticipation\t0\nminority\tdisgust\t0\nminority\tfear\t0\nminority\tjoy\t0\nminority\tnegative\t1\nminority\tpositive\t0\nminority\tsadness\t0\nminority\tsurprise\t0\nminority\ttrust\t0\nminstrel\tanger\t0\nminstrel\tanticipation\t0\nminstrel\tdisgust\t0\nminstrel\tfear\t0\nminstrel\tjoy\t0\nminstrel\tnegative\t0\nminstrel\tpositive\t0\nminstrel\tsadness\t0\nminstrel\tsurprise\t0\nminstrel\ttrust\t0\nmint\tanger\t0\nmint\tanticipation\t0\nmint\tdisgust\t0\nmint\tfear\t0\nmint\tjoy\t0\nmint\tnegative\t0\nmint\tpositive\t0\nmint\tsadness\t0\nmint\tsurprise\t0\nmint\ttrust\t0\nminuscule\tanger\t0\nminuscule\tanticipation\t0\nminuscule\tdisgust\t0\nminuscule\tfear\t0\nminuscule\tjoy\t0\nminuscule\tnegative\t0\nminuscule\tpositive\t0\nminuscule\tsadness\t0\nminuscule\tsurprise\t0\nminuscule\ttrust\t0\nminute\tanger\t0\nminute\tanticipation\t0\nminute\tdisgust\t0\nminute\tfear\t0\nminute\tjoy\t0\nminute\tnegative\t0\nminute\tpositive\t0\nminute\tsadness\t0\nminute\tsurprise\t0\nminute\ttrust\t0\nminutiae\tanger\t0\nminutiae\tanticipation\t0\nminutiae\tdisgust\t0\nminutiae\tfear\t0\nminutiae\tjoy\t0\nminutiae\tnegative\t0\nminutiae\tpositive\t0\nminutiae\tsadness\t0\nminutiae\tsurprise\t0\nminutiae\ttrust\t0\nmir\tanger\t0\nmir\tanticipation\t0\nmir\tdisgust\t0\nmir\tfear\t0\nmir\tjoy\t0\nmir\tnegative\t0\nmir\tpositive\t0\nmir\tsadness\t0\nmir\tsurprise\t0\nmir\ttrust\t0\nmiracle\tanger\t0\nmiracle\tanticipation\t1\nmiracle\tdisgust\t0\nmiracle\tfear\t0\nmiracle\tjoy\t1\nmiracle\tnegative\t0\nmiracle\tpositive\t1\nmiracle\tsadness\t0\nmiracle\tsurprise\t1\nmiracle\ttrust\t1\nmiraculous\tanger\t0\nmiraculous\tanticipation\t0\nmiraculous\tdisgust\t0\nmiraculous\tfear\t0\nmiraculous\tjoy\t1\nmiraculous\tnegative\t0\nmiraculous\tpositive\t1\nmiraculous\tsadness\t0\nmiraculous\tsurprise\t1\nmiraculous\ttrust\t0\nmirage\tanger\t0\nmirage\tanticipation\t0\nmirage\tdisgust\t0\nmirage\tfear\t0\nmirage\tjoy\t0\nmirage\tnegative\t0\nmirage\tpositive\t0\nmirage\tsadness\t0\nmirage\tsurprise\t0\nmirage\ttrust\t0\nmire\tanger\t0\nmire\tanticipation\t0\nmire\tdisgust\t1\nmire\tfear\t0\nmire\tjoy\t0\nmire\tnegative\t1\nmire\tpositive\t0\nmire\tsadness\t0\nmire\tsurprise\t0\nmire\ttrust\t0\nmirror\tanger\t0\nmirror\tanticipation\t0\nmirror\tdisgust\t0\nmirror\tfear\t0\nmirror\tjoy\t0\nmirror\tnegative\t0\nmirror\tpositive\t0\nmirror\tsadness\t0\nmirror\tsurprise\t0\nmirror\ttrust\t0\nmirth\tanger\t0\nmirth\tanticipation\t0\nmirth\tdisgust\t0\nmirth\tfear\t0\nmirth\tjoy\t1\nmirth\tnegative\t0\nmirth\tpositive\t1\nmirth\tsadness\t0\nmirth\tsurprise\t0\nmirth\ttrust\t0\nmisappropriation\tanger\t0\nmisappropriation\tanticipation\t0\nmisappropriation\tdisgust\t0\nmisappropriation\tfear\t0\nmisappropriation\tjoy\t0\nmisappropriation\tnegative\t0\nmisappropriation\tpositive\t0\nmisappropriation\tsadness\t0\nmisappropriation\tsurprise\t0\nmisappropriation\ttrust\t0\nmisbehavior\tanger\t1\nmisbehavior\tanticipation\t0\nmisbehavior\tdisgust\t1\nmisbehavior\tfear\t0\nmisbehavior\tjoy\t0\nmisbehavior\tnegative\t1\nmisbehavior\tpositive\t0\nmisbehavior\tsadness\t0\nmisbehavior\tsurprise\t1\nmisbehavior\ttrust\t0\nmiscarriage\tanger\t0\nmiscarriage\tanticipation\t0\nmiscarriage\tdisgust\t0\nmiscarriage\tfear\t1\nmiscarriage\tjoy\t0\nmiscarriage\tnegative\t1\nmiscarriage\tpositive\t0\nmiscarriage\tsadness\t1\nmiscarriage\tsurprise\t0\nmiscarriage\ttrust\t0\nmiscellaneous\tanger\t0\nmiscellaneous\tanticipation\t0\nmiscellaneous\tdisgust\t0\nmiscellaneous\tfear\t0\nmiscellaneous\tjoy\t0\nmiscellaneous\tnegative\t0\nmiscellaneous\tpositive\t0\nmiscellaneous\tsadness\t0\nmiscellaneous\tsurprise\t0\nmiscellaneous\ttrust\t0\nmiscellany\tanger\t0\nmiscellany\tanticipation\t0\nmiscellany\tdisgust\t0\nmiscellany\tfear\t0\nmiscellany\tjoy\t0\nmiscellany\tnegative\t0\nmiscellany\tpositive\t0\nmiscellany\tsadness\t0\nmiscellany\tsurprise\t0\nmiscellany\ttrust\t0\nmischief\tanger\t0\nmischief\tanticipation\t0\nmischief\tdisgust\t0\nmischief\tfear\t0\nmischief\tjoy\t0\nmischief\tnegative\t1\nmischief\tpositive\t0\nmischief\tsadness\t0\nmischief\tsurprise\t0\nmischief\ttrust\t0\nmischievous\tanger\t0\nmischievous\tanticipation\t0\nmischievous\tdisgust\t0\nmischievous\tfear\t0\nmischievous\tjoy\t0\nmischievous\tnegative\t1\nmischievous\tpositive\t0\nmischievous\tsadness\t0\nmischievous\tsurprise\t0\nmischievous\ttrust\t0\nmisconception\tanger\t1\nmisconception\tanticipation\t0\nmisconception\tdisgust\t1\nmisconception\tfear\t1\nmisconception\tjoy\t0\nmisconception\tnegative\t1\nmisconception\tpositive\t0\nmisconception\tsadness\t0\nmisconception\tsurprise\t0\nmisconception\ttrust\t0\nmisconduct\tanger\t0\nmisconduct\tanticipation\t0\nmisconduct\tdisgust\t1\nmisconduct\tfear\t0\nmisconduct\tjoy\t0\nmisconduct\tnegative\t1\nmisconduct\tpositive\t0\nmisconduct\tsadness\t0\nmisconduct\tsurprise\t0\nmisconduct\ttrust\t0\nmisdemeanor\tanger\t0\nmisdemeanor\tanticipation\t0\nmisdemeanor\tdisgust\t0\nmisdemeanor\tfear\t0\nmisdemeanor\tjoy\t0\nmisdemeanor\tnegative\t0\nmisdemeanor\tpositive\t0\nmisdemeanor\tsadness\t0\nmisdemeanor\tsurprise\t0\nmisdemeanor\ttrust\t0\nmiserable\tanger\t1\nmiserable\tanticipation\t0\nmiserable\tdisgust\t1\nmiserable\tfear\t0\nmiserable\tjoy\t0\nmiserable\tnegative\t1\nmiserable\tpositive\t0\nmiserable\tsadness\t1\nmiserable\tsurprise\t0\nmiserable\ttrust\t0\nmiserably\tanger\t0\nmiserably\tanticipation\t0\nmiserably\tdisgust\t0\nmiserably\tfear\t0\nmi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onastery\tfear\t0\nmonastery\tjoy\t0\nmonastery\tnegative\t0\nmonastery\tpositive\t0\nmonastery\tsadness\t0\nmonastery\tsurprise\t0\nmonastery\ttrust\t0\nmonastic\tanger\t0\nmonastic\tanticipation\t0\nmonastic\tdisgust\t0\nmonastic\tfear\t0\nmonastic\tjoy\t0\nmonastic\tnegative\t0\nmonastic\tpositive\t0\nmonastic\tsadness\t0\nmonastic\tsurprise\t0\nmonastic\ttrust\t0\nmonetary\tanger\t0\nmonetary\tanticipation\t1\nmonetary\tdisgust\t0\nmonetary\tfear\t0\nmonetary\tjoy\t0\nmonetary\tnegative\t0\nmonetary\tpositive\t1\nmonetary\tsadness\t0\nmonetary\tsurprise\t0\nmonetary\ttrust\t0\nmoney\tanger\t1\nmoney\tanticipation\t1\nmoney\tdisgust\t0\nmoney\tfear\t0\nmoney\tjoy\t1\nmoney\tnegative\t0\nmoney\tpositive\t1\nmoney\tsadness\t0\nmoney\tsurprise\t1\nmoney\ttrust\t1\nmonk\tanger\t0\nmonk\tanticipation\t0\nmonk\tdisgust\t0\nmonk\tfear\t0\nmonk\tjoy\t0\nmonk\tnegative\t0\nmonk\tpositive\t1\nmonk\tsadness\t0\nmonk\tsurprise\t0\nmonk\ttrust\t1\nmonkey\tanger\t0\nmonkey\tanticipation\t0\nmonkey\tdisgust\t0\nmonkey\tfear\t0\nmonkey\tjoy\t0\nmonkey\tnegative\t0\nmonkey\tpositive\t0\nmonkey\tsadness\t0\nmonkey\tsurprise\t0\nmonkey\ttrust\t0\nmonochrome\tanger\t0\nmonochrome\tanticipation\t0\nmonochrome\tdisgust\t1\nmonochrome\tfear\t0\nmonochrome\tjoy\t0\nmonochrome\tnegative\t1\nmonochrome\tpositive\t0\nmonochrome\tsadness\t0\nmonochrome\tsurprise\t0\nmonochrome\ttrust\t0\nmonogamy\tanger\t0\nmonogamy\tanticipation\t0\nmonogamy\tdisgust\t0\nmonogamy\tfear\t0\nmonogamy\tjoy\t0\nmonogamy\tnegative\t0\nmonogamy\tpositive\t0\nmonogamy\tsadness\t0\nmonogamy\tsurprise\t0\nmonogamy\ttrust\t1\nmonogram\tanger\t0\nmonogram\tanticipation\t0\nmonogram\tdisgust\t0\nmonogram\tfear\t0\nmonogram\tjoy\t0\nmonogram\tnegative\t0\nmonogram\tpositive\t0\nmonogram\tsadness\t0\nmonogram\tsurprise\t0\nmonogram\ttrust\t0\nmonograph\tanger\t0\nmonograph\tanticipation\t0\nmonograph\tdisgust\t0\nmonograph\tfear\t0\nmonograph\tjoy\t0\nmonograph\tnegative\t0\nmonograph\tpositive\t0\nmonograph\tsadness\t0\nmonograph\tsurprise\t0\nmonograph\ttrust\t0\nmonolayer\tanger\t0\nmonolayer\tanticipation\t0\nmonolayer\tdisgust\t0\nmonolayer\tfear\t0\nmonolayer\tjoy\t0\nmonolayer\tnegative\t0\nmonolayer\tpositive\t0\nmonolayer\tsadness\t0\nmonolayer\tsurprise\t0\nmonolayer\ttrust\t0\nmonologue\tanger\t0\nmonologue\tanticipation\t0\nmonologue\tdisgust\t0\nmonologue\tfear\t0\nmonologue\tjoy\t0\nmonologue\tnegative\t0\nmonologue\tpositive\t0\nmonologue\tsadness\t0\nmonologue\tsurprise\t0\nmonologue\ttrust\t0\nmonopolist\tanger\t0\nmonopolist\tanticipation\t0\nmonopolist\tdisgust\t0\nmonopolist\tfear\t0\nmonopolist\tjoy\t0\nmonopolist\tnegative\t1\nmonopolist\tpositive\t0\nmonopolist\tsadness\t0\nmonopolist\tsurprise\t0\nmonopolist\ttrust\t0\nmonopoly\tanger\t0\nmonopoly\tanticipation\t0\nmonopoly\tdisgust\t0\nmonopoly\tfear\t0\nmonopoly\tjoy\t0\nmonopoly\tnegative\t0\nmonopoly\tpositive\t0\nmonopoly\tsadness\t0\nmonopoly\tsurprise\t0\nmonopoly\ttrust\t0\nmonotony\tanger\t0\nmonotony\tanticipation\t0\nmonotony\tdisgust\t0\nmonotony\tfear\t0\nmonotony\tjoy\t0\nmonotony\tnegative\t0\nmonotony\tpositive\t0\nmonotony\tsadness\t0\nmonotony\tsurprise\t0\nmonotony\ttrust\t0\nmonsoon\tanger\t0\nmonsoon\tanticipation\t0\nmonsoon\tdisgust\t0\nmonsoon\tfear\t0\nmonsoon\tjoy\t0\nmonsoon\tnegative\t1\nmonsoon\tpositive\t0\nmonsoon\tsadness\t1\nmonsoon\tsurprise\t0\nmonsoon\ttrust\t0\nmonster\tanger\t0\nmonster\tanticipation\t0\nmonster\tdisgust\t0\nmonster\tfear\t1\nmonster\tjoy\t0\nmonster\tnegative\t1\nmonster\tpositive\t0\nmonster\tsadness\t0\nmonster\tsurprise\t0\nmonster\ttrust\t0\nmonstrosity\tanger\t1\nmonstrosity\tanticipation\t0\nmonstrosity\tdisgust\t1\nmonstrosity\tfear\t1\nmonstrosity\tjoy\t0\nmonstrosity\tnegative\t1\nmonstrosity\tpositive\t0\nmonstrosity\tsadness\t0\nmonstrosity\tsurprise\t1\nmonstrosity\ttrust\t0\nmonte\tanger\t0\nmonte\tanticipation\t0\nmonte\tdisgust\t0\nmonte\tfear\t0\nmonte\tjoy\t0\nmonte\tnegative\t0\nmonte\tpositive\t0\nmonte\tsadness\t0\nmonte\tsurprise\t0\nmonte\ttrust\t0\nmonth\tanger\t0\nmonth\tanticipation\t0\nmonth\tdisgust\t0\nmonth\tfear\t0\nmonth\tjoy\t0\nmonth\tnegative\t0\nmonth\tpositive\t0\nmonth\tsadness\t0\nmonth\tsurprise\t0\nmonth\ttrust\t0\nmonthly\tanger\t0\nmonthly\tanticipation\t0\nmonthly\tdisgust\t0\nmonthly\tfear\t0\nmonthly\tjoy\t0\nmonthly\tnegative\t0\nmonthly\tpositive\t0\nmonthly\tsadness\t0\nmonthly\tsurprise\t0\nmonthly\ttrust\t0\nmonument\tanger\t0\nmonument\tanticipation\t0\nmonument\tdisgust\t0\nmonument\tfear\t0\nmonument\tjoy\t0\nmonument\tnegative\t0\nmonument\tpositive\t1\nmonument\tsadness\t0\nmonument\tsurprise\t0\nmonument\ttrust\t0\nmonumental\tanger\t0\nmonumental\tanticipation\t0\nmonumental\tdisgust\t0\nmonumental\tfear\t0\nmonumental\tjoy\t0\nmonumental\tnegative\t0\nmonumental\tpositive\t0\nmonumental\tsadness\t0\nmonumental\tsurprise\t0\nmonumental\ttrust\t0\nmoo\tanger\t0\nmoo\tanticipation\t0\nmoo\tdisgust\t0\nmoo\tfear\t0\nmoo\tjoy\t0\nmoo\tnegative\t0\nmoo\tpositive\t0\nmoo\tsadness\t0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rprise\t0\nmoronic\ttrust\t0\nmorphine\tanger\t0\nmorphine\tanticipation\t0\nmorphine\tdisgust\t0\nmorphine\tfear\t0\nmorphine\tjoy\t0\nmorphine\tnegative\t0\nmorphine\tpositive\t0\nmorphine\tsadness\t0\nmorphine\tsurprise\t0\nmorphine\ttrust\t0\nmorphism\tanger\t0\nmorphism\tanticipation\t0\nmorphism\tdisgust\t0\nmorphism\tfear\t0\nmorphism\tjoy\t0\nmorphism\tnegative\t0\nmorphism\tpositive\t0\nmorphism\tsadness\t0\nmorphism\tsurprise\t0\nmorphism\ttrust\t0\nmorphology\tanger\t0\nmorphology\tanticipation\t0\nmorphology\tdisgust\t0\nmorphology\tfear\t0\nmorphology\tjoy\t0\nmorphology\tnegative\t0\nmorphology\tpositive\t0\nmorphology\tsadness\t0\nmorphology\tsurprise\t0\nmorphology\ttrust\t0\nmorrow\tanger\t0\nmorrow\tanticipation\t1\nmorrow\tdisgust\t0\nmorrow\tfear\t0\nmorrow\tjoy\t0\nmorrow\tnegative\t0\nmorrow\tpositive\t0\nmorrow\tsadness\t0\nmorrow\tsurprise\t0\nmorrow\ttrust\t0\nmorsel\tanger\t0\nmorsel\tanticipation\t0\nmorsel\tdisgust\t0\nmorsel\tfear\t0\nmorsel\tjoy\t0\nmorsel\tnegative\t1\nmorsel\tpositive\t0\nmorsel\tsadness\t0\nmorsel\tsurprise\t0\nmorsel\ttrust\t0\nmortal\tanger\t0\nmortal\tanticipation\t0\nmortal\tdisgust\t0\nmortal\tfear\t0\nmortal\tjoy\t0\nmortal\tnegative\t1\nmortal\tpositive\t0\nmortal\tsadness\t0\nmortal\tsurprise\t0\nmortal\ttrust\t0\nmortality\tanger\t1\nmortality\tanticipation\t0\nmortality\tdisgust\t0\nmortality\tfear\t1\nmortality\tjoy\t0\nmortality\tnegative\t1\nmortality\tpositive\t0\nmortality\tsadness\t1\nmortality\tsurprise\t0\nmortality\ttrust\t0\nmortar\tanger\t0\nmortar\tanticipation\t0\nmortar\tdisgust\t0\nmortar\tfear\t0\nmortar\tjoy\t0\nmortar\tnegative\t0\nmortar\tpositive\t1\nmortar\tsadness\t0\nmortar\tsurprise\t0\nmortar\ttrust\t0\nmortgage\tanger\t0\nmortgage\tanticipation\t0\nmortgage\tdisgust\t0\nmortgage\tfear\t1\nmortgage\tjoy\t0\nmortgage\tnegative\t0\nmortgage\tpositive\t0\nmortgage\tsadness\t0\nmortgage\tsurprise\t0\nmortgage\ttrust\t0\nmortgagee\tanger\t0\nmortgagee\tanticipation\t0\nmortgagee\tdisgust\t0\nmortgagee\tfear\t0\nmortgagee\tjoy\t0\nmortgagee\tnegative\t0\nmortgagee\tpositive\t0\nmortgagee\tsadness\t0\nmortgagee\tsurprise\t0\nmortgagee\ttrust\t1\nmortgagor\tanger\t0\nmortgagor\tanticipation\t0\nmortgagor\tdisgust\t0\nmortgagor\tfear\t1\nmortgagor\tjoy\t0\nmortgagor\tnegative\t0\nmortgagor\tpositive\t0\nmortgagor\tsadness\t0\nmortgagor\tsurprise\t0\nmortgagor\ttrust\t0\nmortification\tanger\t0\nmortification\tanticipation\t1\nmortification\tdisgust\t1\nmortification\tfear\t1\nmortification\tjoy\t0\nmortification\tnegative\t1\nmortification\tpositive\t0\nmortification\tsadness\t1\nmortification\tsurprise\t0\nmortification\ttrust\t0\nmortuary\tanger\t0\nmortuary\tanticipation\t0\nmortuary\tdisgust\t0\nmortuary\tfear\t1\nmortuary\tjoy\t0\nmortuary\tnegative\t1\nmortuary\tpositive\t0\nmortuary\tsadness\t1\nmortuary\tsurprise\t0\nmortuary\ttrust\t0\nmosaic\tanger\t0\nmosaic\tanticipation\t0\nmosaic\tdisgust\t0\nmosaic\tfear\t0\nmosaic\tjoy\t0\nmosaic\tnegative\t0\nmosaic\tpositive\t0\nmosaic\tsadness\t0\nmosaic\tsurprise\t0\nmosaic\ttrust\t0\nmosque\tanger\t1\nmosque\tanticipation\t0\nmosque\tdisgust\t0\nmosque\tfear\t0\nmosque\tjoy\t0\nmosque\tnegative\t0\nmosque\tpositive\t0\nmosque\tsadness\t0\nmosque\tsurprise\t0\nmosque\ttrust\t0\nmosquito\tanger\t1\nmosquito\tanticipation\t0\nmosquito\tdisgust\t1\nmosquito\tfear\t0\nmosquito\tjoy\t0\nmosquito\tnegative\t1\nmosquito\tpositive\t0\nmosquito\tsadness\t0\nmosquito\tsurprise\t0\nmosquito\ttrust\t0\nmoss\tanger\t0\nmoss\tanticipation\t0\nmoss\tdisgust\t0\nmoss\tfear\t0\nmoss\tjoy\t0\nmoss\tnegative\t0\nmoss\tpositive\t0\nmoss\tsadness\t0\nmoss\tsurprise\t0\nmoss\ttrust\t0\nmossy\tanger\t0\nmossy\tanticipation\t0\nmossy\tdisgust\t0\nmossy\tfear\t0\nmossy\tjoy\t0\nmossy\tnegative\t0\nmossy\tpositive\t0\nmossy\tsadness\t0\nmossy\tsurprise\t0\nmossy\ttrust\t0\nmote\tanger\t0\nmote\tanticipation\t0\nmote\tdisgust\t0\nmote\tfear\t0\nmote\tjoy\t0\nmote\tnegative\t0\nmote\tpositive\t0\nmote\tsadness\t0\nmote\tsurprise\t0\nmote\ttrust\t0\nmoth\tanger\t0\nmoth\tanticipation\t0\nmoth\tdisgust\t0\nmoth\tfear\t0\nmoth\tjoy\t0\nmoth\tnegative\t0\nmoth\tpositive\t0\nmoth\tsadness\t0\nmoth\tsurprise\t0\nmoth\ttrust\t0\nmother\tanger\t0\nmother\tanticipation\t1\nmother\tdisgust\t0\nmother\tfear\t0\nmother\tjoy\t1\nmother\tnegative\t1\nmother\tpositive\t1\nmother\tsadness\t1\nmother\tsurprise\t0\nmother\ttrust\t1\nmotherhood\tanger\t0\nmotherhood\tanticipation\t0\nmotherhood\tdisgust\t0\nmotherhood\tfear\t0\nmotherhood\tjoy\t1\nmotherhood\tnegative\t0\nmotherhood\tpositive\t1\nmotherhood\tsadness\t0\nmotherhood\tsurprise\t0\nmotherhood\ttrust\t1\nmotion\tanger\t0\nmotion\tanticipation\t1\nmotion\tdisgust\t0\nmotion\tfear\t0\nmotion\tjoy\t0\nmotion\tnegative\t0\nmotion\tpositive\t0\nmotion\tsadness\t0\nmotion\tsurprise\t0\nmotion\ttrust\t0\nmotionless\tanger\t0\nmotionless\tanticipation\t0\nmotionless\tdisgust\t0\nmotionless\tfear\t0\nmotionless\tjoy\t0\nmotionless\tnegative\t0\nmotionless\tpositive\t0\nmotionless\tsadness\t0\nmotionless\tsurprise\t0\nmotionless\ttrust\t0\nmotive\tanger\t0\nmotive\tanticipation\t0\nmotive\tdisgust\t0\nmotive\tfear\t0\nmotive\tjoy\t0\nmotive\tnegative\t0\nmotive\tpositive\t1\nmotive\tsadness\t0\nmotive\tsurprise\t0\nmotive\ttrust\t0\nmotley\tanger\t0\nmotley\tanticipation\t0\nmotley\tdisgust\t0\nmotley\tfear\t0\nmotley\tjoy\t0\nmotley\tnegative\t0\nmotley\tpositive\t0\nmotley\tsadness\t0\nmotley\tsurprise\t0\nmotley\ttrust\t0\nmotor\tanger\t0\nmotor\tanticipation\t0\nmotor\tdisgust\t0\nmotor\tfear\t0\nmotor\tjoy\t0\nmotor\tnegative\t0\nmotor\tpositive\t0\nmotor\tsadness\t0\nmotor\tsurprise\t0\nmotor\ttrust\t0\nmotorbike\tanger\t0\nmotorbike\tanticipation\t0\nmotorbike\tdisgust\t0\nmotorbike\tfear\t0\nmotorbike\tjoy\t0\nmotorbike\tnegative\t0\nmotorbike\tpositive\t0\nmotorbike\tsadness\t0\nmotorbike\tsurprise\t0\nmotorbike\ttrust\t0\nmotorcycle\tanger\t0\nmotorcycle\tanticipation\t0\nmotorcycle\tdisgust\t0\nmotorcycle\tfear\t0\nmotorcycle\tjoy\t0\nmotorcycle\tnegative\t0\nmotorcycle\tpositive\t0\nmotorcycle\tsadness\t0\nmotorcycle\tsurprise\t0\nmotorcycle\ttrust\t0\nmotte\tanger\t0\nmotte\tanticipation\t0\nmotte\tdisgust\t0\nmotte\tfear\t0\nmotte\tjoy\t0\nmotte\tnegative\t0\nmotte\tpositive\t0\nmotte\tsadness\t0\nmotte\tsurprise\t0\nmotte\ttrust\t0\nmottled\tanger\t0\nmottled\tanticipation\t0\nmottled\tdisgust\t0\nmottled\tfear\t0\nmottled\tjoy\t0\nmottled\tnegative\t0\nmottled\tpositive\t0\nmottled\tsadness\t0\nmottled\tsurprise\t0\nmottled\ttrust\t0\nmotto\tanger\t0\nmotto\tanticipation\t0\nmotto\tdisgust\t0\nmotto\tfear\t0\nmotto\tjoy\t0\nmotto\tnegative\t0\nmotto\tpositive\t0\nmotto\tsadness\t0\nmotto\tsurprise\t0\nmotto\ttrust\t0\nmould\tanger\t0\nmould\tanticipation\t0\nmould\tdisgust\t0\nmould\tfear\t0\nmould\tjoy\t0\nmould\tnegative\t0\nmould\tpositive\t0\nmould\tsadness\t0\nmould\tsurprise\t0\nmould\ttrust\t0\nmound\tanger\t0\nmound\tanticipation\t0\nmound\tdisgust\t0\nmound\tfear\t0\nmound\tjoy\t0\nmound\tnegative\t0\nmound\tpositive\t0\nmound\tsadness\t0\nmound\tsurprise\t0\nmound\ttrust\t0\nmount\tanger\t0\nmount\tanticipation\t0\nmount\tdisgust\t0\nmount\tfear\t0\nmount\tjoy\t0\nmount\tnegative\t0\nmount\tpositive\t0\nmount\tsadness\t0\nmount\tsurprise\t0\nmount\ttrust\t0\nmountain\tanger\t0\nmountain\tanticipation\t1\nmountain\tdisgust\t0\nmountain\tfear\t0\nmountain\tjoy\t0\nmountain\tnegative\t0\nmountain\tpositive\t0\nmountain\tsadness\t0\nmountain\tsurprise\t0\nmountain\ttrust\t0\nmountaineer\tanger\t0\nmountaineer\tanticipation\t0\nmountaineer\tdisgust\t0\nmountaineer\tfear\t0\nmountaineer\tjoy\t0\nmountaineer\tnegative\t0\nmountaineer\tpositive\t0\nmountaineer\tsadness\t0\nmountaineer\tsurprise\t0\nmountaineer\ttrust\t0\nmountainous\tanger\t0\nmountainous\tanticipation\t0\nmountainous\tdisgust\t0\nmountainous\tfear\t0\nmountainous\tjoy\t0\nmountainous\tnegative\t0\nmountainous\tpositive\t0\nmountainous\tsadness\t0\nmountainous\tsurprise\t0\nmountainous\ttrust\t0\nmourn\tanger\t0\nmourn\tanticipation\t0\nmourn\tdisgust\t0\nmourn\tfear\t0\nmourn\tjoy\t0\nmourn\tnegative\t1\nmourn\tpositive\t0\nmourn\tsadness\t1\nmourn\tsurprise\t0\nmourn\ttrust\t0\nmournful\tanger\t1\nmournful\tanticipation\t0\nmournful\tdisgust\t0\nmournful\tfear\t1\nmournful\tjoy\t0\nmournful\tnegative\t1\nmournful\tpositive\t0\nmournful\tsadness\t1\nmournful\tsurprise\t0\nmournful\ttrust\t0\nmourning\tanger\t0\nmourning\tanticipation\t0\nmourning\tdisgust\t0\nmourning\tfear\t0\nmourning\tjoy\t0\nmourning\tnegative\t1\nmourning\tpositive\t0\nmourning\tsadness\t1\nmourning\tsurprise\t0\nmourning\ttrust\t0\nmouse\tanger\t0\nmouse\tanticipation\t0\nmouse\tdisgust\t0\nmouse\tfear\t0\nmouse\tjoy\t0\nmouse\tnegative\t0\nmouse\tpositive\t0\nmouse\tsadness\t0\nmouse\tsurprise\t0\nmouse\ttrust\t0\nmoustache\tanger\t0\nmoustache\tanticipation\t0\nmoustache\tdisgust\t0\nmoustache\tfear\t0\nmoustache\tjoy\t0\nmoustache\tnegative\t0\nmoustache\tpositive\t0\nmoustache\tsadness\t0\nmoustache\tsurprise\t0\nmoustache\ttrust\t0\nmouth\tanger\t0\nmouth\tanticipation\t0\nmouth\tdisgust\t0\nmouth\tfear\t0\nmouth\tjoy\t0\nmouth\tnegative\t0\nmouth\tpositive\t0\nmouth\tsadness\t0\nmouth\tsurprise\t1\nmouth\ttrust\t0\nmouthful\tanger\t0\nmouthful\tanticipation\t0\nmouthful\tdisgust\t1\nmouthful\tfear\t0\nmouthful\tjoy\t0\nmouthful\tnegative\t0\nmouthful\tpositive\t0\nmouthful\tsadness\t0\nmouthful\tsurprise\t0\nmouthful\ttrust\t0\nmouthpiece\tanger\t0\nmouthpiece\tanticipation\t0\nmouthpiece\tdisgust\t0\nmouthpiece\tfear\t0\nmouthpiece\tjoy\t0\nmouthpiece\tnegative\t0\nmouthpiece\tpositive\t0\nmouthpiece\tsadness\t0\nmouthpiece\tsurprise\t0\nmouthpiece\ttrust\t0\nmovable\tanger\t0\nmovable\tanticipation\t0\nmovable\tdisgust\t0\nmovable\tfear\t0\nmovable\tjoy\t0\nmovable\tnegative\t0\nmovable\tpositive\t1\nmovable\tsadness\t0\nmovable\tsurprise\t0\nmovable\ttrust\t0\nmove\tanger\t0\nmove\tanticipation\t0\nmove\tdisgust\t0\nmove\tfear\t0\nmove\tjoy\t0\nmove\tnegative\t0\nmove\tpositive\t0\nmove\tsadness\t0\nmove\tsurprise\t0\nmove\ttrust\t0\nmovement\tanger\t0\nmovement\tanticipation\t0\nmovement\tdisgust\t0\nmovement\tfear\t0\nmovement\tjoy\t0\nmovement\tnegative\t0\nmovement\tpositive\t0\nmovement\tsadness\t0\nmovement\tsurprise\t0\nmovement\ttrust\t0\nmover\tanger\t0\nmover\tanticipation\t0\nmover\tdisgust\t0\nmover\tfear\t0\nmover\tjoy\t0\nmover\tnegative\t0\nmover\tpositive\t1\nmover\tsadness\t0\nmover\tsurprise\t0\nmover\ttrust\t0\nmovie\tanger\t0\nmovie\tanticipation\t0\nmovie\tdisgust\t0\nmovie\tfear\t0\nmovie\tjoy\t0\nmovie\tnegative\t0\nmovie\tpositive\t0\nmovie\tsadness\t0\nmovie\tsurprise\t0\nmovie\ttrust\t0\nmoving\tanger\t0\nmoving\tanticipation\t0\nmoving\tdisgust\t0\nmoving\tfear\t0\nmoving\tjoy\t0\nmoving\tnegative\t0\nmoving\tpositive\t0\nmoving\tsadness\t0\nmoving\tsurprise\t0\nmoving\ttrust\t0\nmow\tanger\t0\nmow\tanticipation\t0\nmow\tdisgust\t0\nmow\tfear\t0\nmow\tjoy\t0\nmow\tnegative\t0\nmow\tpositive\t0\nmow\tsadness\t0\nmow\tsurprise\t0\nmow\ttrust\t0\nmuck\tanger\t0\nmuck\tanticipation\t0\nmuck\tdisgust\t1\nmuck\tfear\t0\nmuck\tjoy\t0\nmuck\tnegative\t1\nmuck\tpositive\t0\nmuck\tsadness\t0\nmuck\tsurprise\t0\nmuck\ttrust\t0\nmucous\tanger\t0\nmucous\tanticipation\t0\nmucous\tdisgust\t1\nmucous\tfear\t0\nmucous\tjoy\t0\nmucous\tnegative\t0\nmucous\tpositive\t0\nmucous\tsadness\t0\nmucous\tsurprise\t0\nmucous\ttrust\t0\nmucus\tanger\t0\nmucus\tanticipation\t0\nmucus\tdisgust\t1\nmucus\tfear\t0\nmucus\tjoy\t0\nmucus\tnegative\t0\nmucus\tpositive\t0\nmucus\tsadness\t0\nmucus\tsurprise\t0\nmucus\ttrust\t0\nmud\tanger\t0\nmud\tanticipation\t0\nmud\tdisgust\t0\nmud\tfear\t0\nmud\tjoy\t0\nmud\tnegative\t1\nmud\tpositive\t0\nmud\tsadness\t0\nmud\tsurprise\t0\nmud\ttrust\t0\nmuddle\tanger\t0\nmuddle\tanticipation\t0\nmuddle\tdisgust\t0\nmuddle\tfear\t0\nmuddle\tjoy\t0\nmuddle\tnegative\t1\nmuddle\tpositive\t0\nmuddle\tsadness\t0\nmuddle\tsurprise\t0\nmuddle\ttrust\t0\nmuddled\tanger\t0\nmuddled\tanticipation\t0\nmuddled\tdisgust\t0\nmuddled\tfear\t0\nmuddled\tjoy\t0\nmuddled\tnegative\t1\nmuddled\tpositive\t0\nmuddled\tsadness\t0\nmuddled\tsurprise\t0\nmuddled\ttrust\t0\nmuddy\tanger\t0\nmuddy\tanticipation\t0\nmuddy\tdisgust\t1\nmuddy\tfear\t0\nmuddy\tjoy\t0\nmuddy\tnegative\t1\nmuddy\tpositive\t0\nmuddy\tsadness\t0\nmuddy\tsurprise\t0\nmuddy\ttrust\t0\nmuff\tanger\t1\nmuff\tanticipation\t0\nmuff\tdisgust\t1\nmuff\tfear\t0\nmuff\tjoy\t0\nmuff\tnegative\t1\nmuff\tpositive\t0\nmuff\tsadness\t0\nmuff\tsurprise\t0\nmuff\ttrust\t0\nmuffled\tanger\t0\nmuffled\tanticipation\t0\nmuffled\tdisgust\t0\nmuffled\tfear\t0\nmuffled\tjoy\t0\nmuffled\tnegative\t0\nmuffled\tpositive\t0\nmuffled\tsadness\t0\nmuffled\tsurprise\t0\nmuffled\ttrust\t0\nmuffler\tanger\t0\nmuffler\tanticipation\t0\nmuffler\tdisgust\t0\nmuffler\tfear\t0\nmuffler\tjoy\t0\nmuffler\tnegative\t0\nmuffler\tpositive\t0\nmuffler\tsadness\t0\nmuffler\tsurprise\t0\nmuffler\ttrust\t0\nmug\tanger\t1\nmug\tanticipation\t0\nmug\tdisgust\t0\nmug\tfear\t1\nmug\tjoy\t0\nmug\tnegative\t1\nmug\tpositive\t1\nmug\tsadness\t1\nmug\tsurprise\t0\nmug\ttrust\t0\nmule\tanger\t1\nmule\tanticipation\t0\nmule\tdisgust\t0\nmule\tfear\t0\nmule\tjoy\t0\nmule\tnegative\t1\nmule\tpositive\t0\nmule\tsadness\t0\nmule\tsurprise\t0\nmule\ttrust\t1\nmultilateral\tanger\t0\nmultilateral\tanticipation\t0\nmultilateral\tdisgust\t0\nmultilateral\tfear\t0\nmultilateral\tjoy\t0\nmultilateral\tnegative\t0\nmultilateral\tpositive\t0\nmultilateral\tsadness\t0\nmultilateral\tsurprise\t0\nmultilateral\ttrust\t0\nmultiple\tanger\t0\nmultiple\tanticipation\t0\nmultiple\tdisgust\t0\nmultiple\tfear\t0\nmultiple\tjoy\t0\nmultiple\tnegative\t0\nmultiple\tpositive\t0\nmultiple\tsadness\t0\nmultiple\tsurprise\t0\nmultiple\ttrust\t0\nmultiplex\tanger\t0\nmultiplex\tanticipation\t0\nmultiplex\tdisgust\t0\nmultiplex\tfear\t0\nmultiplex\tjoy\t0\nmultiplex\tnegative\t0\nmultiplex\tpositive\t0\nmultiplex\tsadness\t0\nmultiplex\tsurprise\t0\nmultiplex\ttrust\t0\nmultiplication\tanger\t0\nmultiplication\tanticipation\t0\nmultiplication\tdisgust\t0\nmultiplication\tfear\t0\nmultiplication\tjoy\t0\nmultiplication\tnegative\t0\nmultiplication\tpositive\t0\nmultiplication\tsadness\t0\nmultiplication\tsurprise\t0\nmultiplication\ttrust\t0\nmultiplicity\tanger\t0\nmultiplicity\tanticipation\t0\nmultiplicity\tdisgust\t0\nmultiplicity\tfear\t0\nmultiplicity\tjoy\t0\nmultiplicity\tnegative\t0\nmultiplicity\tpositive\t0\nmultiplicity\tsadness\t0\nmultiplicity\tsurprise\t0\nmultiplicity\ttrust\t0\nmultiplied\tanger\t0\nmultiplied\tanticipation\t0\nmultiplied\tdisgust\t0\nmultiplied\tfear\t0\nmultiplied\tjoy\t0\nmultiplied\tnegative\t0\nmultiplied\tpositive\t0\nmultiplied\tsadness\t0\nmultiplied\tsurprise\t0\nmultiplied\ttrust\t0\nmultiplier\tanger\t0\nmultiplier\tanticipation\t0\nmultiplier\tdisgust\t0\nmultiplier\tfear\t0\nmultiplier\tjoy\t0\nmultiplier\tnegative\t0\nmultiplier\tpositive\t0\nmultiplier\tsadness\t0\nmultiplier\tsurprise\t0\nmultiplier\ttrust\t0\nmultiply\tanger\t0\nmultiply\tanticipation\t0\nmultiply\tdisgust\t0\nmultiply\tfear\t0\nmultiply\tjoy\t0\nmultiply\tnegative\t0\nmultiply\tpositive\t0\nmultiply\tsadness\t0\nmultiply\tsurprise\t0\nmultiply\ttrust\t0\nmultitude\tanger\t0\nmultitude\tanticipation\t0\nmultitude\tdisgust\t0\nmultitude\tfear\t0\nmultitude\tjoy\t0\nmultitude\tnegative\t0\nmultitude\tpositive\t0\nmultitude\tsadness\t0\nmultitude\tsurprise\t0\nmultitude\ttrust\t0\nmum\tanger\t0\nmum\tanticipation\t0\nmum\tdisgust\t0\nmum\tfear\t1\nmum\tjoy\t0\nmum\tnegative\t1\nmum\tpositive\t0\nmum\tsadness\t0\nmum\tsurprise\t0\nmum\ttrust\t0\nmumble\tanger\t0\nmumble\tanticipation\t0\nmumble\tdisgust\t0\nmumble\tfear\t0\nmumble\tjoy\t0\nmumble\tnegative\t1\nmumble\tpositive\t0\nmumble\tsadness\t0\nmumble\tsurprise\t0\nmumble\ttrust\t0\nmummy\tanger\t0\nmummy\tanticipation\t0\nmummy\tdisgust\t0\nmummy\tfear\t0\nmummy\tjoy\t0\nmummy\tnegative\t0\nmummy\tpositive\t0\nmummy\tsadness\t0\nmummy\tsurprise\t0\nmummy\ttrust\t0\nmumps\tanger\t0\nmumps\tanticipation\t0\nmumps\tdisgust\t0\nmumps\tfear\t0\nmumps\tjoy\t0\nmumps\tnegative\t1\nmumps\tpositive\t0\nmumps\tsadness\t0\nmumps\tsurprise\t0\nmumps\ttrust\t0\nmunch\tanger\t0\nmunch\tanticipation\t0\nmunch\tdisgust\t0\nmunch\tfear\t0\nmunch\tjoy\t0\nmunch\tnegative\t0\nmunch\tpositive\t0\nmunch\tsadness\t0\nmunch\tsurprise\t0\nmunch\ttrust\t0\nmundane\tanger\t0\nmundane\tanticipation\t0\nmundane\tdisgust\t0\nmundane\tfear\t0\nmundane\tjoy\t0\nmundane\tnegative\t0\nmundane\tpositive\t0\nmundane\tsadness\t0\nmundane\tsurprise\t0\nmundane\ttrust\t0\nmunicipal\tanger\t0\nmunicipal\tanticipation\t0\nmunicipal\tdisgust\t0\nmunicipal\tfear\t0\nmunicipal\tjoy\t0\nmunicipal\tnegative\t0\nmunicipal\tpositive\t0\nmunicipal\tsadness\t0\nmunicipal\tsurprise\t0\nmunicipal\ttrust\t0\nmunicipality\tanger\t0\nmunicipality\tanticipation\t0\nmunicipality\tdisgust\t0\nmunicipality\tfear\t0\nmunicipality\tjoy\t0\nmunicipality\tnegative\t0\nmunicipality\tpositive\t0\nmunicipality\tsadness\t0\nmunicipality\tsurprise\t0\nmunicipality\ttrust\t0\nmural\tanger\t0\nmural\tanticipation\t0\nmural\tdisgust\t0\nmural\tfear\t0\nmural\tjoy\t0\nmural\tnegative\t0\nmural\tpositive\t0\nmural\tsadness\t0\nmural\tsurprise\t0\nmural\ttrust\t0\nmurder\tanger\t1\nmurder\tanticipation\t0\nmurder\tdisgust\t1\nmurder\tfear\t1\nmurder\tjoy\t0\nmurder\tnegative\t1\nmurder\tpositive\t0\nmurder\tsadness\t1\nmurder\tsurprise\t1\nmurder\ttrust\t0\nmurderer\tanger\t1\nmurderer\tanticipation\t0\nmurderer\tdisgust\t1\nmurderer\tfear\t1\nmurderer\tjoy\t0\nmurderer\tnegative\t1\nmurderer\tpositive\t0\nmurderer\tsadness\t1\nmurderer\tsurprise\t0\nmurderer\ttrust\t0\nmurderous\tanger\t1\nmurderous\tanticipation\t0\nmurderous\tdisgust\t1\nmurderous\tfear\t1\nmurderous\tjoy\t0\nmurderous\tnegative\t1\nmurderous\tpositive\t0\nmurderous\tsadness\t1\nmurderous\tsurprise\t1\nmurderous\ttrust\t0\nmurky\tanger\t0\nmurky\tanticipation\t0\nmurky\tdisgust\t1\nmurky\tfear\t0\nmurky\tjoy\t0\nmurky\tnegative\t1\nmurky\tpositive\t0\nmurky\tsadness\t1\nmurky\tsurprise\t0\nmurky\ttrust\t0\nmurmur\tanger\t0\nmurmur\tanticipation\t0\nmurmur\tdisgust\t0\nmurmur\tfear\t0\nmurmur\tjoy\t0\nmurmur\tnegative\t0\nmurmur\tpositive\t0\nmurmur\tsadness\t0\nmurmur\tsurprise\t0\nmurmur\ttrust\t0\nmuscle\tanger\t0\nmuscle\tanticipation\t0\nmuscle\tdisgust\t0\nmuscle\tfear\t0\nmuscle\tjoy\t0\nmuscle\tnegative\t0\nmuscle\tpositive\t0\nmuscle\tsadness\t0\nmuscle\tsurprise\t0\nmuscle\ttrust\t0\nmuscular\tanger\t0\nmuscular\tanticipation\t0\nmuscular\tdisgust\t0\nmuscular\tfear\t0\nmuscular\tjoy\t0\nmuscular\tnegative\t0\nmuscular\tpositive\t1\nmuscular\tsadness\t0\nmuscular\tsurprise\t0\nmuscular\ttrust\t0\nmuse\tanger\t0\nmuse\tanticipation\t0\nmuse\tdisgust\t0\nmuse\tfear\t0\nmuse\tjoy\t0\nmuse\tnegative\t0\nmuse\tpositive\t0\nmuse\tsadness\t0\nmuse\tsurprise\t0\nmuse\ttrust\t0\nmuses\tanger\t0\nmuses\tanticipation\t0\nmuses\tdisgust\t0\nmuses\tfear\t0\nmuses\tjoy\t0\nmuses\tnegative\t0\nmuses\tpositive\t0\nmuses\tsadness\t0\nmuses\tsurprise\t0\nmuses\ttrust\t0\nmuseum\tanger\t0\nmuseum\tanticipation\t0\nmuseum\tdisgust\t0\nmuseum\tfear\t0\nmuseum\tjoy\t0\nmuseum\tnegative\t0\nmuseum\tpositive\t0\nmuseum\tsadness\t0\nmuseum\tsurprise\t0\nmuseum\ttrust\t0\nmush\tanger\t0\nmush\tanticipation\t0\nmush\tdisgust\t0\nmush\tfear\t0\nmush\tjoy\t0\nmush\tnegative\t0\nmush\tpositive\t0\nmush\tsadness\t0\nmush\tsurprise\t0\nmush\ttrust\t0\nmushroom\tanger\t0\nmushroom\tanticipation\t0\nmushroom\tdisgust\t0\nmushroom\tfear\t0\nmushroom\tjoy\t0\nmushroom\tnegative\t0\nmushroom\tpositive\t0\nmushroom\tsadness\t0\nmushroom\tsurprise\t0\nmushroom\ttrust\t0\nmusic\tanger\t0\nmusic\tanticipation\t0\nmusic\tdisgust\t0\nmusic\tfear\t0\nmusic\tjoy\t1\nmusic\tnegative\t0\nmusic\tpositive\t1\nmusic\tsadness\t1\nmusic\tsurprise\t0\nmusic\ttrust\t0\nmusical\tanger\t1\nmusical\tanticipation\t1\nmusical\tdisgust\t0\nmusical\tfear\t0\nmusical\tjoy\t1\nmusical\tnegative\t0\nmusical\tpositive\t1\nmusical\tsadness\t1\nmusical\tsurprise\t1\nmusical\ttrust\t1\nmusician\tanger\t0\nmusician\tanticipation\t0\nmusician\tdisgust\t0\nmusician\tfear\t0\nmusician\tjoy\t0\nmusician\tnegative\t0\nmusician\tpositive\t0\nmusician\tsadness\t0\nmusician\tsurprise\t0\nmusician\ttrust\t0\nmusing\tanger\t0\nmusing\tanticipation\t0\nmusing\tdisgust\t0\nmusing\tfear\t0\nmusing\tjoy\t0\nmusing\tnegative\t0\nmusing\tpositive\t0\nmusing\tsadness\t0\nmusing\tsurprise\t0\nmusing\ttrust\t0\nmusk\tanger\t0\nmusk\tanticipation\t0\nmusk\tdisgust\t0\nmusk\tfear\t0\nmusk\tjoy\t0\nmusk\tnegative\t0\nmusk\tpositive\t0\nmusk\tsadness\t0\nmusk\tsurprise\t0\nmusk\ttrust\t0\nmusket\tanger\t0\nmusket\tanticipation\t0\nmusket\tdisgust\t0\nmusket\tfear\t1\nmusket\tjoy\t0\nmusket\tnegative\t0\nmusket\tpositive\t0\nmusket\tsadness\t0\nmusket\tsurprise\t0\nmusket\ttrust\t0\nmuslin\tanger\t0\nmuslin\tanticipation\t0\nmuslin\tdisgust\t0\nmuslin\tfear\t0\nmuslin\tjoy\t0\nmuslin\tnegative\t0\nmuslin\tpositive\t0\nmuslin\tsadness\t0\nmuslin\tsurprise\t0\nmuslin\ttrust\t0\nmuss\tanger\t0\nmuss\tanticipation\t0\nmuss\tdisgust\t0\nmuss\tfear\t0\nmuss\tjoy\t0\nmuss\tnegative\t1\nmuss\tpositive\t0\nmuss\tsadness\t0\nmuss\tsurprise\t0\nmuss\ttrust\t0\nmustang\tanger\t0\nmustang\tanticipation\t0\nmustang\tdisgust\t0\nmustang\tfear\t0\nmustang\tjoy\t0\nmustang\tnegative\t0\nmustang\tpositive\t0\nmustang\tsadness\t0\nmustang\tsurprise\t0\nmustang\ttrust\t0\nmustard\tanger\t0\nmustard\tanticipation\t0\nmustard\tdisgust\t0\nmustard\tfear\t0\nmustard\tjoy\t0\nmustard\tnegative\t0\nmustard\tpositive\t0\nmustard\tsadness\t0\nmustard\tsurprise\t0\nmustard\ttrust\t0\nmuster\tanger\t0\nmuster\tanticipation\t0\nmuster\tdisgust\t0\nmuster\tfear\t0\nmuster\tjoy\t0\nmuster\tnegative\t0\nmuster\tpositive\t0\nmuster\tsadness\t0\nmuster\tsurprise\t0\nmuster\ttrust\t0\nmusty\tanger\t0\nmusty\tanticipation\t0\nmusty\tdisgust\t1\nmusty\tfear\t0\nmusty\tjoy\t0\nmusty\tnegative\t1\nmusty\tpositive\t0\nmusty\tsadness\t0\nmusty\tsurprise\t0\nmusty\ttrust\t0\nmutable\tanger\t0\nmutable\tanticipation\t1\nmutable\tdisgust\t0\nmutable\tfear\t0\nmutable\tjoy\t0\nmutable\tnegative\t0\nmutable\tpositive\t1\nmutable\tsadness\t0\nmutable\tsurprise\t0\nmutable\ttrust\t0\nmutant\tanger\t0\nmutant\tanticipation\t0\nmutant\tdisgust\t0\nmutant\tfear\t0\nmutant\tjoy\t0\nmutant\tnegative\t1\nmutant\tpositive\t0\nmutant\tsadness\t0\nmutant\tsurprise\t0\nmutant\ttrust\t0\nmutation\tanger\t0\nmutation\tanticipation\t0\nmutation\tdisgust\t0\nmutation\tfear\t0\nmutation\tjoy\t0\nmutation\tnegative\t0\nmutation\tpositive\t0\nmutation\tsadness\t0\nmutation\tsurprise\t0\nmutation\ttrust\t0\nmutilated\tanger\t0\nmutilated\tanticipation\t0\nmutilated\tdisgust\t1\nmutilated\tfear\t0\nmutilated\tjoy\t0\nmutilated\tnegative\t1\nmutilated\tpositive\t0\nmutilated\tsadness\t0\nmutilated\tsurprise\t0\nmutilated\ttrust\t0\nmutilation\tanger\t1\nmutilation\tanticipation\t0\nmutilation\tdisgust\t1\nmutilation\tfear\t1\nmutilation\tjoy\t0\nmutilation\tnegative\t1\nmutilation\tpositive\t0\nmutilation\tsadness\t1\nmutilation\tsurprise\t0\nmutilation\ttrust\t0\nmutiny\tanger\t1\nmutiny\tanticipation\t0\nmutiny\tdisgust\t1\nmutiny\tfear\t1\nmutiny\tjoy\t0\nmutiny\tnegative\t1\nmutiny\tpositive\t0\nmutiny\tsadness\t0\nmutiny\tsurprise\t1\nmutiny\ttrust\t0\nmutter\tanger\t1\nmutter\tanticipation\t0\nmutter\tdisgust\t0\nmutter\tfear\t0\nmutter\tjoy\t0\nmutter\tnegative\t1\nmutter\tpositive\t0\nmutter\tsadness\t0\nmutter\tsurprise\t0\nmutter\ttrust\t0\nmutton\tanger\t0\nmutton\tanticipation\t0\nmutton\tdisgust\t0\nmutton\tfear\t0\nmutton\tjoy\t0\nmutton\tnegative\t0\nmutton\tpositive\t0\nmutton\tsadness\t0\nmutton\tsurprise\t0\nmutton\ttrust\t0\nmutual\tanger\t0\nmutual\tanticipation\t0\nmutual\tdisgust\t0\nmutual\tfear\t0\nmutual\tjoy\t0\nmutual\tnegative\t0\nmutual\tpositive\t1\nmutual\tsadness\t0\nmutual\tsurprise\t0\nmutual\ttrust\t0\nmutually\tanger\t0\nmutually\tanticipation\t0\nmutually\tdisgust\t0\nmutually\tfear\t0\nmutually\tjoy\t0\nmutually\tnegative\t0\nmutually\tpositive\t0\nmutually\tsadness\t0\nmutually\tsurprise\t0\nmutually\ttrust\t0\nmuzzle\tanger\t0\nmuzzle\tanticipation\t0\nmuzzle\tdisgust\t0\nmuzzle\tfear\t1\nmuzzle\tjoy\t0\nmuzzle\tnegative\t1\nmuzzle\tpositive\t0\nmuzzle\tsadness\t0\nmuzzle\tsurprise\t0\nmuzzle\ttrust\t0\nmyopia\tanger\t1\nmyopia\tanticipation\t0\nmyopia\tdisgust\t0\nmyopia\tfear\t0\nmyopia\tjoy\t0\nmyopia\tnegative\t1\nmyopia\tpositive\t0\nmyopia\tsadness\t1\nmyopia\tsurprise\t0\nmyopia\ttrust\t0\nmyopic\tanger\t0\nmyopic\tanticipation\t0\nmyopic\tdisgust\t0\nmyopic\tfear\t0\nmyopic\tjoy\t0\nmyopic\tnegative\t0\nmyopic\tpositive\t0\nmyopic\tsadness\t0\nmyopic\tsurprise\t0\nmyopic\ttrust\t0\nmyriad\tanger\t0\nmyriad\tanticipation\t0\nmyriad\tdisgust\t0\nmyriad\tfear\t0\nmyriad\tjoy\t0\nmyriad\tnegative\t0\nmyriad\tpositive\t0\nmyriad\tsadness\t0\nmyriad\tsurprise\t0\nmyriad\ttrust\t0\nmysterious\tanger\t0\nmysterious\tanticipation\t1\nmysterious\tdisgust\t0\nmysterious\tfear\t1\nmysterious\tjoy\t0\nmysterious\tnegative\t0\nmysterious\tpositive\t0\nmysterious\tsadne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ralize\tnegative\t0\nneutralize\tpositive\t0\nneutralize\tsadness\t0\nneutralize\tsurprise\t0\nneutralize\ttrust\t0\nnewborn\tanger\t0\nnewborn\tanticipation\t0\nnewborn\tdisgust\t0\nnewborn\tfear\t0\nnewborn\tjoy\t0\nnewborn\tnegative\t0\nnewborn\tpositive\t0\nnewborn\tsadness\t0\nnewborn\tsurprise\t0\nnewborn\ttrust\t0\nnewcomer\tanger\t0\nnewcomer\tanticipation\t0\nnewcomer\tdisgust\t0\nnewcomer\tfear\t1\nnewcomer\tjoy\t0\nnewcomer\tnegative\t0\nnewcomer\tpositive\t0\nnewcomer\tsadness\t0\nnewcomer\tsurprise\t1\nnewcomer\ttrust\t0\nnewly\tanger\t0\nnewly\tanticipation\t0\nnewly\tdisgust\t0\nnewly\tfear\t0\nnewly\tjoy\t0\nnewly\tnegative\t0\nnewly\tpositive\t0\nnewly\tsadness\t0\nnewly\tsurprise\t0\nnewly\ttrust\t0\nnewness\tanger\t0\nnewness\tanticipation\t0\nnewness\tdisgust\t0\nnewness\tfear\t0\nnewness\tjoy\t0\nnewness\tnegative\t0\nnewness\tpositive\t0\nnewness\tsadness\t0\nnewness\tsurprise\t0\nnewness\ttrust\t0\nnews\tanger\t0\nnews\tanticipation\t0\nnews\tdisgust\t0\nnews\tfear\t0\nnews\tjoy\t0\nnews\tnegative\t0\nnews\tpositive\t0\nnews\tsadness\t0\nnews\tsurprise\t0\nnews\ttrust\t0\nnewspaper\tanger\t0\nnewspaper\tanticipation\t0\nnewspaper\tdisgust\t0\nnewspaper\tfear\t0\nnewspaper\tjoy\t0\nnewspaper\tnegative\t0\nnewspaper\tpositive\t0\nnewspaper\tsadness\t0\nnewspaper\tsurprise\t0\nnewspaper\ttrust\t0\nnewsstand\tanger\t0\nnewsstand\tanticipation\t0\nnewsstand\tdisgust\t0\nnewsstand\tfear\t0\nnewsstand\tjoy\t0\nnewsstand\tnegative\t0\nnewsstand\tpositive\t0\nnewsstand\tsadness\t0\nnewsstand\tsurprise\t0\nnewsstand\ttrust\t0\nnib\tanger\t0\nnib\tanticipation\t0\nnib\tdisgust\t0\nnib\tfear\t0\nnib\tjoy\t0\nnib\tnegative\t0\nnib\tpositive\t0\nnib\tsadness\t0\nnib\tsurprise\t0\nnib\ttrust\t0\nnibble\tanger\t0\nnibble\tanticipation\t0\nnibble\tdisgust\t0\nnibble\tfear\t0\nnibble\tjoy\t0\nnibble\tnegative\t0\nnibble\tpositive\t0\nnibble\tsadness\t0\nnibble\tsurprise\t0\nnibble\ttrust\t0\nniche\tanger\t0\nniche\tanticipation\t0\nniche\tdisgust\t0\nniche\tfear\t0\nniche\tjoy\t0\nniche\tnegative\t0\nniche\tpositive\t0\nniche\tsadness\t0\nniche\tsurprise\t0\nniche\ttrust\t0\nnichts\tanger\t0\nnichts\tanticipation\t0\nnichts\tdisgust\t0\nnichts\tfear\t0\nnichts\tjoy\t0\nnichts\tnegative\t0\nnichts\tpositive\t0\nnichts\tsadness\t0\nnichts\tsurprise\t0\nnichts\ttrust\t0\nnick\tanger\t0\nnick\tanticipation\t0\nnick\tdisgust\t0\nnick\tfear\t0\nnick\tjoy\t0\nnick\tnegative\t0\nnick\tpositive\t0\nnick\tsadness\t0\nnick\tsurprise\t0\nnick\ttrust\t0\nnickel\tanger\t0\nnickel\tanticipation\t0\nnickel\tdisgust\t0\nnickel\tfear\t0\nnickel\tjoy\t0\nnickel\tnegative\t0\nnickel\tpositive\t0\nnickel\tsadness\t0\nnickel\tsurprise\t0\nnickel\ttrust\t0\nnickname\tanger\t0\nnickname\tanticipation\t0\nnickname\tdisgust\t0\nnickname\tfear\t0\nnickname\tjoy\t0\nnickname\tnegative\t0\nnickname\tpositive\t0\nnickname\tsadness\t0\nnickname\tsurprise\t0\nnickname\ttrust\t0\nnicotine\tanger\t0\nnicotine\tanticipation\t0\nnicotine\tdisgust\t1\nnicotine\tfear\t0\nnicotine\tjoy\t0\nnicotine\tnegative\t1\nnicotine\tpositive\t0\nnicotine\tsadness\t0\nnicotine\tsurprise\t0\nnicotine\ttrust\t0\nniece\tanger\t0\nniece\tanticipation\t0\nniece\tdisgust\t0\nniece\tfear\t0\nniece\tjoy\t0\nniece\tnegative\t0\nniece\tpositive\t0\nniece\tsadness\t0\nniece\tsurprise\t0\nniece\ttrust\t0\nnigger\tanger\t0\nnigger\tanticipation\t0\nnigger\tdisgust\t0\nnigger\tfear\t0\nnigger\tjoy\t0\nnigger\tnegative\t1\nnigger\tpositive\t0\nnigger\tsadness\t0\nnigger\tsurprise\t0\nnigger\ttrust\t0\nnigh\tanger\t0\nnigh\tanticipation\t0\nnigh\tdisgust\t0\nnigh\tfear\t0\nnigh\tjoy\t0\nnigh\tnegative\t0\nnigh\tpositive\t0\nnigh\tsadness\t0\nnigh\tsurprise\t0\nnigh\ttrust\t0\nnight\tanger\t0\nnight\tanticipation\t0\nnight\tdisgust\t0\nnight\tfear\t0\nnight\tjoy\t0\nnight\tnegative\t0\nnight\tpositive\t0\nnight\tsadness\t0\nnight\tsurprise\t0\nnight\ttrust\t0\nnightfall\tanger\t0\nnightfall\tanticipation\t0\nnightfall\tdisgust\t0\nnightfall\tfear\t0\nnightfall\tjoy\t0\nnightfall\tnegative\t0\nnightfall\tpositive\t0\nnightfall\tsadness\t0\nnightfall\tsurprise\t0\nnightfall\ttrust\t0\nnightingale\tanger\t0\nnightingale\tanticipation\t0\nnightingale\tdisgust\t0\nnightingale\tfear\t0\nnightingale\tjoy\t0\nnightingale\tnegative\t0\nnightingale\tpositive\t0\nnightingale\tsadness\t0\nnightingale\tsurprise\t0\nnightingale\ttrust\t0\nnightmare\tanger\t0\nnightmare\tanticipation\t0\nnightmare\tdisgust\t0\nnightmare\tfear\t1\nnightmare\tjoy\t0\nnightmare\tnegative\t1\nnightmare\tpositive\t0\nnightmare\tsadness\t0\nnightmare\tsurprise\t0\nnightmare\ttrust\t0\nnihilism\tanger\t0\nnihilism\tanticipation\t0\nnihilism\tdisgust\t0\nnihilism\tfear\t0\nnihilism\tjoy\t0\nnihilism\tnegative\t1\nnihilism\tpositive\t0\nnihilism\tsadness\t0\nnihilism\tsurprise\t0\nnihilism\ttrust\t0\nnil\tanger\t0\nnil\tanticipation\t0\nnil\tdisgust\t0\nnil\tfear\t0\nnil\tjoy\t0\nnil\tnegative\t0\nnil\tpositive\t0\nnil\tsadness\t0\nnil\tsurprise\t0\nnil\ttrust\t0\nnimble\tanger\t0\nnimble\tanticipation\t0\nni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ise\t0\nobjection\ttrust\t0\nobjectionable\tanger\t0\nobjectionable\tanticipation\t0\nobjectionable\tdisgust\t0\nobjectionable\tfear\t0\nobjectionable\tjoy\t0\nobjectionable\tnegative\t1\nobjectionable\tpositive\t0\nobjectionable\tsadness\t0\nobjectionable\tsurprise\t0\nobjectionable\ttrust\t0\nobjective\tanger\t0\nobjective\tanticipation\t1\nobjective\tdisgust\t0\nobjective\tfear\t0\nobjective\tjoy\t0\nobjective\tnegative\t0\nobjective\tpositive\t1\nobjective\tsadness\t0\nobjective\tsurprise\t0\nobjective\ttrust\t1\nobligation\tanger\t0\nobligation\tanticipation\t0\nobligation\tdisgust\t0\nobligation\tfear\t0\nobligation\tjoy\t0\nobligation\tnegative\t0\nobligation\tpositive\t0\nobligation\tsadness\t0\nobligation\tsurprise\t0\nobligation\ttrust\t0\nobligatory\tanger\t0\nobligatory\tanticipation\t0\nobligatory\tdisgust\t0\nobligatory\tfear\t0\nobligatory\tjoy\t0\nobligatory\tnegative\t0\nobligatory\tpositive\t0\nobligatory\tsadness\t0\nobligatory\tsurprise\t0\nobligatory\ttrust\t0\noblige\tanger\t0\noblige\tanticipation\t0\noblige\tdisgust\t0\noblige\tfear\t0\noblige\tjoy\t0\noblige\tnegative\t1\noblige\tpositive\t0\noblige\tsadness\t0\noblige\tsurprise\t0\noblige\ttrust\t1\nobliged\tanger\t0\nobliged\tanticipation\t0\nobliged\tdisgust\t0\nobliged\tfear\t0\nobliged\tjoy\t0\nobliged\tnegative\t0\nobliged\tpositive\t0\nobliged\tsadness\t0\nobliged\tsurprise\t0\nobliged\ttrust\t0\nobliging\tanger\t1\nobliging\tanticipation\t1\nobliging\tdisgust\t1\nobliging\tfear\t1\nobliging\tjoy\t1\nobliging\tnegative\t0\nobliging\tpositive\t1\nobliging\tsadness\t0\nobliging\tsurprise\t1\nobliging\ttrust\t1\nobligor\tanger\t0\nobligor\tanticipation\t0\nobligor\tdisgust\t0\nobligor\tfear\t1\nobligor\tjoy\t0\nobligor\tnegative\t1\nobligor\tpositive\t0\nobligor\tsadness\t0\nobligor\tsurprise\t0\nobligor\ttrust\t0\noblique\tanger\t0\noblique\tanticipation\t0\noblique\tdisgust\t0\noblique\tfear\t0\noblique\tjoy\t0\noblique\tnegative\t0\noblique\tpositive\t0\noblique\tsadness\t0\noblique\tsurprise\t0\noblique\ttrust\t0\nobliterate\tanger\t1\nobliterate\tanticipation\t0\nobliterate\tdisgust\t0\nobliterate\tfear\t1\nobliterate\tjoy\t0\nobliterate\tnegative\t1\nobliterate\tpositive\t0\nobliterate\tsadness\t1\nobliterate\tsurprise\t0\nobliterate\ttrust\t0\nobliterated\tanger\t1\nobliterated\tanticipation\t0\nobliterated\tdisgust\t0\nobliterated\tfear\t1\nobliterated\tjoy\t0\nobliterated\tnegative\t1\nobliterated\tpositive\t0\nobliterated\tsadness\t0\nobliterated\tsurprise\t0\nobliterated\ttrust\t0\nobliteration\tanger\t0\nobliteration\tanticipation\t0\nobliteration\tdisgust\t0\nobliteration\tfear\t1\nobliteration\tjoy\t0\nobliteration\tnegative\t1\nobliteration\tpositive\t0\nobliteration\tsadness\t1\nobliteration\tsurprise\t0\nobliteration\ttrust\t0\noblivion\tanger\t1\noblivion\tanticipation\t0\noblivion\tdisgust\t0\noblivion\tfear\t1\noblivion\tjoy\t0\noblivion\tnegative\t1\noblivion\tpositive\t0\noblivion\tsadness\t0\noblivion\tsurprise\t0\noblivion\ttrust\t0\noblivious\tanger\t0\noblivious\tanticipation\t0\noblivious\tdisgust\t0\noblivious\tfear\t0\noblivious\tjoy\t0\noblivious\tnegative\t0\noblivious\tpositive\t0\noblivious\tsadness\t0\noblivious\tsurprise\t0\noblivious\ttrust\t0\noblong\tanger\t0\noblong\tanticipation\t0\noblong\tdisgust\t0\noblong\tfear\t0\noblong\tjoy\t0\noblong\tnegative\t0\noblong\tpositive\t0\noblong\tsadness\t0\noblong\tsurprise\t0\noblong\ttrust\t0\nobnoxious\tanger\t1\nobnoxious\tanticipation\t0\nobnoxious\tdisgust\t1\nobnoxious\tfear\t0\nobnoxious\tjoy\t0\nobnoxious\tnegative\t1\nobnoxious\tpositive\t0\nobnoxious\tsadness\t1\nobnoxious\tsurprise\t0\nobnoxious\ttrust\t0\noboe\tanger\t0\noboe\tanticipation\t0\noboe\tdisgust\t0\noboe\tfear\t0\noboe\tjoy\t0\noboe\tnegative\t0\noboe\tpositive\t0\noboe\tsadness\t0\noboe\tsurprise\t0\noboe\ttrust\t0\nobscene\tanger\t0\nobscene\tanticipation\t0\nobscene\tdisgust\t1\nobscene\tfear\t0\nobscene\tjoy\t0\nobscene\tnegative\t1\nobscene\tpositive\t0\nobscene\tsadness\t0\nobscene\tsurprise\t0\nobscene\ttrust\t0\nobscenity\tanger\t1\nobscenity\tanticipation\t0\nobscenity\tdisgust\t1\nobscenity\tfear\t0\nobscenity\tjoy\t0\nobscenity\tnegative\t1\nobscenity\tpositive\t0\nobscenity\tsadness\t0\nobscenity\tsurprise\t0\nobscenity\ttrust\t0\nobscure\tanger\t0\nobscure\tanticipation\t0\nobscure\tdisgust\t0\nobscure\tfear\t0\nobscure\tjoy\t0\nobscure\tnegative\t0\nobscure\tpositive\t0\nobscure\tsadness\t0\nobscure\tsurprise\t0\nobscure\ttrust\t0\nobscured\tanger\t0\nobscured\tanticipation\t0\nobscured\tdisgust\t0\nobscured\tfear\t0\nobscured\tjoy\t0\nobscured\tnegative\t0\nobscured\tpositive\t0\nobscured\tsadness\t0\nobscured\tsurprise\t0\nobscured\ttrust\t0\nobscurity\tanger\t0\nobscurity\tanticipation\t0\nobscurity\tdisgust\t0\nobscurity\tfear\t0\nobscurity\tjoy\t0\nobscurity\tnegative\t1\nobscurity\tpositive\t0\nobscurity\tsadness\t0\nobscurity\tsurprise\t0\nobscurity\ttrust\t0\nobservance\tanger\t0\nobservance\tanticipation\t0\nobservance\tdisgust\t0\nobservance\tfear\t0\no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ous\tpositive\t0\npernicious\tsadness\t1\npernicious\tsurprise\t0\npernicious\ttrust\t0\nperpendicular\tanger\t0\nperpendicular\tanticipation\t0\nperpendicular\tdisgust\t0\nperpendicular\tfear\t0\nperpendicular\tjoy\t0\nperpendicular\tnegative\t0\nperpendicular\tpositive\t0\nperpendicular\tsadness\t0\nperpendicular\tsurprise\t0\nperpendicular\ttrust\t0\nperpetrate\tanger\t0\nperpetrate\tanticipation\t0\nperpetrate\tdisgust\t0\nperpetrate\tfear\t0\nperpetrate\tjoy\t0\nperpetrate\tnegative\t0\nperpetrate\tpositive\t0\nperpetrate\tsadness\t0\nperpetrate\tsurprise\t0\nperpetrate\ttrust\t0\nperpetrator\tanger\t1\nperpetrator\tanticipation\t0\nperpetrator\tdisgust\t1\nperpetrator\tfear\t1\nperpetrator\tjoy\t0\nperpetrator\tnegative\t1\nperpetrator\tpositive\t0\nperpetrator\tsadness\t1\nperpetrator\tsurprise\t0\nperpetrator\ttrust\t0\nperpetual\tanger\t0\nperpetual\tanticipation\t0\nperpetual\tdisgust\t0\nperpetual\tfear\t0\nperpetual\tjoy\t0\nperpetual\tnegative\t0\nperpetual\tpositive\t0\nperpetual\tsadness\t0\nperpetual\tsurprise\t0\nperpetual\ttrust\t0\nperpetually\tanger\t0\nperpetually\tanticipation\t0\nperpetually\tdisgust\t0\nperpetually\tfear\t0\nperpetually\tjoy\t0\nperpetually\tnegative\t0\nperpetually\tpositive\t0\nperpetually\tsadness\t0\nperpetually\tsurprise\t0\nperpetually\ttrust\t0\nperpetuate\tanger\t0\nperpetuate\tanticipation\t1\nperpetuate\tdisgust\t0\nperpetuate\tfear\t0\nperpetuate\tjoy\t0\nperpetuate\tnegative\t0\nperpetuate\tpositive\t0\nperpetuate\tsadness\t0\nperpetuate\tsurprise\t0\nperpetuate\ttrust\t0\nperpetuation\tanger\t0\nperpetuation\tanticipation\t0\nperpetuation\tdisgust\t0\nperpetuation\tfear\t0\nperpetuation\tjoy\t0\nperpetuation\tnegative\t1\nperpetuation\tpositive\t0\nperpetuation\tsadness\t0\nperpetuation\tsurprise\t0\nperpetuation\ttrust\t0\nperpetuity\tanger\t0\nperpetuity\tanticipation\t1\nperpetuity\tdisgust\t0\nperpetuity\tfear\t0\nperpetuity\tjoy\t0\nperpetuity\tnegative\t0\nperpetuity\tpositive\t1\nperpetuity\tsadness\t0\nperpetuity\tsurprise\t0\nperpetuity\ttrust\t1\nperplexed\tanger\t0\nperplexed\tanticipation\t0\nperplexed\tdisgust\t0\nperplexed\tfear\t0\nperplexed\tjoy\t0\nperplexed\tnegative\t1\nperplexed\tpositive\t0\nperplexed\tsadness\t0\nperplexed\tsurprise\t0\nperplexed\ttrust\t0\nperplexing\tanger\t0\nperplexing\tanticipation\t0\nperplexing\tdisgust\t0\nperplexing\tfear\t0\nperplexing\tjoy\t0\nperplexing\tnegative\t0\nperplexing\tpositive\t0\nperplexing\tsadness\t0\nperplexing\tsurprise\t0\nperplexing\ttrust\t0\nperplexity\tanger\t0\nperplexity\tanticipation\t0\nperplexity\tdisgust\t0\nperplexity\tfear\t0\nperplexity\tjoy\t0\nperplexity\tnegative\t1\nperplexity\tpositive\t0\nperplexity\tsadness\t1\nperplexity\tsurprise\t0\nperplexity\ttrust\t0\npersecute\tanger\t1\npersecute\tanticipation\t0\npersecute\tdisgust\t0\npersecute\tfear\t1\npersecute\tjoy\t0\npersecute\tnegative\t1\npersecute\tpositive\t0\npersecute\tsadness\t0\npersecute\tsurprise\t0\npersecute\ttrust\t0\npersecution\tanger\t1\npersecution\tanticipation\t0\npersecution\tdisgust\t1\npersecution\tfear\t1\npersecution\tjoy\t0\npersecution\tnegative\t1\npersecution\tpositive\t0\npersecution\tsadness\t1\npersecution\tsurprise\t0\npersecution\ttrust\t0\nperseverance\tanger\t0\nperseverance\tanticipation\t0\nperseverance\tdisgust\t0\nperseverance\tfear\t0\nperseverance\tjoy\t0\nperseverance\tnegative\t0\nperseverance\tpositive\t0\nperseverance\tsadness\t0\nperseverance\tsurprise\t0\nperseverance\ttrust\t0\npersevere\tanger\t0\npersevere\tanticipation\t0\npersevere\tdisgust\t0\npersevere\tfear\t0\npersevere\tjoy\t0\npersevere\tnegative\t0\npersevere\tpositive\t0\npersevere\tsadness\t0\npersevere\tsurprise\t0\npersevere\ttrust\t0\npersist\tanger\t0\npersist\tanticipation\t0\npersist\tdisgust\t0\npersist\tfear\t0\npersist\tjoy\t0\npersist\tnegative\t0\npersist\tpositive\t0\npersist\tsadness\t0\npersist\tsurprise\t0\npersist\ttrust\t0\npersistence\tanger\t0\npersistence\tanticipation\t0\npersistence\tdisgust\t0\npersistence\tfear\t0\npersistence\tjoy\t0\npersistence\tnegative\t0\npersistence\tpositive\t1\npersistence\tsadness\t0\npersistence\tsurprise\t0\npersistence\ttrust\t0\npersistent\tanger\t0\npersistent\tanticipation\t0\npersistent\tdisgust\t0\npersistent\tfear\t0\npersistent\tjoy\t0\npersistent\tnegative\t0\npersistent\tpositive\t1\npersistent\tsadness\t0\npersistent\tsurprise\t0\npersistent\ttrust\t0\npersisting\tanger\t0\npersisting\tanticipation\t0\npersisting\tdisgust\t0\npersisting\tfear\t0\npersisting\tjoy\t0\npersisting\tnegative\t0\npersisting\tpositive\t0\npersisting\tsadness\t0\npersisting\tsurprise\t0\npersisting\ttrust\t0\nperson\tanger\t0\nperson\tanticipation\t0\nperson\tdisgust\t0\nperson\tfear\t0\nperson\tjoy\t0\nperson\tnegative\t0\nperson\tpositive\t0\nperson\tsadness\t0\nperson\tsurprise\t0\nperson\ttrust\t0\npersonable\tanger\t0\npersonable\tanticipation\t0\npersonable\tdisgust\t0\npersonable\tfear\t0\npersonable\tjoy\t0\npersonable\tnegative\t0\npersonable\tpositive\t1\nperso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sitive\t1\npresent\tsadness\t0\npresent\tsurprise\t1\npresent\ttrust\t1\npresentable\tanger\t0\npresentable\tanticipation\t0\npresentable\tdisgust\t0\npresentable\tfear\t0\npresentable\tjoy\t0\npresentable\tnegative\t0\npresentable\tpositive\t1\npresentable\tsadness\t0\npresentable\tsurprise\t0\npresentable\ttrust\t0\npresentation\tanger\t0\npresentation\tanticipation\t0\npresentation\tdisgust\t0\npresentation\tfear\t0\npresentation\tjoy\t0\npresentation\tnegative\t0\npresentation\tpositive\t0\npresentation\tsadness\t0\npresentation\tsurprise\t0\npresentation\ttrust\t0\npresentment\tanger\t0\npresentment\tanticipation\t0\npresentment\tdisgust\t0\npresentment\tfear\t0\npresentment\tjoy\t0\npresentment\tnegative\t1\npresentment\tpositive\t1\npresentment\tsadness\t0\npresentment\tsurprise\t0\npresentment\ttrust\t0\npreservation\tanger\t0\npreservation\tanticipation\t0\npreservation\tdisgust\t0\npreservation\tfear\t0\npreservation\tjoy\t0\npreservation\tnegative\t0\npreservation\tpositive\t0\npreservation\tsadness\t0\npreservation\tsurprise\t0\npreservation\ttrust\t0\npreservative\tanger\t0\npreservative\tanticipation\t1\npreservative\tdisgust\t0\npreservative\tfear\t0\npreservative\tjoy\t1\npreservative\tnegative\t0\npreservative\tpositive\t1\npreservative\tsadness\t0\npreservative\tsurprise\t1\npreservative\ttrust\t1\npreserve\tanger\t0\npreserve\tanticipation\t0\npreserve\tdisgust\t0\npreserve\tfear\t0\npreserve\tjoy\t0\npreserve\tnegative\t0\npreserve\tpositive\t1\npreserve\tsadness\t0\npreserve\tsurprise\t0\npreserve\ttrust\t0\npreserved\tanger\t0\npreserved\tanticipation\t0\npreserved\tdisgust\t0\npreserved\tfear\t0\npreserved\tjoy\t0\npreserved\tnegative\t0\npreserved\tpositive\t0\npreserved\tsadness\t0\npreserved\tsurprise\t0\npreserved\ttrust\t0\npreserving\tanger\t0\npreserving\tanticipation\t0\npreserving\tdisgust\t0\npreserving\tfear\t0\npreserving\tjoy\t0\npreserving\tnegative\t0\npreserving\tpositive\t0\npreserving\tsadness\t0\npreserving\tsurprise\t0\npreserving\ttrust\t0\npreside\tanger\t0\npreside\tanticipation\t0\npreside\tdisgust\t0\npreside\tfear\t0\npreside\tjoy\t0\npreside\tnegative\t0\npreside\tpositive\t0\npreside\tsadness\t0\npreside\tsurprise\t0\npreside\ttrust\t0\npresidency\tanger\t0\npresidency\tanticipation\t0\npresidency\tdisgust\t0\npresidency\tfear\t0\npresidency\tjoy\t0\npresidency\tnegative\t0\npresidency\tpositive\t0\npresidency\tsadness\t0\npresidency\tsurprise\t0\npresidency\ttrust\t0\npresident\tanger\t0\npresident\tanticipation\t0\npresident\tdisgust\t0\npresident\tfear\t0\npresident\tjoy\t0\npresident\tnegative\t0\npresident\tpositive\t1\npresident\tsadness\t0\npresident\tsurprise\t0\npresident\ttrust\t1\npress\tanger\t0\npress\tanticipation\t0\npress\tdisgust\t0\npress\tfear\t0\npress\tjoy\t0\npress\tnegative\t0\npress\tpositive\t0\npress\tsadness\t0\npress\tsurprise\t0\npress\ttrust\t0\npressing\tanger\t0\npressing\tanticipation\t0\npressing\tdisgust\t0\npressing\tfear\t0\npressing\tjoy\t0\npressing\tnegative\t0\npressing\tpositive\t0\npressing\tsadness\t0\npressing\tsurprise\t0\npressing\ttrust\t0\npressure\tanger\t0\npressure\tanticipation\t0\npressure\tdisgust\t0\npressure\tfear\t0\npressure\tjoy\t0\npressure\tnegative\t1\npressure\tpositive\t0\npressure\tsadness\t0\npressure\tsurprise\t0\npressure\ttrust\t0\nprestige\tanger\t0\nprestige\tanticipation\t0\nprestige\tdisgust\t0\nprestige\tfear\t0\nprestige\tjoy\t1\nprestige\tnegative\t0\nprestige\tpositive\t1\nprestige\tsadness\t0\nprestige\tsurprise\t0\nprestige\ttrust\t1\npresto\tanger\t0\npresto\tanticipation\t0\npresto\tdisgust\t0\npresto\tfear\t0\npresto\tjoy\t1\npresto\tnegative\t0\npresto\tpositive\t1\npresto\tsadness\t0\npresto\tsurprise\t1\npresto\ttrust\t0\npresumption\tanger\t0\npresumption\tanticipation\t0\npresumption\tdisgust\t0\npresumption\tfear\t0\npresumption\tjoy\t0\npresumption\tnegative\t0\npresumption\tpositive\t0\npresumption\tsadness\t0\npresumption\tsurprise\t0\npresumption\ttrust\t1\npresumptive\tanger\t0\npresumptive\tanticipation\t0\npresumptive\tdisgust\t0\npresumptive\tfear\t0\npresumptive\tjoy\t0\npresumptive\tnegative\t0\npresumptive\tpositive\t0\npresumptive\tsadness\t0\npresumptive\tsurprise\t0\npresumptive\ttrust\t0\npresumptuous\tanger\t1\npresumptuous\tanticipation\t0\npresumptuous\tdisgust\t1\npresumptuous\tfear\t0\npresumptuous\tjoy\t0\npresumptuous\tnegative\t1\npresumptuous\tpositive\t0\npresumptuous\tsadness\t0\npresumptuous\tsurprise\t0\npresumptuous\ttrust\t0\npresuppose\tanger\t0\npresuppose\tanticipation\t0\npresuppose\tdisgust\t0\npresuppose\tfear\t0\npresuppose\tjoy\t0\npresuppose\tnegative\t0\npresuppose\tpositive\t0\npresuppose\tsadness\t0\npresuppose\tsurprise\t0\npresuppose\ttrust\t0\npretend\tanger\t0\npretend\tanticipation\t0\npretend\tdisgust\t0\npretend\tfear\t0\npretend\tjoy\t0\npretend\tnegative\t1\npretend\tpositive\t0\npretend\tsadness\t0\npretend\tsurprise\t0\npretend\ttrust\t0\npretended\tanger\t0\npretended\tanticipation\t0\npretended\tdisgust\t0\npretended\tfear\t0\npretended\tjoy\t0\npretended\tnegative\t1\npretended\tpositive\t0\npretended\tsadness\t0\npretended\tsurprise\t0\npretended\ttrust\t0\npretending\tanger\t1\npretending\tanticipation\t0\npretending\tdisgust\t0\npretending\tfear\t0\npretending\tjoy\t0\npretending\tnegative\t1\npretending\tpositive\t0\npretending\tsadness\t0\npretending\tsurprise\t0\npretending\ttrust\t0\npretense\tanger\t0\npretense\tanticipation\t0\npretense\tdisgust\t0\npretense\tfear\t0\npretense\tjoy\t0\npretense\tnegative\t1\npretense\tpositive\t0\npretense\tsadness\t0\npretense\tsurprise\t0\npretense\ttrust\t0\npretensions\tanger\t0\npretensions\tanticipation\t0\npretensions\tdisgust\t0\npretensions\tfear\t0\npretensions\tjoy\t0\npretensions\tnegative\t1\npretensions\tpositive\t0\npretensions\tsadness\t0\npretensions\tsurprise\t0\npretensions\ttrust\t0\npretext\tanger\t0\npretext\tanticipation\t0\npretext\tdisgust\t0\npretext\tfear\t0\npretext\tjoy\t0\npretext\tnegative\t0\npretext\tpositive\t0\npretext\tsadness\t0\npretext\tsurprise\t0\npretext\ttrust\t0\npretty\tanger\t0\npretty\tanticipation\t1\npretty\tdisgust\t0\npretty\tfear\t0\npretty\tjoy\t1\npretty\tnegative\t0\npretty\tpositive\t1\npretty\tsadness\t0\npretty\tsurprise\t0\npretty\ttrust\t1\nprevail\tanger\t0\nprevail\tanticipation\t1\nprevail\tdisgust\t0\nprevail\tfear\t0\nprevail\tjoy\t1\nprevail\tnegative\t0\nprevail\tpositive\t1\nprevail\tsadness\t0\nprevail\tsurprise\t0\nprevail\ttrust\t0\nprevailing\tanger\t0\nprevailing\tanticipation\t0\nprevailing\tdisgust\t0\nprevailing\tfear\t0\nprevailing\tjoy\t0\nprevailing\tnegative\t0\nprevailing\tpositive\t0\nprevailing\tsadness\t0\nprevailing\tsurprise\t0\nprevailing\ttrust\t0\nprevalence\tanger\t0\nprevalence\tanticipation\t0\nprevalence\tdisgust\t0\nprevalence\tfear\t0\nprevalence\tjoy\t0\nprevalence\tnegative\t0\nprevalence\tpositive\t0\nprevalence\tsadness\t0\nprevalence\tsurprise\t0\nprevalence\ttrust\t0\nprevalent\tanger\t0\nprevalent\tanticipation\t0\nprevalent\tdisgust\t0\nprevalent\tfear\t0\nprevalent\tjoy\t0\nprevalent\tnegative\t0\nprevalent\tpositive\t0\nprevalent\tsadness\t0\nprevalent\tsurprise\t0\nprevalent\ttrust\t1\nprevent\tanger\t0\nprevent\tanticipation\t0\nprevent\tdisgust\t0\nprevent\tfear\t1\nprevent\tjoy\t0\nprevent\tnegative\t0\nprevent\tpositive\t0\nprevent\tsadness\t0\nprevent\tsurprise\t0\nprevent\ttrust\t0\npreventative\tanger\t0\npreventative\tanticipation\t0\npreventative\tdisgust\t0\npreventative\tfear\t0\npreventative\tjoy\t0\npreventative\tnegative\t0\npreventative\tpositive\t0\npreventative\tsadness\t0\npreventative\tsurprise\t0\npreventative\ttrust\t0\nprevention\tanger\t0\nprevention\tanticipation\t1\nprevention\tdisgust\t0\nprevention\tfear\t0\nprevention\tjoy\t0\nprevention\tnegative\t0\nprevention\tpositive\t1\nprevention\tsadness\t0\nprevention\tsurprise\t0\nprevention\ttrust\t0\npreventive\tanger\t0\npreventive\tanticipation\t0\npreventive\tdisgust\t0\npreventive\tfear\t0\npreventive\tjoy\t0\npreventive\tnegative\t1\npreventive\tpositive\t0\npreventive\tsadness\t0\npreventive\tsurprise\t0\npreventive\ttrust\t0\nprevious\tanger\t0\nprevious\tanticipation\t0\nprevious\tdisgust\t0\nprevious\tfear\t0\nprevious\tjoy\t0\nprevious\tnegative\t0\nprevious\tpositive\t0\nprevious\tsadness\t0\nprevious\tsurprise\t0\nprevious\ttrust\t0\npreviously\tanger\t0\npreviously\tanticipation\t0\npreviously\tdisgust\t0\npreviously\tfear\t0\npreviously\tjoy\t0\npreviously\tnegative\t0\npreviously\tpositive\t0\npreviously\tsadness\t0\npreviously\tsurprise\t0\npreviously\ttrust\t0\nprey\tanger\t0\nprey\tanticipation\t0\nprey\tdisgust\t0\nprey\tfear\t1\nprey\tjoy\t0\nprey\tnegative\t1\nprey\tpositive\t0\nprey\tsadness\t0\nprey\tsurprise\t0\nprey\ttrust\t0\nprice\tanger\t0\nprice\tanticipation\t0\nprice\tdisgust\t0\nprice\tfear\t0\nprice\tjoy\t0\nprice\tnegative\t0\nprice\tpositive\t0\nprice\tsadness\t0\nprice\tsurprise\t0\nprice\ttrust\t0\npriceless\tanger\t0\npriceless\tanticipation\t0\npriceless\tdisgust\t0\npriceless\tfear\t0\npriceless\tjoy\t0\npriceless\tnegative\t0\npriceless\tpositive\t1\npriceless\tsadness\t0\npriceless\tsurprise\t0\npriceless\ttrust\t0\nprick\tanger\t1\nprick\tanticipation\t0\nprick\tdisgust\t1\nprick\tfear\t1\nprick\tjoy\t0\nprick\tnegative\t1\nprick\tpositive\t0\nprick\tsadness\t0\nprick\tsurprise\t1\nprick\ttrust\t0\nprickly\tanger\t0\nprickly\tanticipation\t0\nprickly\tdisgust\t0\nprickly\tfear\t0\nprickly\tjoy\t0\nprickly\tnegative\t1\nprickly\tpositive\t0\nprickly\tsadness\t0\nprickly\tsurprise\t0\nprickly\ttrust\t0\npride\tanger\t0\npride\tanticipation\t0\npride\tdisgust\t0\npride\tfear\t0\npride\tjoy\t1\npride\tnegative\t0\npride\tpositive\t1\npride\tsadness\t0\npride\tsurprise\t0\npride\ttrust\t0\npriest\tanger\t0\npriest\tanticipation\t0\npriest\tdisgust\t0\npriest\tfear\t0\npriest\tjoy\t0\npriest\tnegative\t0\npriest\tpositive\t1\npriest\tsadness\t0\npriest\tsurprise\t0\npriest\ttrust\t1\npriesthood\tanger\t0\npriesthood\tanticipation\t1\npriesthood\tdisgust\t0\npriesthood\tfear\t0\npriesthood\tjoy\t1\npriesthood\tnegative\t0\npriesthood\tpositive\t1\npriesthood\tsadness\t1\npriesthood\tsurprise\t0\npriesthood\ttrust\t1\npriestly\tanger\t0\npriestly\tanticipation\t0\npriestly\tdisgust\t0\npriestly\tfear\t0\npriestly\tjoy\t0\npriestly\tnegative\t0\npriestly\tpositive\t1\npriestly\tsadness\t0\npriestly\tsurprise\t0\npriestly\ttrust\t0\nprim\tanger\t0\nprim\tanticipation\t0\nprim\tdisgust\t0\nprim\tfear\t0\nprim\tjoy\t0\nprim\tnegative\t0\nprim\tpositive\t0\nprim\tsadness\t0\nprim\tsurprise\t0\nprim\ttrust\t0\nprimacy\tanger\t0\nprimacy\tanticipation\t0\nprimacy\tdisgust\t0\nprimacy\tfear\t0\nprimacy\tjoy\t0\nprimacy\tnegative\t0\nprimacy\tpositive\t1\nprimacy\tsadness\t0\nprimacy\tsurprise\t0\nprimacy\ttrust\t0\nprimary\tanger\t0\nprimary\tanticipation\t0\nprimary\tdisgust\t0\nprimary\tfear\t0\nprimary\tjoy\t0\nprimary\tnegative\t0\nprimary\tpositive\t1\nprimary\tsadness\t0\nprimary\tsurprise\t0\nprimary\ttrust\t0\nprimate\tanger\t0\nprimate\tanticipation\t0\nprimate\tdisgust\t0\nprimate\tfear\t0\nprimate\tjoy\t0\nprimate\tnegative\t0\nprimate\tpositive\t0\nprimate\tsadness\t0\nprimate\tsurprise\t0\nprimate\ttrust\t0\nprimates\tanger\t0\nprimates\tanticipation\t0\nprimates\tdisgust\t0\nprimates\tfear\t0\nprimates\tjoy\t0\nprimates\tnegative\t0\nprimates\tpositive\t0\nprimates\tsadness\t0\nprimates\tsurprise\t0\nprimates\ttrust\t0\nprime\tanger\t0\nprime\tanticipation\t0\nprime\tdisgust\t0\nprime\tfear\t0\nprime\tjoy\t0\nprime\tnegative\t0\nprime\tpositive\t1\nprime\tsadness\t0\nprime\tsurprise\t0\nprime\ttrust\t0\nprimed\tanger\t0\nprimed\tanticipation\t0\nprimed\tdisgust\t0\nprimed\tfear\t0\nprimed\tjoy\t0\nprimed\tnegative\t0\nprimed\tpositive\t0\nprimed\tsadness\t0\nprimed\tsurprise\t0\nprimed\ttrust\t0\nprimer\tanger\t0\nprimer\tanticipation\t0\nprimer\tdisgust\t0\nprimer\tfear\t0\nprimer\tjoy\t0\nprimer\tnegative\t0\nprimer\tpositive\t1\nprimer\tsadness\t0\nprimer\tsurprise\t0\nprimer\ttrust\t1\nprimeval\tanger\t0\nprimeval\tanticipation\t0\nprimeval\tdisgust\t0\nprimeval\tfear\t0\nprimeval\tjoy\t0\nprimeval\tnegative\t0\nprimeval\tpositive\t0\nprimeval\tsadness\t0\nprimeval\tsurprise\t0\nprimeval\ttrust\t0\npriming\tanger\t0\npriming\tanticipation\t0\npriming\tdisgust\t0\npriming\tfear\t0\npriming\tjoy\t0\npriming\tnegative\t0\npriming\tpositive\t0\npriming\tsadness\t0\npriming\tsurprise\t0\npriming\ttrust\t0\nprimitive\tanger\t0\nprimitive\tanticipation\t0\nprimitive\tdisgust\t0\nprimitive\tfear\t0\nprimitive\tjoy\t0\nprimitive\tnegative\t0\nprimitive\tpositive\t0\nprimitive\tsadness\t0\nprimitive\tsurprise\t0\nprimitive\ttrust\t0\nprimordial\tanger\t0\nprimordial\tanticipation\t0\nprimordial\tdisgust\t0\nprimordial\tfear\t0\nprimordial\tjoy\t0\nprimordial\tnegative\t0\nprimordial\tpositive\t0\nprimordial\tsadness\t0\nprimordial\tsurprise\t0\nprimordial\ttrust\t0\nprince\tanger\t0\nprince\tanticipation\t0\nprince\tdisgust\t0\nprince\tfear\t0\nprince\tjoy\t0\nprince\tnegative\t0\nprince\tpositive\t1\nprince\tsadness\t0\nprince\tsurprise\t0\nprince\ttrust\t0\nprincely\tanger\t0\nprincely\tanticipation\t1\nprincely\tdisgust\t0\nprincely\tfear\t0\nprincely\tjoy\t1\nprincely\tnegative\t0\nprincely\tpositive\t1\nprincely\tsadness\t0\nprincely\tsurprise\t1\nprincely\ttrust\t1\nprincess\tanger\t0\nprincess\tanticipation\t0\nprincess\tdisgust\t0\nprincess\tfear\t0\nprincess\tjoy\t0\nprincess\tnegative\t0\nprincess\tpositive\t1\nprincess\tsadness\t0\nprincess\tsurprise\t0\nprincess\ttrust\t0\nprincipal\tanger\t0\nprincipal\tanticipation\t0\nprincipal\tdisgust\t0\nprincipal\tfear\t0\nprincipal\tjoy\t0\nprincipal\tnegative\t0\nprincipal\tpositive\t1\nprincipal\tsadness\t0\nprincipal\tsurprise\t0\nprincipal\ttrust\t1\nprincipally\tanger\t0\nprincipally\tanticipation\t0\nprincipally\tdisgust\t0\nprincipally\tfear\t0\nprincipally\tjoy\t0\nprincipally\tnegative\t0\nprincipally\tpositive\t0\nprincipally\tsadness\t0\nprincipally\tsurprise\t0\nprincipally\ttrust\t0\nprinciple\tanger\t0\nprinciple\tanticipation\t0\nprinciple\tdisgust\t0\nprinciple\tfear\t0\nprinciple\tjoy\t0\nprinciple\tnegative\t0\nprinciple\tpositive\t0\nprinciple\tsadness\t0\nprinciple\tsurprise\t0\nprinciple\ttrust\t0\nprint\tanger\t0\nprint\tanticipation\t0\nprint\tdisgust\t0\nprint\tfear\t0\nprint\tjoy\t0\nprint\tnegative\t0\nprint\tpositive\t0\nprint\tsadness\t0\nprint\tsurprise\t0\nprint\ttrust\t0\nprinter\tanger\t0\nprinter\tanticipation\t0\nprinter\tdisgust\t0\nprinter\tfear\t0\nprinter\tjoy\t0\nprinter\tnegative\t0\nprinter\tpositive\t0\nprinter\tsadness\t0\nprinter\tsurprise\t0\nprinter\ttrust\t0\nprinting\tanger\t0\nprinting\tanticipation\t0\nprinting\tdisgust\t0\nprinting\tfear\t0\nprinting\tjoy\t0\nprinting\tnegative\t0\nprinting\tpositive\t0\nprinting\tsadness\t0\nprinting\tsurprise\t0\nprinting\ttrust\t0\nprior\tanger\t0\nprior\tanticipation\t0\nprior\tdisgust\t0\nprior\tfear\t0\nprior\tjoy\t0\nprior\tnegative\t0\nprior\tpositive\t0\nprior\tsadness\t0\nprior\tsurprise\t0\nprior\ttrust\t0\npriority\ta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rprise\t0\npromenade\ttrust\t0\nprominence\tanger\t0\nprominence\tanticipation\t0\nprominence\tdisgust\t0\nprominence\tfear\t0\nprominence\tjoy\t0\nprominence\tnegative\t0\nprominence\tpositive\t1\nprominence\tsadness\t0\nprominence\tsurprise\t0\nprominence\ttrust\t0\nprominently\tanger\t0\nprominently\tanticipation\t0\nprominently\tdisgust\t0\nprominently\tfear\t0\nprominently\tjoy\t0\nprominently\tnegative\t0\nprominently\tpositive\t1\nprominently\tsadness\t0\nprominently\tsurprise\t0\nprominently\ttrust\t0\npromiscuous\tanger\t0\npromiscuous\tanticipation\t0\npromiscuous\tdisgust\t0\npromiscuous\tfear\t0\npromiscuous\tjoy\t0\npromiscuous\tnegative\t1\npromiscuous\tpositive\t0\npromiscuous\tsadness\t0\npromiscuous\tsurprise\t0\npromiscuous\ttrust\t0\npromise\tanger\t0\npromise\tanticipation\t0\npromise\tdisgust\t0\npromise\tfear\t0\npromise\tjoy\t1\npromise\tnegative\t0\npromise\tpositive\t1\npromise\tsadness\t0\npromise\tsurprise\t0\npromise\ttrust\t1\npromising\tanger\t0\npromising\tanticipation\t0\npromising\tdisgust\t0\npromising\tfear\t0\npromising\tjoy\t0\npromising\tnegative\t0\npromising\tpositive\t1\npromising\tsadness\t0\npromising\tsurprise\t0\npromising\ttrust\t0\npromissory\tanger\t0\npromissory\tanticipation\t0\npromissory\tdisgust\t0\npromissory\tfear\t0\npromissory\tjoy\t0\npromissory\tnegative\t0\npromissory\tpositive\t0\npromissory\tsadness\t0\npromissory\tsurprise\t0\npromissory\ttrust\t0\npromontory\tanger\t0\npromontory\tanticipation\t0\npromontory\tdisgust\t0\npromontory\tfear\t0\npromontory\tjoy\t0\npromontory\tnegative\t0\npromontory\tpositive\t0\npromontory\tsadness\t0\npromontory\tsurprise\t0\npromontory\ttrust\t0\npromote\tanger\t0\npromote\tanticipation\t0\npromote\tdisgust\t0\npromote\tfear\t0\npromote\tjoy\t0\npromote\tnegative\t0\npromote\tpositive\t0\npromote\tsadness\t0\npromote\tsurprise\t0\npromote\ttrust\t0\npromoter\tanger\t0\npromoter\tanticipation\t0\npromoter\tdisgust\t0\npromoter\tfear\t0\npromoter\tjoy\t0\npromoter\tnegative\t0\npromoter\tpositive\t0\npromoter\tsadness\t0\npromoter\tsurprise\t0\npromoter\ttrust\t0\npromotion\tanger\t0\npromotion\tanticipation\t0\npromotion\tdisgust\t0\npromotion\tfear\t0\npromotion\tjoy\t0\npromotion\tnegative\t0\npromotion\tpositive\t1\npromotion\tsadness\t0\npromotion\tsurprise\t0\npromotion\ttrust\t0\nprompt\tanger\t0\nprompt\tanticipation\t0\nprompt\tdisgust\t0\nprompt\tfear\t0\nprompt\tjoy\t0\nprompt\tnegative\t0\nprompt\tpositive\t0\nprompt\tsadness\t0\nprompt\tsurprise\t0\nprompt\ttrust\t0\nprompting\tanger\t0\nprompting\tanticipation\t0\nprompting\tdisgust\t0\nprompting\tfear\t0\nprompting\tjoy\t0\nprompting\tnegative\t0\nprompting\tpositive\t0\nprompting\tsadness\t0\nprompting\tsurprise\t0\nprompting\ttrust\t0\npromulgate\tanger\t0\npromulgate\tanticipation\t0\npromulgate\tdisgust\t0\npromulgate\tfear\t0\npromulgate\tjoy\t0\npromulgate\tnegative\t0\npromulgate\tpositive\t0\npromulgate\tsadness\t0\npromulgate\tsurprise\t0\npromulgate\ttrust\t0\npromulgation\tanger\t0\npromulgation\tanticipation\t0\npromulgation\tdisgust\t0\npromulgation\tfear\t0\npromulgation\tjoy\t0\npromulgation\tnegative\t0\npromulgation\tpositive\t0\npromulgation\tsadness\t0\npromulgation\tsurprise\t0\npromulgation\ttrust\t0\nprone\tanger\t0\nprone\tanticipation\t0\nprone\tdisgust\t0\nprone\tfear\t0\nprone\tjoy\t0\nprone\tnegative\t0\nprone\tpositive\t0\nprone\tsadness\t0\nprone\tsurprise\t0\nprone\ttrust\t0\nprong\tanger\t0\nprong\tanticipation\t0\nprong\tdisgust\t0\nprong\tfear\t0\nprong\tjoy\t0\nprong\tnegative\t0\nprong\tpositive\t0\nprong\tsadness\t0\nprong\tsurprise\t0\nprong\ttrust\t0\npronounce\tanger\t0\npronounce\tanticipation\t0\npronounce\tdisgust\t0\npronounce\tfear\t0\npronounce\tjoy\t0\npronounce\tnegative\t0\npronounce\tpositive\t0\npronounce\tsadness\t0\npronounce\tsurprise\t0\npronounce\ttrust\t0\npronounced\tanger\t0\npronounced\tanticipation\t0\npronounced\tdisgust\t0\npronounced\tfear\t0\npronounced\tjoy\t0\npronounced\tnegative\t0\npronounced\tpositive\t0\npronounced\tsadness\t0\npronounced\tsurprise\t0\npronounced\ttrust\t0\npronouncement\tanger\t0\npronouncement\tanticipation\t0\npronouncement\tdisgust\t0\npronouncement\tfear\t0\npronouncement\tjoy\t0\npronouncement\tnegative\t0\npronouncement\tpositive\t0\npronouncement\tsadness\t0\npronouncement\tsurprise\t0\npronouncement\ttrust\t0\npronunciation\tanger\t0\npronunciation\tanticipation\t0\npronunciation\tdisgust\t0\npronunciation\tfear\t0\npronunciation\tjoy\t0\npronunciation\tnegative\t0\npronunciation\tpositive\t0\npronunciation\tsadness\t0\npronunciation\tsurprise\t0\npronunciation\ttrust\t0\nproof\tanger\t0\nproof\tanticipation\t0\nproof\tdisgust\t0\nproof\tfear\t0\nproof\tjoy\t0\nproof\tnegative\t0\nproof\tpositive\t0\nproof\tsadness\t0\nproof\tsurprise\t0\nproof\ttrust\t1\nprop\tanger\t0\nprop\tanticipation\t0\nprop\tdisgust\t0\nprop\tfear\t0\nprop\tjoy\t0\nprop\tnegative\t0\nprop\tpositive\t1\nprop\tsadness\t0\nprop\tsurprise\t0\nprop\ttrust\t0\npropaganda\tanger\t0\npropaganda\tanticipation\t0\npropaganda\tdisgust\t0\npropaganda\tfear\t0\npropaganda\tjoy\t0\npropaganda\tnegative\t1\npropaganda\tpositive\t0\npropaganda\tsadness\t0\npropaganda\tsurprise\t0\npropaganda\ttrust\t0\npropagate\tanger\t0\npropagate\tanticipation\t0\npropagate\tdisgust\t0\npropagate\tfear\t0\npropagate\tjoy\t0\npropagate\tnegative\t0\npropagate\tpositive\t0\npropagate\tsadness\t0\npropagate\tsurprise\t0\npropagate\ttrust\t0\npropagation\tanger\t0\npropagation\tanticipation\t0\npropagation\tdisgust\t0\npropagation\tfear\t0\npropagation\tjoy\t0\npropagation\tnegative\t0\npropagation\tpositive\t0\npropagation\tsadness\t0\npropagation\tsurprise\t0\npropagation\ttrust\t0\npropane\tanger\t0\npropane\tanticipation\t0\npropane\tdisgust\t0\npropane\tfear\t0\npropane\tjoy\t0\npropane\tnegative\t0\npropane\tpositive\t0\npropane\tsadness\t0\npropane\tsurprise\t0\npropane\ttrust\t0\npropel\tanger\t0\npropel\tanticipation\t0\npropel\tdisgust\t0\npropel\tfear\t0\npropel\tjoy\t0\npropel\tnegative\t0\npropel\tpositive\t0\npropel\tsadness\t0\npropel\tsurprise\t0\npropel\ttrust\t0\npropelled\tanger\t0\npropelled\tanticipation\t0\npropelled\tdisgust\t0\npropelled\tfear\t0\npropelled\tjoy\t0\npropelled\tnegative\t0\npropelled\tpositive\t0\npropelled\tsadness\t0\npropelled\tsurprise\t0\npropelled\ttrust\t0\npropeller\tanger\t0\npropeller\tanticipation\t0\npropeller\tdisgust\t0\npropeller\tfear\t0\npropeller\tjoy\t0\npropeller\tnegative\t0\npropeller\tpositive\t0\npropeller\tsadness\t0\npropeller\tsurprise\t0\npropeller\ttrust\t0\npropelling\tanger\t0\npropelling\tanticipation\t0\npropelling\tdisgust\t0\npropelling\tfear\t0\npropelling\tjoy\t0\npropelling\tnegative\t0\npropelling\tpositive\t0\npropelling\tsadness\t0\npropelling\tsurprise\t0\npropelling\ttrust\t0\npropensity\tanger\t0\npropensity\tanticipation\t0\npropensity\tdisgust\t0\npropensity\tfear\t0\npropensity\tjoy\t0\npropensity\tnegative\t0\npropensity\tpositive\t0\npropensity\tsadness\t0\npropensity\tsurprise\t0\npropensity\ttrust\t0\nproper\tanger\t0\nproper\tanticipation\t0\nproper\tdisgust\t0\nproper\tfear\t0\nproper\tjoy\t0\nproper\tnegative\t0\nproper\tpositive\t1\nproper\tsadness\t0\nproper\tsurprise\t0\nproper\ttrust\t0\nproperty\tanger\t0\nproperty\tanticipation\t0\nproperty\tdisgust\t0\nproperty\tfear\t0\nproperty\tjoy\t0\nproperty\tnegative\t0\nproperty\tpositive\t0\nproperty\tsadness\t0\nproperty\tsurprise\t0\nproperty\ttrust\t0\nprophecy\tanger\t0\nprophecy\tanticipation\t1\nprophecy\tdisgust\t0\nprophecy\tfear\t0\nprophecy\tjoy\t0\nprophecy\tnegative\t0\nprophecy\tpositive\t0\nprophecy\tsadness\t0\nprophecy\tsurprise\t0\nprophecy\ttrust\t0\nprophesy\tanger\t0\nprophesy\tanticipation\t0\nprophesy\tdisgust\t0\nprophesy\tfear\t0\nprophesy\tjoy\t0\nprophesy\tnegative\t0\nprophesy\tpositive\t0\nprophesy\tsadness\t0\nprophesy\tsurprise\t0\nprophesy\ttrust\t0\nprophet\tanger\t0\nprophet\tanticipation\t1\nprophet\tdisgust\t0\nprophet\tfear\t0\nprophet\tjoy\t0\nprophet\tnegative\t0\nprophet\tpositive\t1\nprophet\tsadness\t0\nprophet\tsurprise\t0\nprophet\ttrust\t1\nprophetic\tanger\t0\nprophetic\tanticipation\t1\nprophetic\tdisgust\t0\nprophetic\tfear\t0\nprophetic\tjoy\t0\nprophetic\tnegative\t0\nprophetic\tpositive\t0\nprophetic\tsadness\t0\nprophetic\tsurprise\t0\nprophetic\ttrust\t0\nprophylactic\tanger\t0\nprophylactic\tanticipation\t1\nprophylactic\tdisgust\t0\nprophylactic\tfear\t0\nprophylactic\tjoy\t0\nprophylactic\tnegative\t0\nprophylactic\tpositive\t1\nprophylactic\tsadness\t0\nprophylactic\tsurprise\t0\nprophylactic\ttrust\t1\nprophylaxis\tanger\t0\nprophylaxis\tanticipation\t0\nprophylaxis\tdisgust\t0\nprophylaxis\tfear\t0\nprophylaxis\tjoy\t0\nprophylaxis\tnegative\t0\nprophylaxis\tpositive\t0\nprophylaxis\tsadness\t0\nprophylaxis\tsurprise\t0\nprophylaxis\ttrust\t0\nproportion\tanger\t0\nproportion\tanticipation\t0\nproportion\tdisgust\t0\nproportion\tfear\t0\nproportion\tjoy\t0\nproportion\tnegative\t0\nproportion\tpositive\t0\nproportion\tsadness\t0\nproportion\tsurprise\t0\nproportion\ttrust\t0\nproportional\tanger\t0\nproportional\tanticipation\t0\nproportional\tdisgust\t0\nproportional\tfear\t0\nproportional\tjoy\t0\nproportional\tnegative\t0\nproportional\tpositive\t0\nproportional\tsadness\t0\nproportional\tsurprise\t0\nproportional\ttrust\t0\nproportionate\tanger\t0\nproportionate\tanticipation\t0\nproportionate\tdisgust\t0\nproportionate\tfear\t0\nproportionate\tjoy\t0\nproportionate\tnegative\t0\nproportionate\tpositive\t0\nproportionate\tsadness\t0\nproportionate\tsurprise\t0\nproportionate\ttrust\t0\nproportions\tanger\t0\nproportions\tanticipation\t0\nproportions\tdisgust\t0\nproportions\tfear\t0\nproportions\tjoy\t0\nproportions\tnegative\t0\nproportions\tpositive\t0\nproportions\tsadness\t0\nproportions\tsurprise\t0\nproportions\ttrust\t0\nproposal\tanger\t0\nproposal\tanticipation\t0\nproposal\tdisgust\t0\nproposal\tfear\t0\nproposal\tjoy\t0\nproposal\tnegative\t0\nproposal\tpositive\t0\nproposal\tsadness\t0\nproposal\tsurprise\t0\nproposal\ttrust\t0\nproposition\tanger\t0\nproposition\tanticipation\t0\nproposition\tdisgust\t0\nproposition\tfear\t0\nproposition\tjoy\t0\nproposition\tnegative\t0\nproposition\tpositive\t1\nproposition\tsadness\t0\nproposition\tsurprise\t0\nproposition\ttrust\t0\nproprietary\tanger\t0\nproprietary\tanticipation\t0\nproprietary\tdisgust\t0\nproprietary\tfear\t0\nproprietary\tjoy\t0\nproprietary\tnegative\t0\nproprietary\tpositive\t0\nproprietary\tsadness\t0\nproprietary\tsurprise\t0\nproprietary\ttrust\t0\nproprietor\tanger\t0\nproprietor\tanticipation\t0\nproprietor\tdisgust\t0\nproprietor\tfear\t0\nproprietor\tjoy\t0\nproprietor\tnegative\t0\nproprietor\tpositive\t0\nproprietor\tsadness\t0\nproprietor\tsurprise\t0\nproprietor\ttrust\t0\nproprietorship\tanger\t0\nproprietorship\tanticipation\t0\nproprietorship\tdisgust\t0\nproprietorship\tfear\t0\nproprietorship\tjoy\t0\nproprietorship\tnegative\t0\nproprietorship\tpositive\t0\nproprietorship\tsadness\t0\nproprietorship\tsurprise\t0\nproprietorship\ttrust\t0\npropriety\tanger\t0\npropriety\tanticipation\t0\npropriety\tdisgust\t0\npropriety\tfear\t0\npropriety\tjoy\t0\npropriety\tnegative\t0\npropriety\tpositive\t0\npropriety\tsadness\t0\npropriety\tsurprise\t0\npropriety\ttrust\t0\npropulsion\tanger\t0\npropulsion\tanticipation\t0\npropulsion\tdisgust\t0\npropulsion\tfear\t0\npropulsion\tjoy\t0\npropulsion\tnegative\t0\npropulsion\tpositive\t0\npropulsion\tsadness\t0\npropulsion\tsurprise\t0\npropulsion\ttrust\t0\nprose\tanger\t0\nprose\tanticipation\t0\nprose\tdisgust\t0\nprose\tfear\t0\nprose\tjoy\t0\nprose\tnegative\t0\nprose\tpositive\t0\nprose\tsadness\t0\nprose\tsurprise\t0\nprose\ttrust\t0\nprosecute\tanger\t1\nprosecute\tanticipation\t0\nprosecute\tdisgust\t0\nprosecute\tfear\t1\nprosecute\tjoy\t0\nprosecute\tnegative\t1\nprosecute\tpositive\t0\nprosecute\tsadness\t1\nprosecute\tsurprise\t0\nprosecute\ttrust\t0\nprosecution\tanger\t0\nprosecution\tanticipation\t0\nprosecution\tdisgust\t1\nprosecution\tfear\t0\nprosecution\tjoy\t0\nprosecution\tnegative\t1\nprosecution\tpositive\t0\nprosecution\tsadness\t0\nprosecution\tsurprise\t0\nprosecution\ttrust\t0\nprosecutor\tanger\t0\nprosecutor\tanticipation\t0\nprosecutor\tdisgust\t0\nprosecutor\tfear\t0\nprosecutor\tjoy\t0\nprosecutor\tnegative\t0\nprosecutor\tpositive\t0\nprosecutor\tsadness\t0\nprosecutor\tsurprise\t0\nprosecutor\ttrust\t0\nprospect\tanger\t0\nprospect\tanticipation\t0\nprospect\tdisgust\t0\nprospect\tfear\t0\nprospect\tjoy\t0\nprospect\tnegative\t0\nprospect\tpositive\t1\nprospect\tsadness\t0\nprospect\tsurprise\t0\nprospect\ttrust\t0\nprospective\tanger\t0\nprospective\tanticipation\t0\nprospective\tdisgust\t0\nprospective\tfear\t0\nprospective\tjoy\t0\nprospective\tnegative\t0\nprospective\tpositive\t0\nprospective\tsadness\t0\nprospective\tsurprise\t0\nprospective\ttrust\t0\nprospectively\tanger\t0\nprospectively\tanticipation\t1\nprospectively\tdisgust\t0\nprospectively\tfear\t0\nprospectively\tjoy\t0\nprospectively\tnegative\t0\nprospectively\tpositive\t0\nprospectively\tsadness\t0\nprospectively\tsurprise\t0\nprospectively\ttrust\t0\nprospectus\tanger\t0\nprospectus\tanticipation\t0\nprospectus\tdisgust\t0\nprospectus\tfear\t0\nprospectus\tjoy\t0\nprospectus\tnegative\t0\nprospectus\tpositive\t0\nprospectus\tsadness\t0\nprospectus\tsurprise\t0\nprospectus\ttrust\t0\nprosper\tanger\t0\nprosper\tanticipation\t1\nprosper\tdisgust\t0\nprosper\tfear\t0\nprosper\tjoy\t1\nprosper\tnegative\t0\nprosper\tpositive\t1\nprosper\tsadness\t0\nprosper\tsurprise\t0\nprosper\ttrust\t0\nprosperity\tanger\t0\nprosperity\tanticipation\t0\nprosperity\tdisgust\t0\nprosperity\tfear\t0\nprosperity\tjoy\t0\nprosperity\tnegative\t0\nprosperity\tpositive\t1\nprosperity\tsadness\t0\nprosperity\tsurprise\t0\nprosperity\ttrust\t0\nprosperous\tanger\t0\nprosperous\tanticipation\t0\nprosperous\tdisgust\t0\nprosperous\tfear\t0\nprosperous\tjoy\t1\nprosperous\tnegative\t0\nprosperous\tpositive\t1\nprosperous\tsadness\t0\nprosperous\tsurprise\t0\nprosperous\ttrust\t0\nprostitute\tanger\t0\nprostitute\tanticipation\t0\nprostitute\tdisgust\t1\nprostitute\tfear\t0\nprostitute\tjoy\t0\nprostitute\tnegative\t1\nprostitute\tpositive\t0\nprostitute\tsadness\t0\nprostitute\tsurprise\t0\nprostitute\ttrust\t0\nprostitution\tanger\t0\nprostitution\tanticipation\t0\nprostitution\tdisgust\t1\nprostitution\tfear\t0\nprostitution\tjoy\t0\nprostitution\tnegative\t1\nprostitution\tpositive\t0\nprostitution\tsadness\t1\nprostitution\tsurprise\t0\nprostitution\ttrust\t0\nprostrate\tanger\t0\nprostrate\tanticipation\t0\nprostrate\tdisgust\t0\nprostrate\tfear\t0\nprostrate\tjoy\t0\nprostrate\tnegative\t0\nprostrate\tpositive\t0\nprostrate\tsadness\t0\nprostrate\tsurprise\t0\nprostrate\ttrust\t0\nprotagonist\tanger\t0\nprotagonist\tanticipation\t0\nprotagonist\tdisgust\t0\nprotagonist\tfear\t0\nprotagonist\tjoy\t0\nprotagonist\tnegative\t0\nprotagonist\tpositive\t0\nprotagonist\tsadness\t0\nprotagonist\tsurprise\t0\nprotagonist\ttrust\t0\nprotect\tanger\t0\nprotect\tanticipation\t0\nprotect\tdisgust\t0\nprotect\tfear\t0\nprotect\tjoy\t0\nprotect\tnegative\t0\nprotect\tpositive\t1\nprotect\tsadness\t0\nprotect\tsurprise\t0\nprotect\ttrust\t0\nprotected\tanger\t0\nprotected\tanticipation\t0\nprotected\tdisgust\t0\nprotected\tfear\t0\nprotected\tjoy\t0\nprotected\tnegative\t0\nprotected\tpositive\t0\nprotected\tsadness\t0\nprotected\tsurprise\t0\nprotected\ttrust\t1\nprotecting\tanger\t0\nprotecting\tanticipation\t0\nprotecting\tdisgust\t0\nprotecting\tfear\t0\nprotecting\tjoy\t0\nprotecting\tnegative\t0\nprotecting\tpositive\t1\nprotecting\tsadness\t0\nprotecting\tsurprise\t0\nprotecting\ttrust\t1\nprotection\tanger\t0\nprotection\tanticipation\t0\nprotection\tdisgust\t0\nprotection\tfear\t0\nprotection\tjoy\t0\nprotection\tnegative\t0\nprotection\tpositive\t0\nprotection\tsadness\t0\nprotection\tsurprise\t0\nprotection\ttrust\t0\nprotective\tanger\t0\nprotective\tanticipation\t0\nprotective\tdisgust\t0\nprotective\tfear\t0\nprotective\tjoy\t0\nprotective\tnegative\t0\nprotective\tpositive\t1\nprotective\tsadness\t0\nprotective\tsurprise\t0\nprotective\ttrust\t0\nprotector\tanger\t0\nprotector\tanticipation\t0\nprotector\tdisgust\t0\nprotector\tfear\t0\nprotector\tjoy\t0\nprotector\tnegative\t0\nprotector\tpositive\t1\nprotector\tsadness\t0\nprotector\tsurprise\t0\nprotector\ttrust\t1\nprotein\tanger\t0\nprotein\tanticipation\t0\nprotein\tdisgust\t0\nprotein\tfear\t0\nprotein\tjoy\t0\nprotein\tnegative\t0\nprotein\tpositive\t0\nprotein\tsadness\t0\nprotein\tsurprise\t0\nprotein\ttrust\t0\nprotest\tanger\t0\nprotest\tanticipation\t0\nprotest\tdisgust\t0\nprotest\tfear\t0\nprotest\tjoy\t0\nprotest\tnegative\t0\nprotest\tpositive\t0\nprotest\tsadness\t0\nprotest\tsurprise\t0\nprotest\ttrust\t0\nprotestant\tanger\t0\nprotestant\tanticipation\t0\nprotestant\tdisgust\t0\nprotestant\tfear\t1\nprotestant\tjoy\t0\nprotestant\tnegative\t0\nprotestant\tpositive\t0\nprotestant\tsadness\t0\nprotestant\tsurprise\t0\nprotestant\ttrust\t0\nprotocol\tanger\t0\nprotocol\tanticipation\t0\nprotocol\tdisgust\t0\nprotocol\tfear\t0\nprotocol\tjoy\t0\nprotocol\tnegative\t0\nprotocol\tpositive\t0\nprotocol\tsadness\t0\nprotocol\tsurprise\t0\nprotocol\ttrust\t0\nprototype\tanger\t0\nprototype\tanticipation\t0\nprototype\tdisgust\t0\nprototype\tfear\t0\nprototype\tjoy\t0\nprototype\tnegative\t0\nprototype\tpositive\t0\nprototype\tsadness\t0\nprototype\tsurprise\t0\nprototype\ttrust\t0\nprotozoa\tanger\t0\nprotozoa\tanticipation\t0\nprotozoa\tdisgust\t0\nprotozoa\tfear\t0\nprotozoa\tjoy\t0\nprotozoa\tnegative\t0\nprotozoa\tpositive\t0\nprotozoa\tsadness\t0\nprotozoa\tsurprise\t0\nprotozoa\ttrust\t0\nprotracted\tanger\t0\nprotracted\tanticipation\t0\nprotracted\tdisgust\t0\nprotracted\tfear\t0\nprotracted\tjoy\t0\nprotracted\tnegative\t0\nprotracted\tpositive\t0\nprotracted\tsadness\t0\nprotracted\tsurprise\t0\nprotracted\ttrust\t0\nprotrude\tanger\t0\nprotrude\tanticipation\t0\nprotrude\tdisgust\t0\nprotrude\tfear\t0\nprotrude\tjoy\t0\nprotrude\tnegative\t0\nprotrude\tpositive\t0\nprotrude\tsadness\t0\nprotrude\tsurprise\t0\nprotrude\ttrust\t0\nprotrusion\tanger\t0\nprotrusion\tanticipation\t0\nprotrusion\tdisgust\t0\nprotrusion\tfear\t0\nprotrusion\tjoy\t0\nprotrusion\tnegative\t0\nprotrusion\tpositive\t0\nprotrusion\tsadness\t0\nprotrusion\tsurprise\t0\nprotrusion\ttrust\t0\nproud\tanger\t0\nproud\tanticipation\t1\nproud\tdisgust\t0\nproud\tfear\t0\nproud\tjoy\t1\nproud\tnegative\t0\nproud\tpositive\t1\nproud\tsadness\t0\nproud\tsurprise\t0\nproud\ttrust\t1\nprove\tanger\t0\nprove\tanticipation\t0\nprove\tdisgust\t0\nprove\tfear\t0\nprove\tjoy\t0\nprove\tnegative\t0\nprove\tpositive\t1\nprove\tsadness\t0\nprove\tsurprise\t0\nprove\ttrust\t0\nproven\tanger\t0\nproven\tanticipation\t0\nproven\tdisgust\t0\nproven\tfear\t0\nproven\tjoy\t0\nproven\tnegative\t0\nproven\tpositive\t0\nproven\tsadness\t0\nproven\tsurprise\t0\nproven\ttrust\t1\nproverb\tanger\t0\nproverb\tanticipation\t0\nproverb\tdisgust\t0\nproverb\tfear\t0\nproverb\tjoy\t0\nproverb\tnegative\t0\nproverb\tpositive\t0\nproverb\tsadness\t0\nproverb\tsurprise\t0\nproverb\ttrust\t0\nproverbial\tanger\t0\nproverbial\tanticipation\t0\nproverbial\tdisgust\t0\nproverbial\tfear\t0\nproverbial\tjoy\t0\nproverbial\tnegative\t0\nproverbial\tpositive\t1\nproverbial\tsadness\t0\nproverbial\tsurprise\t0\nproverbial\ttrust\t0\nprovide\tanger\t0\nprovide\tanticipation\t0\nprovide\tdisgust\t0\nprovide\tfear\t0\nprovide\tjoy\t0\nprovide\tnegative\t0\nprovide\tpositive\t1\nprovide\tsadness\t0\nprovide\tsurprise\t0\nprovide\ttrust\t1\nprovided\tanger\t0\nprovided\tanticipation\t0\nprovided\tdisgust\t0\nprovided\tfear\t0\nprovided\tjoy\t0\nprovided\tnegative\t0\nprovided\tpositive\t0\nprovided\tsadness\t0\nprovided\tsurprise\t0\nprovided\ttrust\t0\nprovidence\tanger\t0\nprovidence\tanticipation\t0\nprovidence\tdisgust\t0\nprovidence\tfear\t0\nprovidence\tjoy\t0\nprovidence\tnegative\t0\nprovidence\tpositive\t0\npro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urprise\t0\npsalm\ttrust\t0\npseudo\tanger\t0\npseudo\tanticipation\t0\npseudo\tdisgust\t0\npseudo\tfear\t0\npseudo\tjoy\t0\npseudo\tnegative\t0\npseudo\tpositive\t0\npseudo\tsadness\t0\npseudo\tsurprise\t0\npseudo\ttrust\t0\npseudonym\tanger\t0\npseudonym\tanticipation\t0\npseudonym\tdisgust\t0\npseudonym\tfear\t0\npseudonym\tjoy\t0\npseudonym\tnegative\t0\npseudonym\tpositive\t0\npseudonym\tsadness\t0\npseudonym\tsurprise\t0\npseudonym\ttrust\t0\npsyche\tanger\t0\npsyche\tanticipation\t0\npsyche\tdisgust\t0\npsyche\tfear\t0\npsyche\tjoy\t0\npsyche\tnegative\t0\npsyche\tpositive\t0\npsyche\tsadness\t0\npsyche\tsurprise\t0\npsyche\ttrust\t0\npsychical\tanger\t0\npsychical\tanticipation\t0\npsychical\tdisgust\t0\npsychical\tfear\t0\npsychical\tjoy\t0\npsychical\tnegative\t0\npsychical\tpositive\t0\npsychical\tsadness\t0\npsychical\tsurprise\t0\npsychical\ttrust\t0\npsychics\tanger\t0\npsychics\tanticipation\t0\npsychics\tdisgust\t0\npsychics\tfear\t0\npsychics\tjoy\t0\npsychics\tnegative\t0\npsychics\tpositive\t0\npsychics\tsadness\t0\npsychics\tsurprise\t0\npsychics\ttrust\t0\npsychological\tanger\t0\npsychological\tanticipation\t0\npsychological\tdisgust\t0\npsychological\tfear\t0\npsychological\tjoy\t0\npsychological\tnegative\t0\npsychological\tpositive\t0\npsychological\tsadness\t0\npsychological\tsurprise\t0\npsychological\ttrust\t0\npsychologist\tanger\t0\npsychologist\tanticipation\t0\npsychologist\tdisgust\t0\npsychologist\tfear\t0\npsychologist\tjoy\t0\npsychologist\tnegative\t0\npsychologist\tpositive\t0\npsychologist\tsadness\t0\npsychologist\tsurprise\t0\npsychologist\ttrust\t0\npsychology\tanger\t0\npsychology\tanticipation\t0\npsychology\tdisgust\t0\npsychology\tfear\t0\npsychology\tjoy\t0\npsychology\tnegative\t0\npsychology\tpositive\t0\npsychology\tsadness\t0\npsychology\tsurprise\t0\npsychology\ttrust\t0\npsychosis\tanger\t1\npsychosis\tanticipation\t0\npsychosis\tdisgust\t0\npsychosis\tfear\t1\npsychosis\tjoy\t0\npsychosis\tnegative\t1\npsychosis\tpositive\t0\npsychosis\tsadness\t1\npsychosis\tsurprise\t0\npsychosis\ttrust\t0\npub\tanger\t0\npub\tanticipation\t0\npub\tdisgust\t0\npub\tfear\t0\npub\tjoy\t0\npub\tnegative\t0\npub\tpositive\t0\npub\tsadness\t0\npub\tsurprise\t0\npub\ttrust\t0\npuberty\tanger\t0\npuberty\tanticipation\t0\npuberty\tdisgust\t0\npuberty\tfear\t0\npuberty\tjoy\t0\npuberty\tnegative\t0\npuberty\tpositive\t0\npuberty\tsadness\t0\npuberty\tsurprise\t0\npuberty\ttrust\t0\npubescent\tanger\t0\npubescent\tanticipation\t0\npubescent\tdisgust\t0\npubescent\tfear\t0\npubescent\tjoy\t0\npubescent\tnegative\t0\npubescent\tpositive\t0\npubescent\tsadness\t0\npubescent\tsurprise\t0\npubescent\ttrust\t0\npublic\tanger\t0\npublic\tanticipation\t1\npublic\tdisgust\t0\npublic\tfear\t0\npublic\tjoy\t0\npublic\tnegative\t0\npublic\tpositive\t1\npublic\tsadness\t0\npublic\tsurprise\t0\npublic\ttrust\t0\npublication\tanger\t0\npublication\tanticipation\t0\npublication\tdisgust\t0\npublication\tfear\t0\npublication\tjoy\t0\npublication\tnegative\t0\npublication\tpositive\t0\npublication\tsadness\t0\npublication\tsurprise\t0\npublication\ttrust\t0\npublicist\tanger\t0\npublicist\tanticipation\t0\npublicist\tdisgust\t0\npublicist\tfear\t0\npublicist\tjoy\t0\npublicist\tnegative\t1\npublicist\tpositive\t0\npublicist\tsadness\t0\npublicist\tsurprise\t0\npublicist\ttrust\t0\npublicity\tanger\t0\npublicity\tanticipation\t0\npublicity\tdisgust\t0\npublicity\tfear\t0\npublicity\tjoy\t0\npublicity\tnegative\t0\npublicity\tpositive\t0\npublicity\tsadness\t0\npublicity\tsurprise\t0\npublicity\ttrust\t0\npublicly\tanger\t0\npublicly\tanticipation\t0\npublicly\tdisgust\t0\npublicly\tfear\t0\npublicly\tjoy\t0\npublicly\tnegative\t0\npublicly\tpositive\t0\npublicly\tsadness\t0\npublicly\tsurprise\t0\npublicly\ttrust\t0\npublish\tanger\t0\npublish\tanticipation\t0\npublish\tdisgust\t0\npublish\tfear\t0\npublish\tjoy\t0\npublish\tnegative\t0\npublish\tpositive\t0\npublish\tsadness\t0\npublish\tsurprise\t0\npublish\ttrust\t0\npublished\tanger\t0\npublished\tanticipation\t0\npublished\tdisgust\t0\npublished\tfear\t0\npublished\tjoy\t0\npublished\tnegative\t0\npublished\tpositive\t0\npublished\tsadness\t0\npublished\tsurprise\t0\npublished\ttrust\t0\npublisher\tanger\t0\npublisher\tanticipation\t0\npublisher\tdisgust\t0\npublisher\tfear\t0\npublisher\tjoy\t0\npublisher\tnegative\t0\npublisher\tpositive\t0\npublisher\tsadness\t0\npublisher\tsurprise\t0\npublisher\ttrust\t0\npudding\tanger\t0\npudding\tanticipation\t0\npudding\tdisgust\t0\npudding\tfear\t0\npudding\tjoy\t0\npudding\tnegative\t0\npudding\tpositive\t0\npudding\tsadness\t0\npudding\tsurprise\t0\npudding\ttrust\t0\npuddle\tanger\t0\npuddle\tanticipation\t0\npuddle\tdisgust\t0\npuddle\tfear\t0\npuddle\tjoy\t0\npuddle\tnegative\t0\npuddle\tpositive\t0\npuddle\tsadness\t0\npuddle\tsurprise\t0\npuddle\ttrust\t0\npuff\tanger\t0\npuff\tanticipation\t0\npuff\tdisgust\t0\npuff\tfear\t0\npuff\tjoy\t0\npuff\tnegative\t0\npuff\tpositive\t0\npuff\tsadness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urprise\t1\nrandomly\ttrust\t0\nrandomness\tanger\t0\nrandomness\tanticipation\t0\nrandomness\tdisgust\t0\nrandomness\tfear\t0\nrandomness\tjoy\t0\nrandomness\tnegative\t0\nrandomness\tpositive\t0\nrandomness\tsadness\t0\nrandomness\tsurprise\t0\nrandomness\ttrust\t0\nrandy\tanger\t0\nrandy\tanticipation\t0\nrandy\tdisgust\t0\nrandy\tfear\t0\nrandy\tjoy\t0\nrandy\tnegative\t0\nrandy\tpositive\t0\nrandy\tsadness\t0\nrandy\tsurprise\t0\nrandy\ttrust\t0\nranger\tanger\t0\nranger\tanticipation\t0\nranger\tdisgust\t0\nranger\tfear\t0\nranger\tjoy\t0\nranger\tnegative\t0\nranger\tpositive\t0\nranger\tsadness\t0\nranger\tsurprise\t0\nranger\ttrust\t1\nrank\tanger\t0\nrank\tanticipation\t0\nrank\tdisgust\t0\nrank\tfear\t0\nrank\tjoy\t0\nrank\tnegative\t0\nrank\tpositive\t0\nrank\tsadness\t0\nrank\tsurprise\t0\nrank\ttrust\t0\nransom\tanger\t1\nransom\tanticipation\t0\nransom\tdisgust\t0\nransom\tfear\t1\nransom\tjoy\t0\nransom\tnegative\t1\nransom\tpositive\t0\nransom\tsadness\t0\nransom\tsurprise\t0\nransom\ttrust\t0\nrant\tanger\t0\nrant\tanticipation\t0\nrant\tdisgust\t0\nrant\tfear\t0\nrant\tjoy\t0\nrant\tnegative\t0\nrant\tpositive\t0\nrant\tsadness\t0\nrant\tsurprise\t0\nrant\ttrust\t0\nrap\tanger\t0\nrap\tanticipation\t0\nrap\tdisgust\t0\nrap\tfear\t0\nrap\tjoy\t0\nrap\tnegative\t0\nrap\tpositive\t0\nrap\tsadness\t0\nrap\tsurprise\t0\nrap\ttrust\t0\nrape\tanger\t1\nrape\tanticipation\t0\nrape\tdisgust\t1\nrape\tfear\t1\nrape\tjoy\t0\nrape\tnegative\t1\nrape\tpositive\t0\nrape\tsadness\t1\nrape\tsurprise\t0\nrape\ttrust\t0\nrapid\tanger\t0\nrapid\tanticipation\t0\nrapid\tdisgust\t0\nrapid\tfear\t0\nrapid\tjoy\t0\nrapid\tnegative\t0\nrapid\tpositive\t0\nrapid\tsadness\t0\nrapid\tsurprise\t1\nrapid\ttrust\t0\nrapidity\tanger\t0\nrapidity\tanticipation\t0\nrapidity\tdisgust\t0\nrapidity\tfear\t0\nrapidity\tjoy\t0\nrapidity\tnegative\t0\nrapidity\tpositive\t0\nrapidity\tsadness\t0\nrapidity\tsurprise\t0\nrapidity\ttrust\t0\nrapids\tanger\t0\nrapids\tanticipation\t0\nrapids\tdisgust\t0\nrapids\tfear\t0\nrapids\tjoy\t0\nrapids\tnegative\t0\nrapids\tpositive\t0\nrapids\tsadness\t0\nrapids\tsurprise\t0\nrapids\ttrust\t0\nrapping\tanger\t1\nrapping\tanticipation\t0\nrapping\tdisgust\t0\nrapping\tfear\t0\nrapping\tjoy\t0\nrapping\tnegative\t0\nrapping\tpositive\t0\nrapping\tsadness\t0\nrapping\tsurprise\t0\nrapping\ttrust\t0\nrapt\tanger\t0\nrapt\tanticipation\t0\nrapt\tdisgust\t0\nrapt\tfear\t0\nrapt\tjoy\t1\nrapt\tnegative\t0\nrapt\tpositive\t1\nrapt\tsadness\t0\nrapt\tsurprise\t1\nrapt\ttrust\t1\nraptors\tanger\t0\nraptors\tanticipation\t0\nraptors\tdisgust\t0\nraptors\tfear\t1\nraptors\tjoy\t0\nraptors\tnegative\t1\nraptors\tpositive\t0\nraptors\tsadness\t0\nraptors\tsurprise\t0\nraptors\ttrust\t0\nrapture\tanger\t0\nrapture\tanticipation\t1\nrapture\tdisgust\t0\nrapture\tfear\t0\nrapture\tjoy\t1\nrapture\tnegative\t0\nrapture\tpositive\t1\nrapture\tsadness\t0\nrapture\tsurprise\t0\nrapture\ttrust\t0\nrarely\tanger\t0\nrarely\tanticipation\t0\nrarely\tdisgust\t0\nrarely\tfear\t0\nrarely\tjoy\t0\nrarely\tnegative\t0\nrarely\tpositive\t0\nrarely\tsadness\t0\nrarely\tsurprise\t0\nrarely\ttrust\t0\nrarity\tanger\t0\nrarity\tanticipation\t0\nrarity\tdisgust\t0\nrarity\tfear\t0\nrarity\tjoy\t0\nrarity\tnegative\t0\nrarity\tpositive\t0\nrarity\tsadness\t0\nrarity\tsurprise\t1\nrarity\ttrust\t0\nrascal\tanger\t1\nrascal\tanticipation\t0\nrascal\tdisgust\t1\nrascal\tfear\t1\nrascal\tjoy\t0\nrascal\tnegative\t1\nrascal\tpositive\t0\nrascal\tsadness\t0\nrascal\tsurprise\t0\nrascal\ttrust\t0\nrash\tanger\t0\nrash\tanticipation\t0\nrash\tdisgust\t1\nrash\tfear\t0\nrash\tjoy\t0\nrash\tnegative\t1\nrash\tpositive\t0\nrash\tsadness\t0\nrash\tsurprise\t0\nrash\ttrust\t0\nrat\tanger\t0\nrat\tanticipation\t0\nrat\tdisgust\t1\nrat\tfear\t1\nrat\tjoy\t0\nrat\tnegative\t1\nrat\tpositive\t0\nrat\tsadness\t0\nrat\tsurprise\t0\nrat\ttrust\t0\nratchet\tanger\t0\nratchet\tanticipation\t0\nratchet\tdisgust\t0\nratchet\tfear\t0\nratchet\tjoy\t0\nratchet\tnegative\t0\nratchet\tpositive\t0\nratchet\tsadness\t0\nratchet\tsurprise\t0\nratchet\ttrust\t0\nrate\tanger\t0\nrate\tanticipation\t0\nrate\tdisgust\t0\nrate\tfear\t0\nrate\tjoy\t0\nrate\tnegative\t0\nrate\tpositive\t0\nrate\tsadness\t0\nrate\tsurprise\t0\nrate\ttrust\t0\nratification\tanger\t0\nratification\tanticipation\t0\nratification\tdisgust\t0\nratification\tfear\t0\nratification\tjoy\t0\nratification\tnegative\t0\nratification\tpositive\t0\nratification\tsadness\t0\nratification\tsurprise\t0\nratification\ttrust\t0\nratify\tanger\t0\nratify\tanticipation\t0\nratify\tdisgust\t0\nratify\tfear\t0\nratify\tjoy\t0\nratify\tnegative\t0\nratify\tpositive\t0\nratify\tsadness\t0\nratify\tsurprise\t0\nratify\ttrust\t1\nrating\tanger\t1\nrating\tanticipation\t0\nrating\tdisgust\t0\nrating\tfear\t1\nrating\tjoy\t0\nrating\tnegative\t1\nrating\tpositive\t0\nrating\tsadness\t1\nrating\tsurprise\t0\nrating\ttrust\t0\nratio\tanger\t0\nratio\tanticipation\t0\nratio\tdisgust\t0\nratio\tfear\t0\nratio\t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r\tjoy\t0\nseminar\tnegative\t0\nseminar\tpositive\t0\nseminar\tsadness\t0\nseminar\tsurprise\t0\nseminar\ttrust\t0\nseminary\tanger\t0\nseminary\tanticipation\t0\nseminary\tdisgust\t0\nseminary\tfear\t0\nseminary\tjoy\t0\nseminary\tnegative\t0\nseminary\tpositive\t0\nseminary\tsadness\t0\nseminary\tsurprise\t0\nseminary\ttrust\t0\nsemiotics\tanger\t0\nsemiotics\tanticipation\t0\nsemiotics\tdisgust\t0\nsemiotics\tfear\t0\nsemiotics\tjoy\t0\nsemiotics\tnegative\t0\nsemiotics\tpositive\t0\nsemiotics\tsadness\t0\nsemiotics\tsurprise\t0\nsemiotics\ttrust\t0\nsenate\tanger\t0\nsenate\tanticipation\t0\nsenate\tdisgust\t0\nsenate\tfear\t0\nsenate\tjoy\t0\nsenate\tnegative\t0\nsenate\tpositive\t0\nsenate\tsadness\t0\nsenate\tsurprise\t0\nsenate\ttrust\t1\nsenator\tanger\t0\nsenator\tanticipation\t0\nsenator\tdisgust\t0\nsenator\tfear\t0\nsenator\tjoy\t0\nsenator\tnegative\t0\nsenator\tpositive\t0\nsenator\tsadness\t0\nsenator\tsurprise\t0\nsenator\ttrust\t0\nsend\tanger\t0\nsend\tanticipation\t0\nsend\tdisgust\t0\nsend\tfear\t0\nsend\tjoy\t0\nsend\tnegative\t0\nsend\tpositive\t0\nsend\tsadness\t0\nsend\tsurprise\t0\nsend\ttrust\t0\nsenescence\tanger\t0\nsenescence\tanticipation\t0\nsenescence\tdisgust\t0\nsenescence\tfear\t0\nsenescence\tjoy\t0\nsenescence\tnegative\t0\nsenescence\tpositive\t0\nsenescence\tsadness\t0\nsenescence\tsurprise\t0\nsenescence\ttrust\t0\nsenile\tanger\t0\nsenile\tanticipation\t0\nsenile\tdisgust\t0\nsenile\tfear\t1\nsenile\tjoy\t0\nsenile\tnegative\t1\nsenile\tpositive\t0\nsenile\tsadness\t1\nsenile\tsurprise\t0\nsenile\ttrust\t0\nsenior\tanger\t0\nsenior\tanticipation\t0\nsenior\tdisgust\t0\nsenior\tfear\t0\nsenior\tjoy\t0\nsenior\tnegative\t0\nsenior\tpositive\t0\nsenior\tsadness\t0\nsenior\tsurprise\t0\nsenior\ttrust\t0\nseniority\tanger\t0\nseniority\tanticipation\t0\nseniority\tdisgust\t0\nseniority\tfear\t0\nseniority\tjoy\t0\nseniority\tnegative\t0\nseniority\tpositive\t1\nseniority\tsadness\t0\nseniority\tsurprise\t0\nseniority\ttrust\t1\nsensation\tanger\t0\nsensation\tanticipation\t0\nsensation\tdisgust\t0\nsensation\tfear\t0\nsensation\tjoy\t0\nsensation\tnegative\t0\nsensation\tpositive\t0\nsensation\tsadness\t0\nsensation\tsurprise\t0\nsensation\ttrust\t0\nsensational\tanger\t0\nsensational\tanticipation\t0\nsensational\tdisgust\t0\nsensational\tfear\t0\nsensational\tjoy\t1\nsensational\tnegative\t0\nsensational\tpositive\t1\nsensational\tsadness\t0\nsensational\tsurprise\t0\nsensational\ttrust\t0\nsense\tanger\t0\nsense\tanticipation\t0\nsense\tdisgust\t0\nsense\tfear\t0\nsense\tjoy\t0\nsense\tnegative\t0\nsense\tpositive\t1\nsense\tsadness\t0\nsense\tsurprise\t0\nsense\ttrust\t0\nsenseless\tanger\t1\nsenseless\tanticipation\t0\nsenseless\tdisgust\t1\nsenseless\tfear\t1\nsenseless\tjoy\t0\nsenseless\tnegative\t1\nsenseless\tpositive\t0\nsenseless\tsadness\t1\nsenseless\tsurprise\t1\nsenseless\ttrust\t0\nsenses\tanger\t0\nsenses\tanticipation\t0\nsenses\tdisgust\t0\nsenses\tfear\t0\nsenses\tjoy\t0\nsenses\tnegative\t0\nsenses\tpositive\t0\nsenses\tsadness\t0\nsenses\tsurprise\t0\nsenses\ttrust\t0\nsensibility\tanger\t0\nsensibility\tanticipation\t0\nsensibility\tdisgust\t0\nsensibility\tfear\t0\nsensibility\tjoy\t0\nsensibility\tnegative\t0\nsensibility\tpositive\t1\nsensibility\tsadness\t0\nsensibility\tsurprise\t0\nsensibility\ttrust\t0\nsensibly\tanger\t0\nsensibly\tanticipation\t0\nsensibly\tdisgust\t0\nsensibly\tfear\t0\nsensibly\tjoy\t0\nsensibly\tnegative\t0\nsensibly\tpositive\t1\nsensibly\tsadness\t0\nsensibly\tsurprise\t0\nsensibly\ttrust\t0\nsensitive\tanger\t0\nsensitive\tanticipation\t0\nsensitive\tdisgust\t0\nsensitive\tfear\t0\nsensitive\tjoy\t0\nsensitive\tnegative\t0\nsensitive\tpositive\t0\nsensitive\tsadness\t0\nsensitive\tsurprise\t0\nsensitive\ttrust\t0\nsensory\tanger\t0\nsensory\tanticipation\t0\nsensory\tdisgust\t0\nsensory\tfear\t0\nsensory\tjoy\t0\nsensory\tnegative\t0\nsensory\tpositive\t0\nsensory\tsadness\t0\nsensory\tsurprise\t0\nsensory\ttrust\t0\nsensual\tanger\t0\nsensual\tanticipation\t1\nsensual\tdisgust\t0\nsensual\tfear\t0\nsensual\tjoy\t1\nsensual\tnegative\t1\nsensual\tpositive\t1\nsensual\tsadness\t0\nsensual\tsurprise\t1\nsensual\ttrust\t1\nsensuality\tanger\t0\nsensuality\tanticipation\t1\nsensuality\tdisgust\t0\nsensuality\tfear\t0\nsensuality\tjoy\t1\nsensuality\tnegative\t0\nsensuality\tpositive\t1\nsensuality\tsadness\t0\nsensuality\tsurprise\t0\nsensuality\ttrust\t0\nsensuous\tanger\t0\nsensuous\tanticipation\t0\nsensuous\tdisgust\t0\nsensuous\tfear\t0\nsensuous\tjoy\t1\nsensuous\tnegative\t0\nsensuous\tpositive\t1\nsensuous\tsadness\t0\nsensuous\tsurprise\t0\nsensuous\ttrust\t0\nsentence\tanger\t1\nsentence\tanticipation\t1\nsentence\tdisgust\t1\nsentence\tfear\t1\nsentence\tjoy\t0\nsentence\tnegative\t1\nsentence\tpositive\t0\nsentence\tsadness\t1\nsentence\tsurprise\t0\nsentence\ttrust\t0\nsentient\tanger\t0\nsentient\tanticipation\t0\nsentient\tdisgust\t0\nsentient\tfear\t0\nsentient\tjoy\t0\nsentient\tnegative\t0\nsentient\t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adowy\tpositive\t0\nshadowy\tsadness\t0\nshadowy\tsurprise\t0\nshadowy\ttrust\t0\nshady\tanger\t0\nshady\tanticipation\t0\nshady\tdisgust\t0\nshady\tfear\t1\nshady\tjoy\t0\nshady\tnegative\t1\nshady\tpositive\t0\nshady\tsadness\t0\nshady\tsurprise\t0\nshady\ttrust\t0\nshaft\tanger\t0\nshaft\tanticipation\t0\nshaft\tdisgust\t0\nshaft\tfear\t0\nshaft\tjoy\t0\nshaft\tnegative\t0\nshaft\tpositive\t0\nshaft\tsadness\t0\nshaft\tsurprise\t0\nshaft\ttrust\t0\nshag\tanger\t0\nshag\tanticipation\t0\nshag\tdisgust\t0\nshag\tfear\t0\nshag\tjoy\t0\nshag\tnegative\t0\nshag\tpositive\t0\nshag\tsadness\t0\nshag\tsurprise\t0\nshag\ttrust\t0\nshaggy\tanger\t0\nshaggy\tanticipation\t0\nshaggy\tdisgust\t0\nshaggy\tfear\t0\nshaggy\tjoy\t0\nshaggy\tnegative\t0\nshaggy\tpositive\t0\nshaggy\tsadness\t0\nshaggy\tsurprise\t0\nshaggy\ttrust\t0\nshake\tanger\t0\nshake\tanticipation\t0\nshake\tdisgust\t0\nshake\tfear\t0\nshake\tjoy\t0\nshake\tnegative\t0\nshake\tpositive\t0\nshake\tsadness\t0\nshake\tsurprise\t0\nshake\ttrust\t0\nshaken\tanger\t0\nshaken\tanticipation\t0\nshaken\tdisgust\t0\nshaken\tfear\t0\nshaken\tjoy\t0\nshaken\tnegative\t0\nshaken\tpositive\t0\nshaken\tsadness\t0\nshaken\tsurprise\t0\nshaken\ttrust\t0\nshaking\tanger\t0\nshaking\tanticipation\t0\nshaking\tdisgust\t0\nshaking\tfear\t1\nshaking\tjoy\t0\nshaking\tnegative\t1\nshaking\tpositive\t0\nshaking\tsadness\t0\nshaking\tsurprise\t0\nshaking\ttrust\t0\nshaky\tanger\t1\nshaky\tanticipation\t1\nshaky\tdisgust\t0\nshaky\tfear\t1\nshaky\tjoy\t0\nshaky\tnegative\t1\nshaky\tpositive\t0\nshaky\tsadness\t0\nshaky\tsurprise\t0\nshaky\ttrust\t0\nsham\tanger\t1\nsham\tanticipation\t0\nsham\tdisgust\t1\nsham\tfear\t0\nsham\tjoy\t0\nsham\tnegative\t1\nsham\tpositive\t0\nsham\tsadness\t0\nsham\tsurprise\t0\nsham\ttrust\t0\nshaman\tanger\t0\nshaman\tanticipation\t0\nshaman\tdisgust\t0\nshaman\tfear\t0\nshaman\tjoy\t0\nshaman\tnegative\t0\nshaman\tpositive\t0\nshaman\tsadness\t0\nshaman\tsurprise\t0\nshaman\ttrust\t0\nshambles\tanger\t0\nshambles\tanticipation\t0\nshambles\tdisgust\t0\nshambles\tfear\t0\nshambles\tjoy\t0\nshambles\tnegative\t1\nshambles\tpositive\t0\nshambles\tsadness\t0\nshambles\tsurprise\t0\nshambles\ttrust\t0\nshame\tanger\t0\nshame\tanticipation\t0\nshame\tdisgust\t1\nshame\tfear\t1\nshame\tjoy\t0\nshame\tnegative\t1\nshame\tpositive\t0\nshame\tsadness\t1\nshame\tsurprise\t0\nshame\ttrust\t0\nshameful\tanger\t0\nshameful\tanticipation\t0\nshameful\tdisgust\t0\nshameful\tfear\t0\nshameful\tjoy\t0\nshameful\tnegative\t1\nshameful\tpositive\t0\nshameful\tsadness\t1\nshameful\tsurprise\t0\nshameful\ttrust\t0\nshameless\tanger\t0\nshameless\tanticipation\t0\nshameless\tdisgust\t1\nshameless\tfear\t0\nshameless\tjoy\t0\nshameless\tnegative\t1\nshameless\tpositive\t0\nshameless\tsadness\t0\nshameless\tsurprise\t0\nshameless\ttrust\t0\nshanghai\tanger\t0\nshanghai\tanticipation\t0\nshanghai\tdisgust\t1\nshanghai\tfear\t1\nshanghai\tjoy\t0\nshanghai\tnegative\t1\nshanghai\tpositive\t0\nshanghai\tsadness\t0\nshanghai\tsurprise\t0\nshanghai\ttrust\t0\nshank\tanger\t0\nshank\tanticipation\t0\nshank\tdisgust\t0\nshank\tfear\t1\nshank\tjoy\t0\nshank\tnegative\t0\nshank\tpositive\t0\nshank\tsadness\t0\nshank\tsurprise\t0\nshank\ttrust\t0\nshanty\tanger\t0\nshanty\tanticipation\t0\nshanty\tdisgust\t0\nshanty\tfear\t0\nshanty\tjoy\t0\nshanty\tnegative\t0\nshanty\tpositive\t0\nshanty\tsadness\t0\nshanty\tsurprise\t0\nshanty\ttrust\t0\nshape\tanger\t0\nshape\tanticipation\t0\nshape\tdisgust\t0\nshape\tfear\t0\nshape\tjoy\t0\nshape\tnegative\t0\nshape\tpositive\t1\nshape\tsadness\t0\nshape\tsurprise\t0\nshape\ttrust\t0\nshapely\tanger\t0\nshapely\tanticipation\t0\nshapely\tdisgust\t0\nshapely\tfear\t0\nshapely\tjoy\t0\nshapely\tnegative\t0\nshapely\tpositive\t1\nshapely\tsadness\t0\nshapely\tsurprise\t0\nshapely\ttrust\t0\nshare\tanger\t0\nshare\tanticipation\t1\nshare\tdisgust\t0\nshare\tfear\t0\nshare\tjoy\t1\nshare\tnegative\t0\nshare\tpositive\t1\nshare\tsadness\t0\nshare\tsurprise\t0\nshare\ttrust\t1\nshareholder\tanger\t0\nshareholder\tanticipation\t0\nshareholder\tdisgust\t0\nshareholder\tfear\t0\nshareholder\tjoy\t0\nshareholder\tnegative\t0\nshareholder\tpositive\t0\nshareholder\tsadness\t0\nshareholder\tsurprise\t0\nshareholder\ttrust\t0\nshark\tanger\t0\nshark\tanticipation\t0\nshark\tdisgust\t0\nshark\tfear\t0\nshark\tjoy\t0\nshark\tnegative\t1\nshark\tpositive\t0\nshark\tsadness\t0\nshark\tsurprise\t0\nshark\ttrust\t0\nsharpen\tanger\t1\nsharpen\tanticipation\t1\nsharpen\tdisgust\t0\nsharpen\tfear\t0\nsharpen\tjoy\t0\nsharpen\tnegative\t0\nsharpen\tpositive\t0\nsharpen\tsadness\t0\nsharpen\tsurprise\t0\nsharpen\ttrust\t0\nsharpened\tanger\t0\nsharpened\tanticipation\t0\nsharpened\tdisgust\t0\nsharpened\tfear\t0\nsharpened\tjoy\t0\nsharpened\tnegative\t0\nsharpened\tpositive\t0\nsharpened\tsadness\t0\nsharpened\tsurprise\t0\nsharpened\ttrust\t0\nsharpener\tanger\t0\nsharpener\tanticipation\t0\nsharpener\tdisgust\t0\nsharpener\tfear\t0\nsharpener\tjoy\t0\nsharpener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thening\tnegative\t0\nstrengthening\tpositive\t1\nstrengthening\tsadness\t0\nstrengthening\tsurprise\t0\nstrengthening\ttrust\t1\nstrenuous\tanger\t0\nstrenuous\tanticipation\t0\nstrenuous\tdisgust\t0\nstrenuous\tfear\t0\nstrenuous\tjoy\t0\nstrenuous\tnegative\t0\nstrenuous\tpositive\t0\nstrenuous\tsadness\t0\nstrenuous\tsurprise\t0\nstrenuous\ttrust\t0\nstress\tanger\t0\nstress\tanticipation\t0\nstress\tdisgust\t0\nstress\tfear\t0\nstress\tjoy\t0\nstress\tnegative\t1\nstress\tpositive\t0\nstress\tsadness\t0\nstress\tsurprise\t0\nstress\ttrust\t0\nstretch\tanger\t0\nstretch\tanticipation\t0\nstretch\tdisgust\t0\nstretch\tfear\t0\nstretch\tjoy\t0\nstretch\tnegative\t0\nstretch\tpositive\t0\nstretch\tsadness\t0\nstretch\tsurprise\t0\nstretch\ttrust\t0\nstretcher\tanger\t0\nstretcher\tanticipation\t0\nstretcher\tdisgust\t0\nstretcher\tfear\t1\nstretcher\tjoy\t0\nstretcher\tnegative\t0\nstretcher\tpositive\t0\nstretcher\tsadness\t1\nstretcher\tsurprise\t0\nstretcher\ttrust\t0\nstricken\tanger\t0\nstricken\tanticipation\t0\nstricken\tdisgust\t0\nstricken\tfear\t0\nstricken\tjoy\t0\nstricken\tnegative\t0\nstricken\tpositive\t0\nstricken\tsadness\t1\nstricken\tsurprise\t0\nstricken\ttrust\t0\nstride\tanger\t0\nstride\tanticipation\t0\nstride\tdisgust\t0\nstride\tfear\t0\nstride\tjoy\t0\nstride\tnegative\t0\nstride\tpositive\t0\nstride\tsadness\t0\nstride\tsurprise\t0\nstride\ttrust\t0\nstrife\tanger\t1\nstrife\tanticipation\t0\nstrife\tdisgust\t0\nstrife\tfear\t0\nstrife\tjoy\t0\nstrife\tnegative\t1\nstrife\tpositive\t0\nstrife\tsadness\t0\nstrife\tsurprise\t0\nstrife\ttrust\t0\nstrike\tanger\t1\nstrike\tanticipation\t0\nstrike\tdisgust\t0\nstrike\tfear\t0\nstrike\tjoy\t0\nstrike\tnegative\t1\nstrike\tpositive\t0\nstrike\tsadness\t0\nstrike\tsurprise\t0\nstrike\ttrust\t0\nstriking\tanger\t0\nstriking\tanticipation\t0\nstriking\tdisgust\t0\nstriking\tfear\t0\nstriking\tjoy\t0\nstriking\tnegative\t0\nstriking\tpositive\t1\nstriking\tsadness\t0\nstriking\tsurprise\t0\nstriking\ttrust\t0\nstrikingly\tanger\t0\nstrikingly\tanticipation\t0\nstrikingly\tdisgust\t0\nstrikingly\tfear\t0\nstrikingly\tjoy\t0\nstrikingly\tnegative\t0\nstrikingly\tpositive\t1\nstrikingly\tsadness\t0\nstrikingly\tsurprise\t0\nstrikingly\ttrust\t0\nstring\tanger\t0\nstring\tanticipation\t0\nstring\tdisgust\t0\nstring\tfear\t0\nstring\tjoy\t0\nstring\tnegative\t0\nstring\tpositive\t0\nstring\tsadness\t0\nstring\tsurprise\t0\nstring\ttrust\t0\nstringy\tanger\t0\nstringy\tanticipation\t0\nstringy\tdisgust\t0\nstringy\tfear\t0\nstringy\tjoy\t0\nstringy\tnegative\t0\nstringy\tpositive\t0\nstringy\tsadness\t0\nstringy\tsurprise\t0\nstringy\ttrust\t0\nstrip\tanger\t0\nstrip\tanticipation\t0\nstrip\tdisgust\t0\nstrip\tfear\t0\nstrip\tjoy\t0\nstrip\tnegative\t1\nstrip\tpositive\t0\nstrip\tsadness\t1\nstrip\tsurprise\t0\nstrip\ttrust\t0\nstripe\tanger\t0\nstripe\tanticipation\t0\nstripe\tdisgust\t0\nstripe\tfear\t0\nstripe\tjoy\t0\nstripe\tnegative\t1\nstripe\tpositive\t0\nstripe\tsadness\t0\nstripe\tsurprise\t0\nstripe\ttrust\t0\nstripped\tanger\t1\nstripped\tanticipation\t1\nstripped\tdisgust\t1\nstripped\tfear\t1\nstripped\tjoy\t0\nstripped\tnegative\t1\nstripped\tpositive\t0\nstripped\tsadness\t1\nstripped\tsurprise\t0\nstripped\ttrust\t0\nstrive\tanger\t0\nstrive\tanticipation\t1\nstrive\tdisgust\t0\nstrive\tfear\t0\nstrive\tjoy\t0\nstrive\tnegative\t0\nstrive\tpositive\t0\nstrive\tsadness\t0\nstrive\tsurprise\t0\nstrive\ttrust\t0\nstrobe\tanger\t0\nstrobe\tanticipation\t0\nstrobe\tdisgust\t0\nstrobe\tfear\t0\nstrobe\tjoy\t0\nstrobe\tnegative\t0\nstrobe\tpositive\t0\nstrobe\tsadness\t0\nstrobe\tsurprise\t0\nstrobe\ttrust\t0\nstroke\tanger\t0\nstroke\tanticipation\t0\nstroke\tdisgust\t0\nstroke\tfear\t1\nstroke\tjoy\t0\nstroke\tnegative\t1\nstroke\tpositive\t0\nstroke\tsadness\t1\nstroke\tsurprise\t0\nstroke\ttrust\t0\nstroll\tanger\t0\nstroll\tanticipation\t0\nstroll\tdisgust\t0\nstroll\tfear\t0\nstroll\tjoy\t0\nstroll\tnegative\t0\nstroll\tpositive\t0\nstroll\tsadness\t0\nstroll\tsurprise\t0\nstroll\ttrust\t0\nstronghold\tanger\t0\nstronghold\tanticipation\t0\nstronghold\tdisgust\t0\nstronghold\tfear\t0\nstronghold\tjoy\t0\nstronghold\tnegative\t0\nstronghold\tpositive\t0\nstronghold\tsadness\t0\nstronghold\tsurprise\t0\nstronghold\ttrust\t0\nstrongly\tanger\t0\nstrongly\tanticipation\t0\nstrongly\tdisgust\t0\nstrongly\tfear\t0\nstrongly\tjoy\t0\nstrongly\tnegative\t0\nstrongly\tpositive\t1\nstrongly\tsadness\t0\nstrongly\tsurprise\t0\nstrongly\ttrust\t0\nstructural\tanger\t0\nstructural\tanticipation\t0\nstructural\tdisgust\t0\nstructural\tfear\t0\nstructural\tjoy\t0\nstructural\tnegative\t0\nstructural\tpositive\t0\nstructural\tsadness\t0\nstructural\tsurprise\t0\nstructural\ttrust\t1\nstructure\tanger\t0\nstructure\tanticipation\t0\nstructure\tdisgust\t0\nstructure\tfear\t0\nstructure\tjoy\t0\nstructure\tnegative\t0\nstructure\tpositive\t1\nstructure\tsadness\t0\nstructure\tsurprise\t0\nstructure\ttrust\t1\nstruggle\tanger\t1\nstruggle\tanticipation\t0\nstruggle\tdisgust\t0\nstruggle\tfear\t1\nstruggle\tjoy\t0\nstruggle\tnegative\t1\nstruggle\tpositive\t0\nstruggle\tsadness\t1\nstruggle\tsurprise\t0\nstruggle\ttrust\t0\nstrut\tanger\t0\nstrut\tanticipation\t0\nstrut\tdisgust\t0\nstrut\tfear\t0\nstrut\tjoy\t0\nstrut\tnegative\t1\nstrut\tpositive\t0\nstrut\tsadness\t0\nstrut\tsurprise\t0\nstrut\ttrust\t0\nstubble\tanger\t0\nstubble\tanticipation\t0\nstubble\tdisgust\t0\nstubble\tfear\t0\nstubble\tjoy\t0\nstubble\tnegative\t0\nstubble\tpositive\t0\nstubble\tsadness\t0\nstubble\tsurprise\t0\nstubble\ttrust\t0\nstubbornness\tanger\t0\nstubbornness\tanticipation\t0\nstubbornness\tdisgust\t0\nstubbornness\tfear\t0\nstubbornness\tjoy\t0\nstubbornness\tnegative\t0\nstubbornness\tpositive\t0\nstubbornness\tsadness\t0\nstubbornness\tsurprise\t0\nstubbornness\ttrust\t0\nstubby\tanger\t0\nstubby\tanticipation\t0\nstubby\tdisgust\t0\nstubby\tfear\t0\nstubby\tjoy\t0\nstubby\tnegative\t0\nstubby\tpositive\t0\nstubby\tsadness\t0\nstubby\tsurprise\t0\nstubby\ttrust\t0\nstucco\tanger\t0\nstucco\tanticipation\t0\nstucco\tdisgust\t0\nstucco\tfear\t0\nstucco\tjoy\t0\nstucco\tnegative\t0\nstucco\tpositive\t0\nstucco\tsadness\t0\nstucco\tsurprise\t0\nstucco\ttrust\t0\nstuck\tanger\t0\nstuck\tanticipation\t0\nstuck\tdisgust\t0\nstuck\tfear\t0\nstuck\tjoy\t0\nstuck\tnegative\t0\nstuck\tpositive\t0\nstuck\tsadness\t0\nstuck\tsurprise\t0\nstuck\ttrust\t0\nstud\tanger\t0\nstud\tanticipation\t0\nstud\tdisgust\t0\nstud\tfear\t0\nstud\tjoy\t0\nstud\tnegative\t0\nstud\tpositive\t1\nstud\tsadness\t0\nstud\tsurprise\t0\nstud\ttrust\t0\nstudded\tanger\t0\nstudded\tanticipation\t0\nstudded\tdisgust\t0\nstudded\tfear\t0\nstudded\tjoy\t0\nstudded\tnegative\t0\nstudded\tpositive\t0\nstudded\tsadness\t0\nstudded\tsurprise\t0\nstudded\ttrust\t0\nstudent\tanger\t0\nstudent\tanticipation\t0\nstudent\tdisgust\t0\nstudent\tfear\t0\nstudent\tjoy\t0\nstudent\tnegative\t0\nstudent\tpositive\t0\nstudent\tsadness\t0\nstudent\tsurprise\t0\nstudent\ttrust\t0\nstudied\tanger\t0\nstudied\tanticipation\t0\nstudied\tdisgust\t0\nstudied\tfear\t0\nstudied\tjoy\t0\nstudied\tnegative\t0\nstudied\tpositive\t0\nstudied\tsadness\t0\nstudied\tsurprise\t0\nstudied\ttrust\t0\nstudio\tanger\t0\nstudio\tanticipation\t0\nstudio\tdisgust\t0\nstudio\tfear\t0\nstudio\tjoy\t0\nstudio\tnegative\t0\nstudio\tpositive\t0\nstudio\tsadness\t0\nstudio\tsurprise\t0\nstudio\ttrust\t0\nstudy\tanger\t0\nstudy\tanticipation\t0\nstudy\tdisgust\t0\nstudy\tfear\t0\nstudy\tjoy\t0\nstudy\tnegative\t0\nstudy\tpositive\t1\nstudy\tsadness\t0\nstudy\tsurprise\t0\nstudy\ttrust\t0\nstuff\tanger\t0\nstuff\tanticipation\t0\nstuff\tdisgust\t0\nstuff\tfear\t0\nstuff\tjoy\t0\nstuff\tnegative\t0\nstuff\tpositive\t0\nstuff\tsadness\t0\nstuff\tsurprise\t0\nstuff\ttrust\t0\nstuffing\tanger\t0\nstuffing\tanticipation\t0\nstuffing\tdisgust\t0\nstuffing\tfear\t0\nstuffing\tjoy\t0\nstuffing\tnegative\t0\nstuffing\tpositive\t0\nstuffing\tsadness\t0\nstuffing\tsurprise\t0\nstuffing\ttrust\t0\nstuffy\tanger\t0\nstuffy\tanticipation\t0\nstuffy\tdisgust\t0\nstuffy\tfear\t0\nstuffy\tjoy\t0\nstuffy\tnegative\t1\nstuffy\tpositive\t0\nstuffy\tsadness\t0\nstuffy\tsurprise\t0\nstuffy\ttrust\t0\nstumble\tanger\t0\nstumble\tanticipation\t0\nstumble\tdisgust\t0\nstumble\tfear\t0\nstumble\tjoy\t0\nstumble\tnegative\t1\nstumble\tpositive\t0\nstumble\tsadness\t0\nstumble\tsurprise\t0\nstumble\ttrust\t0\nstump\tanger\t0\nstump\tanticipation\t0\nstump\tdisgust\t0\nstump\tfear\t0\nstump\tjoy\t0\nstump\tnegative\t0\nstump\tpositive\t0\nstump\tsadness\t0\nstump\tsurprise\t0\nstump\ttrust\t0\nstunned\tanger\t0\nstunned\tanticipation\t0\nstunned\tdisgust\t0\nstunned\tfear\t1\nstunned\tjoy\t0\nstunned\tnegative\t1\nstunned\tpositive\t0\nstunned\tsadness\t0\nstunned\tsurprise\t1\nstunned\ttrust\t0\nstunt\tanger\t0\nstunt\tanticipation\t0\nstunt\tdisgust\t0\nstunt\tfear\t0\nstunt\tjoy\t0\nstunt\tnegative\t0\nstunt\tpositive\t0\nstunt\tsadness\t0\nstunt\tsurprise\t0\nstunt\ttrust\t0\nstunted\tanger\t0\nstunted\tanticipation\t0\nstunted\tdisgust\t0\nstunted\tfear\t0\nstunted\tjoy\t0\nstunted\tnegative\t1\nstunted\tpositive\t0\nstunted\tsadness\t0\nstunted\tsurprise\t0\nstunted\ttrust\t0\nstupendous\tanger\t0\nstupendous\tanticipation\t0\nstupendous\tdisgust\t0\nstupendous\tfear\t0\nstupendous\tjoy\t0\nstupendous\tnegative\t0\nstupendous\tpositive\t0\nstupendous\tsadness\t0\nstupendous\tsurprise\t0\nstupendous\ttrust\t0\nstupid\tanger\t0\nstupid\tanticipation\t0\nstupid\tdisgust\t0\nstupid\tfear\t0\nstupid\tjoy\t0\nstupid\tnegative\t1\nstupid\tpositive\t0\nstupid\tsadness\t0\nstupid\tsurprise\t0\nstupid\ttrust\t0\nstupidity\tanger\t0\nstupidity\tanticipation\t0\nstupidity\tdisgust\t0\nstupidity\tfear\t0\nstupidity\tjoy\t0\nstupidity\tnegative\t1\nstupidity\tpositive\t0\nstupidity\tsadness\t0\nstupidity\tsurprise\t0\nstupidity\ttrust\t0\nstupor\tanger\t0\nstupor\tanticipation\t0\nstupor\tdisgust\t0\nstupor\tfear\t0\nstupor\tjoy\t0\nstupor\tnegative\t1\nstupor\tpositive\t0\nstupor\tsadne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\tpositive\t0\ntestimony\tsadness\t0\ntestimony\tsurprise\t0\ntestimony\ttrust\t1\ntetanus\tanger\t0\ntetanus\tanticipation\t0\ntetanus\tdisgust\t1\ntetanus\tfear\t0\ntetanus\tjoy\t0\ntetanus\tnegative\t1\ntetanus\tpositive\t0\ntetanus\tsadness\t0\ntetanus\tsurprise\t0\ntetanus\ttrust\t0\ntether\tanger\t0\ntether\tanticipation\t0\ntether\tdisgust\t0\ntether\tfear\t0\ntether\tjoy\t0\ntether\tnegative\t1\ntether\tpositive\t0\ntether\tsadness\t0\ntether\tsurprise\t0\ntether\ttrust\t0\ntethered\tanger\t0\ntethered\tanticipation\t0\ntethered\tdisgust\t0\ntethered\tfear\t0\ntethered\tjoy\t0\ntethered\tnegative\t0\ntethered\tpositive\t0\ntethered\tsadness\t0\ntethered\tsurprise\t0\ntethered\ttrust\t0\ntetrahedral\tanger\t0\ntetrahedral\tanticipation\t0\ntetrahedral\tdisgust\t0\ntetrahedral\tfear\t0\ntetrahedral\tjoy\t0\ntetrahedral\tnegative\t0\ntetrahedral\tpositive\t0\ntetrahedral\tsadness\t0\ntetrahedral\tsurprise\t0\ntetrahedral\ttrust\t0\ntext\tanger\t0\ntext\tanticipation\t0\ntext\tdisgust\t0\ntext\tfear\t0\ntext\tjoy\t0\ntext\tnegative\t0\ntext\tpositive\t0\ntext\tsadness\t0\ntext\tsurprise\t0\ntext\ttrust\t0\ntextbook\tanger\t0\ntextbook\tanticipation\t0\ntextbook\tdisgust\t0\ntextbook\tfear\t0\ntextbook\tjoy\t0\ntextbook\tnegative\t0\ntextbook\tpositive\t0\ntextbook\tsadness\t0\ntextbook\tsurprise\t0\ntextbook\ttrust\t0\ntextile\tanger\t0\ntextile\tanticipation\t0\ntextile\tdisgust\t0\ntextile\tfear\t0\ntextile\tjoy\t0\ntextile\tnegative\t0\ntextile\tpositive\t0\ntextile\tsadness\t0\ntextile\tsurprise\t0\ntextile\ttrust\t0\ntextural\tanger\t0\ntextural\tanticipation\t0\ntextural\tdisgust\t0\ntextural\tfear\t0\ntextural\tjoy\t0\ntextural\tnegative\t0\ntextural\tpositive\t0\ntextural\tsadness\t0\ntextural\tsurprise\t0\ntextural\ttrust\t0\ntexture\tanger\t0\ntexture\tanticipation\t0\ntexture\tdisgust\t0\ntexture\tfear\t0\ntexture\tjoy\t0\ntexture\tnegative\t0\ntexture\tpositive\t0\ntexture\tsadness\t0\ntexture\tsurprise\t0\ntexture\ttrust\t0\nthankful\tanger\t0\nthankful\tanticipation\t0\nthankful\tdisgust\t0\nthankful\tfear\t0\nthankful\tjoy\t1\nthankful\tnegative\t0\nthankful\tpositive\t1\nthankful\tsadness\t0\nthankful\tsurprise\t0\nthankful\ttrust\t0\nthanksgiving\tanger\t0\nthanksgiving\tanticipation\t0\nthanksgiving\tdisgust\t0\nthanksgiving\tfear\t0\nthanksgiving\tjoy\t1\nthanksgiving\tnegative\t0\nthanksgiving\tpositive\t1\nthanksgiving\tsadness\t0\nthanksgiving\tsurprise\t0\nthanksgiving\ttrust\t0\nthatch\tanger\t0\nthatch\tanticipation\t0\nthatch\tdisgust\t0\nthatch\tfear\t0\nthatch\tjoy\t0\nthatch\tnegative\t0\nthatch\tpositive\t0\nthatch\tsadness\t0\nthatch\tsurprise\t0\nthatch\ttrust\t0\nthaw\tanger\t0\nthaw\tanticipation\t0\nthaw\tdisgust\t0\nthaw\tfear\t0\nthaw\tjoy\t0\nthaw\tnegative\t0\nthaw\tpositive\t0\nthaw\tsadness\t0\nthaw\tsurprise\t0\nthaw\ttrust\t0\ntheater\tanger\t0\ntheater\tanticipation\t0\ntheater\tdisgust\t0\ntheater\tfear\t0\ntheater\tjoy\t0\ntheater\tnegative\t0\ntheater\tpositive\t0\ntheater\tsadness\t0\ntheater\tsurprise\t0\ntheater\ttrust\t0\ntheatrical\tanger\t0\ntheatrical\tanticipation\t0\ntheatrical\tdisgust\t0\ntheatrical\tfear\t0\ntheatrical\tjoy\t0\ntheatrical\tnegative\t0\ntheatrical\tpositive\t0\ntheatrical\tsadness\t0\ntheatrical\tsurprise\t0\ntheatrical\ttrust\t0\ntheft\tanger\t1\ntheft\tanticipation\t0\ntheft\tdisgust\t1\ntheft\tfear\t1\ntheft\tjoy\t0\ntheft\tnegative\t1\ntheft\tpositive\t0\ntheft\tsadness\t1\ntheft\tsurprise\t0\ntheft\ttrust\t0\ntheism\tanger\t0\ntheism\tanticipation\t0\ntheism\tdisgust\t1\ntheism\tfear\t0\ntheism\tjoy\t0\ntheism\tnegative\t1\ntheism\tpositive\t0\ntheism\tsadness\t0\ntheism\tsurprise\t0\ntheism\ttrust\t0\ntheistic\tanger\t0\ntheistic\tanticipation\t0\ntheistic\tdisgust\t0\ntheistic\tfear\t0\ntheistic\tjoy\t0\ntheistic\tnegative\t0\ntheistic\tpositive\t0\ntheistic\tsadness\t0\ntheistic\tsurprise\t0\ntheistic\ttrust\t0\ntheme\tanger\t0\ntheme\tanticipation\t0\ntheme\tdisgust\t0\ntheme\tfear\t0\ntheme\tjoy\t0\ntheme\tnegative\t0\ntheme\tpositive\t0\ntheme\tsadness\t0\ntheme\tsurprise\t0\ntheme\ttrust\t0\ntheocracy\tanger\t0\ntheocracy\tanticipation\t0\ntheocracy\tdisgust\t0\ntheocracy\tfear\t0\ntheocracy\tjoy\t0\ntheocracy\tnegative\t0\ntheocracy\tpositive\t0\ntheocracy\tsadness\t0\ntheocracy\tsurprise\t0\ntheocracy\ttrust\t0\ntheocratic\tanger\t1\ntheocratic\tanticipation\t0\ntheocratic\tdisgust\t0\ntheocratic\tfear\t1\ntheocratic\tjoy\t0\ntheocratic\tnegative\t1\ntheocratic\tpositive\t0\ntheocratic\tsadness\t1\ntheocratic\tsurprise\t0\ntheocratic\ttrust\t1\ntheologian\tanger\t0\ntheologian\tanticipation\t0\ntheologian\tdisgust\t0\ntheologian\tfear\t0\ntheologian\tjoy\t0\ntheologian\tnegative\t0\ntheologian\tpositive\t0\ntheologian\tsadness\t0\ntheologian\tsurprise\t0\ntheologian\ttrust\t0\ntheological\tanger\t0\ntheological\tanticipation\t0\ntheological\tdisgust\t0\ntheological\tfear\t0\ntheological\tjoy\t0\ntheological\tnegative\t0\ntheological\tpositive\t0\ntheological\tsadness\t0\ntheological\tsurprise\t0\ntheological\ttrust\t1\ntheology\tanger\t0\ntheology\tanticipation\t1\ntheology\tdisgust\t0\ntheology\tfear\t0\ntheology\tjoy\t0\ntheology\tnegative\t0\ntheology\tpositive\t0\ntheology\tsadness\t0\ntheology\tsurprise\t0\ntheology\ttrust\t0\ntheorem\tanger\t0\ntheorem\tanticipation\t0\ntheorem\tdisgust\t0\ntheorem\tfear\t0\ntheorem\tjoy\t0\ntheorem\tnegative\t0\ntheorem\tpositive\t0\ntheorem\tsadness\t0\ntheorem\tsurprise\t0\ntheorem\ttrust\t1\ntheoretical\tanger\t0\ntheoretical\tanticipation\t0\ntheoretical\tdisgust\t0\ntheoretical\tfear\t0\ntheoretical\tjoy\t0\ntheoretical\tnegative\t0\ntheoretical\tpositive\t1\ntheoretical\tsadness\t0\ntheoretical\tsurprise\t0\ntheoretical\ttrust\t0\ntheory\tanger\t0\ntheory\tanticipation\t1\ntheory\tdisgust\t0\ntheory\tfear\t0\ntheory\tjoy\t0\ntheory\tnegative\t0\ntheory\tpositive\t0\ntheory\tsadness\t0\ntheory\tsurprise\t0\ntheory\ttrust\t1\ntherapeutic\tanger\t0\ntherapeutic\tanticipation\t0\ntherapeutic\tdisgust\t0\ntherapeutic\tfear\t0\ntherapeutic\tjoy\t1\ntherapeutic\tnegative\t0\ntherapeutic\tpositive\t1\ntherapeutic\tsadness\t0\ntherapeutic\tsurprise\t0\ntherapeutic\ttrust\t1\ntherapeutics\tanger\t0\ntherapeutics\tanticipation\t0\ntherapeutics\tdisgust\t0\ntherapeutics\tfear\t0\ntherapeutics\tjoy\t0\ntherapeutics\tnegative\t0\ntherapeutics\tpositive\t1\ntherapeutics\tsadness\t0\ntherapeutics\tsurprise\t0\ntherapeutics\ttrust\t0\nthereabouts\tanger\t0\nthereabouts\tanticipation\t0\nthereabouts\tdisgust\t0\nthereabouts\tfear\t0\nthereabouts\tjoy\t0\nthereabouts\tnegative\t0\nthereabouts\tpositive\t0\nthereabouts\tsadness\t0\nthereabouts\tsurprise\t0\nthereabouts\ttrust\t0\nthereof\tanger\t0\nthereof\tanticipation\t0\nthereof\tdisgust\t0\nthereof\tfear\t0\nthereof\tjoy\t0\nthereof\tnegative\t0\nthereof\tpositive\t0\nthereof\tsadness\t0\nthereof\tsurprise\t0\nthereof\ttrust\t0\ntherewith\tanger\t0\ntherewith\tanticipation\t0\ntherewith\tdisgust\t0\ntherewith\tfear\t0\ntherewith\tjoy\t0\ntherewith\tnegative\t0\ntherewith\tpositive\t0\ntherewith\tsadness\t0\ntherewith\tsurprise\t0\ntherewith\ttrust\t0\nthermal\tanger\t0\nthermal\tanticipation\t0\nthermal\tdisgust\t0\nthermal\tfear\t0\nthermal\tjoy\t0\nthermal\tnegative\t0\nthermal\tpositive\t0\nthermal\tsadness\t0\nthermal\tsurprise\t0\nthermal\ttrust\t0\nthermocouple\tanger\t0\nthermocouple\tanticipation\t1\nthermocouple\tdisgust\t0\nthermocouple\tfear\t0\nthermocouple\tjoy\t0\nthermocouple\tnegative\t0\nthermocouple\tpositive\t0\nthermocouple\tsadness\t0\nthermocouple\tsurprise\t0\nthermocouple\ttrust\t0\nthermodynamics\tanger\t0\nthermodynamics\tanticipation\t0\nthermodynamics\tdisgust\t0\nthermodynamics\tfear\t0\nthermodynamics\tjoy\t0\nthermodynamics\tnegative\t0\nthermodynamics\tpositive\t0\nthermodynamics\tsadness\t0\nthermodynamics\tsurprise\t0\nthermodynamics\ttrust\t0\nthermometer\tanger\t0\nthermometer\tanticipation\t0\nthermometer\tdisgust\t0\nthermometer\tfear\t0\nthermometer\tjoy\t0\nthermometer\tnegative\t0\nthermometer\tpositive\t0\nthermometer\tsadness\t0\nthermometer\tsurprise\t0\nthermometer\ttrust\t1\nthermostat\tanger\t0\nthermostat\tanticipation\t0\nthermostat\tdisgust\t0\nthermostat\tfear\t0\nthermostat\tjoy\t0\nthermostat\tnegative\t0\nthermostat\tpositive\t0\nthermostat\tsadness\t0\nthermostat\tsurprise\t0\nthermostat\ttrust\t0\nthesaurus\tanger\t0\nthesaurus\tanticipation\t0\nthesaurus\tdisgust\t0\nthesaurus\tfear\t0\nthesaurus\tjoy\t0\nthesaurus\tnegative\t0\nthesaurus\tpositive\t0\nthesaurus\tsadness\t0\nthesaurus\tsurprise\t0\nthesaurus\ttrust\t0\nthesis\tanger\t0\nthesis\tanticipation\t0\nthesis\tdisgust\t0\nthesis\tfear\t0\nthesis\tjoy\t0\nthesis\tnegative\t0\nthesis\tpositive\t0\nthesis\tsadness\t0\nthesis\tsurprise\t0\nthesis\ttrust\t0\nthick\tanger\t0\nthick\tanticipation\t0\nthick\tdisgust\t0\nthick\tfear\t0\nthick\tjoy\t0\nthick\tnegative\t0\nthick\tpositive\t0\nthick\tsadness\t0\nthick\tsurprise\t0\nthick\ttrust\t0\nthicken\tanger\t0\nthicken\tanticipation\t0\nthicken\tdisgust\t0\nthicken\tfear\t0\nthicken\tjoy\t0\nthicken\tnegative\t0\nthicken\tpositive\t0\nthicken\tsadness\t0\nthicken\tsurprise\t0\nthicken\ttrust\t0\nthickening\tanger\t0\nthickening\tanticipation\t0\nthickening\tdisgust\t0\nthickening\tfear\t0\nthickening\tjoy\t0\nthickening\tnegative\t0\nthickening\tpositive\t0\nthickening\tsadness\t0\nthickening\tsurprise\t0\nthickening\ttrust\t0\nthicket\tanger\t0\nthicket\tanticipation\t0\nthicket\tdisgust\t0\nthicket\tfear\t0\nthicket\tjoy\t0\nthicket\tnegative\t0\nthicket\tpositive\t0\nthicket\tsadness\t0\nthicket\tsurprise\t0\nthicket\ttrust\t0\nthickness\tanger\t0\nthickness\tanticipation\t0\nthickness\tdisgust\t0\nthickness\tfear\t0\nthickness\tjoy\t0\nthickness\tnegative\t0\nthickness\tpositive\t0\nthickness\tsadness\t0\nthickness\tsurprise\t0\nthickness\ttrust\t0\nthief\tanger\t1\nthief\tanticipation\t0\nthief\tdisgust\t1\nthief\tfear\t1\nthief\tjoy\t0\nthief\tnegative\t1\nthief\tpositive\t0\nthief\tsadness\t1\nthief\tsurprise\t1\nthief\ttrust\t0\nthimble\tanger\t0\nthimble\tanticipation\t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mbone\tfear\t0\ntrombone\tjoy\t0\ntrombone\tnegative\t0\ntrombone\tpositive\t0\ntrombone\tsadness\t0\ntrombone\tsurprise\t0\ntrombone\ttrust\t0\ntroop\tanger\t0\ntroop\tanticipation\t0\ntroop\tdisgust\t0\ntroop\tfear\t0\ntroop\tjoy\t0\ntroop\tnegative\t0\ntroop\tpositive\t0\ntroop\tsadness\t0\ntroop\tsurprise\t0\ntroop\ttrust\t0\ntrooper\tanger\t0\ntrooper\tanticipation\t0\ntrooper\tdisgust\t0\ntrooper\tfear\t0\ntrooper\tjoy\t0\ntrooper\tnegative\t0\ntrooper\tpositive\t0\ntrooper\tsadness\t0\ntrooper\tsurprise\t0\ntrooper\ttrust\t0\ntroops\tanger\t0\ntroops\tanticipation\t0\ntroops\tdisgust\t0\ntroops\tfear\t0\ntroops\tjoy\t0\ntroops\tnegative\t0\ntroops\tpositive\t0\ntroops\tsadness\t0\ntroops\tsurprise\t0\ntroops\ttrust\t0\ntrophy\tanger\t0\ntrophy\tanticipation\t1\ntrophy\tdisgust\t0\ntrophy\tfear\t0\ntrophy\tjoy\t1\ntrophy\tnegative\t0\ntrophy\tpositive\t1\ntrophy\tsadness\t0\ntrophy\tsurprise\t1\ntrophy\ttrust\t1\ntropical\tanger\t0\ntropical\tanticipation\t0\ntropical\tdisgust\t0\ntropical\tfear\t0\ntropical\tjoy\t0\ntropical\tnegative\t0\ntropical\tpositive\t0\ntropical\tsadness\t0\ntropical\tsurprise\t0\ntropical\ttrust\t0\ntrot\tanger\t0\ntrot\tanticipation\t0\ntrot\tdisgust\t0\ntrot\tfear\t0\ntrot\tjoy\t0\ntrot\tnegative\t0\ntrot\tpositive\t0\ntrot\tsadness\t0\ntrot\tsurprise\t0\ntrot\ttrust\t0\ntroublesome\tanger\t1\ntroublesome\tanticipation\t0\ntroublesome\tdisgust\t0\ntroublesome\tfear\t1\ntroublesome\tjoy\t0\ntroublesome\tnegative\t1\ntroublesome\tpositive\t0\ntroublesome\tsadness\t0\ntroublesome\tsurprise\t0\ntroublesome\ttrust\t0\ntrough\tanger\t0\ntrough\tanticipation\t0\ntrough\tdisgust\t0\ntrough\tfear\t0\ntrough\tjoy\t0\ntrough\tnegative\t0\ntrough\tpositive\t0\ntrough\tsadness\t0\ntrough\tsurprise\t0\ntrough\ttrust\t0\ntroupe\tanger\t0\ntroupe\tanticipation\t0\ntroupe\tdisgust\t0\ntroupe\tfear\t0\ntroupe\tjoy\t0\ntroupe\tnegative\t0\ntroupe\tpositive\t0\ntroupe\tsadness\t0\ntroupe\tsurprise\t0\ntroupe\ttrust\t0\ntrousers\tanger\t0\ntrousers\tanticipation\t0\ntrousers\tdisgust\t0\ntrousers\tfear\t0\ntrousers\tjoy\t0\ntrousers\tnegative\t0\ntrousers\tpositive\t0\ntrousers\tsadness\t0\ntrousers\tsurprise\t0\ntrousers\ttrust\t0\ntrout\tanger\t0\ntrout\tanticipation\t0\ntrout\tdisgust\t0\ntrout\tfear\t0\ntrout\tjoy\t0\ntrout\tnegative\t0\ntrout\tpositive\t0\ntrout\tsadness\t0\ntrout\tsurprise\t0\ntrout\ttrust\t0\ntrowel\tanger\t0\ntrowel\tanticipation\t0\ntrowel\tdisgust\t0\ntrowel\tfear\t0\ntrowel\tjoy\t0\ntrowel\tnegative\t0\ntrowel\tpositive\t0\ntrowel\tsadness\t0\ntrowel\tsurprise\t0\ntrowel\ttrust\t0\ntruce\tanger\t0\ntruce\tanticipation\t0\ntruce\tdisgust\t0\ntruce\tfear\t0\ntruce\tjoy\t1\ntruce\tnegative\t0\ntruce\tpositive\t1\ntruce\tsadness\t0\ntruce\tsurprise\t0\ntruce\ttrust\t1\ntruck\tanger\t0\ntruck\tanticipation\t0\ntruck\tdisgust\t0\ntruck\tfear\t0\ntruck\tjoy\t0\ntruck\tnegative\t0\ntruck\tpositive\t0\ntruck\tsadness\t0\ntruck\tsurprise\t0\ntruck\ttrust\t1\ntrue\tanger\t0\ntrue\tanticipation\t0\ntrue\tdisgust\t0\ntrue\tfear\t0\ntrue\tjoy\t1\ntrue\tnegative\t0\ntrue\tpositive\t1\ntrue\tsadness\t0\ntrue\tsurprise\t0\ntrue\ttrust\t1\ntruism\tanger\t0\ntruism\tanticipation\t0\ntruism\tdisgust\t0\ntruism\tfear\t0\ntruism\tjoy\t0\ntruism\tnegative\t0\ntruism\tpositive\t0\ntruism\tsadness\t0\ntruism\tsurprise\t0\ntruism\ttrust\t0\ntrump\tanger\t0\ntrump\tanticipation\t0\ntrump\tdisgust\t0\ntrump\tfear\t0\ntrump\tjoy\t0\ntrump\tnegative\t0\ntrump\tpositive\t0\ntrump\tsadness\t0\ntrump\tsurprise\t1\ntrump\ttrust\t0\ntrumpet\tanger\t0\ntrumpet\tanticipation\t0\ntrumpet\tdisgust\t0\ntrumpet\tfear\t0\ntrumpet\tjoy\t0\ntrumpet\tnegative\t1\ntrumpet\tpositive\t0\ntrumpet\tsadness\t0\ntrumpet\tsurprise\t0\ntrumpet\ttrust\t0\ntrumpeter\tanger\t0\ntrumpeter\tanticipation\t0\ntrumpeter\tdisgust\t0\ntrumpeter\tfear\t0\ntrumpeter\tjoy\t0\ntrumpeter\tnegative\t0\ntrumpeter\tpositive\t0\ntrumpeter\tsadness\t0\ntrumpeter\tsurprise\t0\ntrumpeter\ttrust\t0\ntruncate\tanger\t0\ntruncate\tanticipation\t0\ntruncate\tdisgust\t0\ntruncate\tfear\t0\ntruncate\tjoy\t0\ntruncate\tnegative\t0\ntruncate\tpositive\t0\ntruncate\tsadness\t0\ntruncate\tsurprise\t0\ntruncate\ttrust\t0\ntruncated\tanger\t0\ntruncated\tanticipation\t0\ntruncated\tdisgust\t0\ntruncated\tfear\t0\ntruncated\tjoy\t0\ntruncated\tnegative\t0\ntruncated\tpositive\t0\ntruncated\tsadness\t0\ntruncated\tsurprise\t0\ntruncated\ttrust\t0\ntrundle\tanger\t0\ntrundle\tanticipation\t0\ntrundle\tdisgust\t0\ntrundle\tfear\t0\ntrundle\tjoy\t0\ntrundle\tnegative\t0\ntrundle\tpositive\t0\ntrundle\tsadness\t0\ntrundle\tsurprise\t0\ntrundle\ttrust\t0\ntrunk\tanger\t0\ntrunk\tanticipation\t0\ntrunk\tdisgust\t0\ntrunk\tfear\t0\ntrunk\tjoy\t0\ntrunk\tnegative\t0\ntrunk\tpositive\t0\ntrunk\tsadness\t0\ntrunk\tsurprise\t0\ntrunk\ttrust\t0\ntruss\tanger\t0\ntruss\tanticipation\t0\ntruss\tdisgust\t0\ntruss\tfear\t0\ntruss\tjoy\t0\ntruss\tnegative\t0\ntruss\tpositive\t0\ntruss\tsadness\t0\ntruss\tsurprise\t0\ntruss\ttrust\t1\ntrust\tanger\t0\ntrust\tanticipation\t0\ntrust\tdisgust\t0\ntrust\tfear\t0\ntrust\tjoy\t0\ntrust\tnegative\t0\ntrust\tpositive\t0\ntrust\tsadness\t0\ntrust\tsurprise\t0\ntrust\ttrust\t1\ntrustee\tanger\t0\ntrustee\tanticipation\t0\ntrustee\tdisgust\t0\ntrustee\tfear\t0\ntrustee\tjoy\t0\ntrustee\tnegative\t0\ntrustee\tpositive\t0\ntrustee\tsadness\t0\ntrustee\tsurprise\t0\ntrustee\ttrust\t1\ntrusty\tanger\t0\ntrusty\tanticipation\t0\ntrusty\tdisgust\t0\ntrusty\tfear\t0\ntrusty\tjoy\t0\ntrusty\tnegative\t0\ntrusty\tpositive\t1\ntrusty\tsadness\t0\ntrusty\tsurprise\t0\ntrusty\ttrust\t0\ntruth\tanger\t0\ntruth\tanticipation\t0\ntruth\tdisgust\t0\ntruth\tfear\t0\ntruth\tjoy\t0\ntruth\tnegative\t0\ntruth\tpositive\t1\ntruth\tsadness\t0\ntruth\tsurprise\t0\ntruth\ttrust\t1\ntruthful\tanger\t0\ntruthful\tanticipation\t0\ntruthful\tdisgust\t0\ntruthful\tfear\t0\ntruthful\tjoy\t0\ntruthful\tnegative\t0\ntruthful\tpositive\t0\ntruthful\tsadness\t0\ntruthful\tsurprise\t0\ntruthful\ttrust\t1\ntruthfulness\tanger\t0\ntruthfulness\tanticipation\t0\ntruthfulness\tdisgust\t0\ntruthfulness\tfear\t0\ntruthfulness\tjoy\t0\ntruthfulness\tnegative\t0\ntruthfulness\tpositive\t1\ntruthfulness\tsadness\t0\ntruthfulness\tsurprise\t0\ntruthfulness\ttrust\t1\ntryout\tanger\t0\ntryout\tanticipation\t0\ntryout\tdisgust\t0\ntryout\tfear\t0\ntryout\tjoy\t0\ntryout\tnegative\t0\ntryout\tpositive\t0\ntryout\tsadness\t0\ntryout\tsurprise\t0\ntryout\ttrust\t0\ntub\tanger\t0\ntub\tanticipation\t0\ntub\tdisgust\t0\ntub\tfear\t0\ntub\tjoy\t0\ntub\tnegative\t0\ntub\tpositive\t0\ntub\tsadness\t0\ntub\tsurprise\t0\ntub\ttrust\t0\ntube\tanger\t0\ntube\tanticipation\t0\ntube\tdisgust\t0\ntube\tfear\t0\ntube\tjoy\t0\ntube\tnegative\t0\ntube\tpositive\t0\ntube\tsadness\t0\ntube\tsurprise\t0\ntube\ttrust\t0\ntubular\tanger\t0\ntubular\tanticipation\t0\ntubular\tdisgust\t0\ntubular\tfear\t0\ntubular\tjoy\t0\ntubular\tnegative\t0\ntubular\tpositive\t0\ntubular\tsadness\t0\ntubular\tsurprise\t0\ntubular\ttrust\t0\ntubule\tanger\t0\ntubule\tanticipation\t0\ntubule\tdisgust\t0\ntubule\tfear\t0\ntubule\tjoy\t0\ntubule\tnegative\t0\ntubule\tpositive\t0\ntubule\tsadness\t0\ntubule\tsurprise\t0\ntubule\ttrust\t0\ntuck\tanger\t0\ntuck\tanticipation\t0\ntuck\tdisgust\t0\ntuck\tfear\t0\ntuck\tjoy\t0\ntuck\tnegative\t0\ntuck\tpositive\t0\ntuck\tsadness\t0\ntuck\tsurprise\t0\ntuck\ttrust\t0\ntucker\tanger\t0\ntucker\tanticipation\t0\ntucker\tdisgust\t0\ntucker\tfear\t0\ntucker\tjoy\t0\ntucker\tnegative\t0\ntucker\tpositive\t0\ntucker\tsadness\t0\ntucker\tsurprise\t0\ntucker\ttrust\t0\ntufted\tanger\t0\ntufted\tanticipation\t0\ntufted\tdisgust\t0\ntufted\tfear\t0\ntufted\tjoy\t0\ntufted\tnegative\t0\ntufted\tpositive\t0\ntufted\tsadness\t0\ntufted\tsurprise\t0\ntufted\ttrust\t0\ntug\tanger\t0\ntug\tanticipation\t0\ntug\tdisgust\t0\ntug\tfear\t0\ntug\tjoy\t0\ntug\tnegative\t0\ntug\tpositive\t0\ntug\tsadness\t0\ntug\tsurprise\t0\ntug\ttrust\t0\ntuition\tanger\t0\ntuition\tanticipation\t0\ntuition\tdisgust\t0\ntuition\tfear\t0\ntuition\tjoy\t0\ntuition\tnegative\t0\ntuition\tpositive\t0\ntuition\tsadness\t0\ntuition\tsurprise\t0\ntuition\ttrust\t0\ntulip\tanger\t0\ntulip\tanticipation\t0\ntulip\tdisgust\t0\ntulip\tfear\t0\ntulip\tjoy\t0\ntulip\tnegative\t0\ntulip\tpositive\t0\ntulip\tsadness\t0\ntulip\tsurprise\t0\ntulip\ttrust\t0\ntumble\tanger\t0\ntumble\tanticipation\t0\ntumble\tdisgust\t0\ntumble\tfear\t0\ntumble\tjoy\t0\ntumble\tnegative\t1\ntumble\tpositive\t0\ntumble\tsadness\t0\ntumble\tsurprise\t0\ntumble\ttrust\t0\ntumbler\tanger\t0\ntumbler\tanticipation\t0\ntumbler\tdisgust\t0\ntumbler\tfear\t0\ntumbler\tjoy\t0\ntumbler\tnegative\t0\ntumbler\tpositive\t0\ntumbler\tsadness\t0\ntumbler\tsurprise\t0\ntumbler\ttrust\t0\ntumor\tanger\t0\ntumor\tanticipation\t0\ntumor\tdisgust\t0\ntumor\tfear\t1\ntumor\tjoy\t0\ntumor\tnegative\t1\ntumor\tpositive\t0\ntumor\tsadness\t0\ntumor\tsurprise\t0\ntumor\ttrust\t0\ntumour\tanger\t0\ntumour\tanticipation\t0\ntumour\tdisgust\t0\ntumour\tfear\t1\ntumour\tjoy\t0\ntumour\tnegative\t1\ntumour\tpositive\t0\ntumour\tsadness\t1\ntumour\tsurprise\t0\ntumour\ttrust\t0\ntumult\tanger\t1\ntumult\tanticipation\t0\ntumult\tdisgust\t0\ntumult\tfear\t1\ntumult\tjoy\t0\ntumult\tnegative\t1\ntumult\tpositive\t0\ntumult\tsadness\t0\ntumult\tsurprise\t1\ntumult\ttrust\t0\ntumultuous\tanger\t1\ntumultuous\tanticipation\t0\ntumultuous\tdisgust\t0\ntumultuous\tfear\t1\ntumultuous\tjoy\t0\ntumultuous\tnegative\t1\ntumultuous\tpositive\t0\ntumultuous\tsadness\t0\ntumultuous\tsurprise\t0\ntumultuous\ttrust\t0\ntun\tanger\t0\ntun\tanticipation\t0\ntun\tdisgust\t0\ntun\tfear\t0\ntun\tjoy\t0\ntun\tnegative\t0\ntun\tpositive\t0\ntun\tsadness\t0\ntun\tsurprise\t0\ntun\ttrust\t0\ntuna\tanger\t0\ntuna\tanticipation\t0\ntuna\tdisgust\t0\ntuna\tfear\t0\ntuna\tjoy\t0\ntuna\tnegative\t0\ntuna\tpositive\t0\ntuna\tsadness\t0\ntuna\tsurprise\t0\ntuna\ttrust\t0\ntunable\tanger\t0\ntunable\tanticipation\t0\ntunable\tdisgust\t0\ntunable\tfear\t0\ntunable\tjoy\t0\ntunable\tnegative\t0\ntunable\tpositive\t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ged\tfear\t0\nunacknowledged\tjoy\t0\nunacknowledged\tnegative\t0\nunacknowledged\tpositive\t0\nunacknowledged\tsadness\t1\nunacknowledged\tsurprise\t0\nunacknowledged\ttrust\t0\nunadulterated\tanger\t0\nunadulterated\tanticipation\t0\nunadulterated\tdisgust\t0\nunadulterated\tfear\t0\nunadulterated\tjoy\t0\nunadulterated\tnegative\t0\nunadulterated\tpositive\t0\nunadulterated\tsadness\t0\nunadulterated\tsurprise\t0\nunadulterated\ttrust\t0\nunaided\tanger\t0\nunaided\tanticipation\t0\nunaided\tdisgust\t0\nunaided\tfear\t0\nunaided\tjoy\t0\nunaided\tnegative\t0\nunaided\tpositive\t0\nunaided\tsadness\t0\nunaided\tsurprise\t0\nunaided\ttrust\t0\nunaltered\tanger\t0\nunaltered\tanticipation\t0\nunaltered\tdisgust\t0\nunaltered\tfear\t0\nunaltered\tjoy\t0\nunaltered\tnegative\t0\nunaltered\tpositive\t0\nunaltered\tsadness\t0\nunaltered\tsurprise\t0\nunaltered\ttrust\t0\nunambiguous\tanger\t0\nunambiguous\tanticipation\t0\nunambiguous\tdisgust\t0\nunambiguous\tfear\t0\nunambiguous\tjoy\t0\nunambiguous\tnegative\t0\nunambiguous\tpositive\t0\nunambiguous\tsadness\t0\nunambiguous\tsurprise\t0\nunambiguous\ttrust\t0\nunanimity\tanger\t0\nunanimity\tanticipation\t0\nunanimity\tdisgust\t0\nunanimity\tfear\t0\nunanimity\tjoy\t0\nunanimity\tnegative\t0\nunanimity\tpositive\t1\nunanimity\tsadness\t0\nunanimity\tsurprise\t0\nunanimity\ttrust\t0\nunanimous\tanger\t0\nunanimous\tanticipation\t0\nunanimous\tdisgust\t0\nunanimous\tfear\t0\nunanimous\tjoy\t0\nunanimous\tnegative\t0\nunanimous\tpositive\t1\nunanimous\tsadness\t0\nunanimous\tsurprise\t0\nunanimous\ttrust\t0\nunanimously\tanger\t0\nunanimously\tanticipation\t0\nunanimously\tdisgust\t0\nunanimously\tfear\t0\nunanimously\tjoy\t0\nunanimously\tnegative\t0\nunanimously\tpositive\t0\nunanimously\tsadness\t0\nunanimously\tsurprise\t0\nunanimously\ttrust\t0\nunanticipated\tanger\t0\nunanticipated\tanticipation\t0\nunanticipated\tdisgust\t0\nunanticipated\tfear\t0\nunanticipated\tjoy\t0\nunanticipated\tnegative\t0\nunanticipated\tpositive\t0\nunanticipated\tsadness\t0\nunanticipated\tsurprise\t1\nunanticipated\ttrust\t0\nunapproved\tanger\t0\nunapproved\tanticipation\t0\nunapproved\tdisgust\t0\nunapproved\tfear\t0\nunapproved\tjoy\t0\nunapproved\tnegative\t1\nunapproved\tpositive\t0\nunapproved\tsadness\t0\nunapproved\tsurprise\t0\nunapproved\ttrust\t0\nunarmed\tanger\t0\nunarmed\tanticipation\t0\nunarmed\tdisgust\t0\nunarmed\tfear\t0\nunarmed\tjoy\t0\nunarmed\tnegative\t0\nunarmed\tpositive\t0\nunarmed\tsadness\t0\nunarmed\tsurprise\t0\nunarmed\ttrust\t0\nunassisted\tanger\t0\nunassisted\tanticipation\t0\nunassisted\tdisgust\t0\nunassisted\tfear\t0\nunassisted\tjoy\t0\nunassisted\tnegative\t0\nunassisted\tpositive\t0\nunassisted\tsadness\t0\nunassisted\tsurprise\t0\nunassisted\ttrust\t0\nunassuming\tanger\t0\nunassuming\tanticipation\t0\nunassuming\tdisgust\t0\nunassuming\tfear\t0\nunassuming\tjoy\t0\nunassuming\tnegative\t0\nunassuming\tpositive\t1\nunassuming\tsadness\t0\nunassuming\tsurprise\t0\nunassuming\ttrust\t0\nunattached\tanger\t0\nunattached\tanticipation\t0\nunattached\tdisgust\t0\nunattached\tfear\t0\nunattached\tjoy\t0\nunattached\tnegative\t1\nunattached\tpositive\t0\nunattached\tsadness\t0\nunattached\tsurprise\t0\nunattached\ttrust\t0\nunattainable\tanger\t1\nunattainable\tanticipation\t0\nunattainable\tdisgust\t0\nunattainable\tfear\t0\nunattainable\tjoy\t0\nunattainable\tnegative\t1\nunattainable\tpositive\t0\nunattainable\tsadness\t1\nunattainable\tsurprise\t0\nunattainable\ttrust\t0\nunattended\tanger\t0\nunattended\tanticipation\t0\nunattended\tdisgust\t0\nunattended\tfear\t0\nunattended\tjoy\t0\nunattended\tnegative\t0\nunattended\tpositive\t0\nunattended\tsadness\t0\nunattended\tsurprise\t0\nunattended\ttrust\t0\nunattractive\tanger\t0\nunattractive\tanticipation\t0\nunattractive\tdisgust\t1\nunattractive\tfear\t0\nunattractive\tjoy\t0\nunattractive\tnegative\t1\nunattractive\tpositive\t0\nunattractive\tsadness\t1\nunattractive\tsurprise\t0\nunattractive\ttrust\t0\nunauthorized\tanger\t0\nunauthorized\tanticipation\t0\nunauthorized\tdisgust\t0\nunauthorized\tfear\t0\nunauthorized\tjoy\t0\nunauthorized\tnegative\t1\nunauthorized\tpositive\t0\nunauthorized\tsadness\t0\nunauthorized\tsurprise\t0\nunauthorized\ttrust\t0\nunavoidable\tanger\t0\nunavoidable\tanticipation\t0\nunavoidable\tdisgust\t0\nunavoidable\tfear\t0\nunavoidable\tjoy\t0\nunavoidable\tnegative\t1\nunavoidable\tpositive\t0\nunavoidable\tsadness\t0\nunavoidable\tsurprise\t0\nunavoidable\ttrust\t0\nunaware\tanger\t0\nunaware\tanticipation\t0\nunaware\tdisgust\t0\nunaware\tfear\t0\nunaware\tjoy\t0\nunaware\tnegative\t1\nunaware\tpositive\t0\nunaware\tsadness\t0\nunaware\tsurprise\t0\nunaware\ttrust\t0\nunbalanced\tanger\t0\nunbalanced\tanticipation\t0\nunbalanced\tdisgust\t0\nunbalanced\tfear\t0\nunbalanced\tjoy\t0\nunbalanced\tnegative\t0\nunbalanced\tpositive\t0\nunbalanced\tsadness\t0\nunbalanced\tsurprise\t0\nunbalanced\ttrust\t0\nunbearable\tanger\t0\nunbearable\tanticipation\t0\nunbearable\tdisgust\t1\nunbearable\tfear\t0\nunbearable\tjoy\t0\nunbearable\tnegative\t1\nunbearable\tpositive\t0\nunbearable\tsadness\t1\nunbearable\tsurprise\t0\nunbearable\ttrust\t0\nunbeaten\tanger\t0\nunbeaten\tanticipation\t1\nunbeaten\tdisgust\t0\nunbeaten\tfear\t0\nunbeaten\tjoy\t1\nunbeaten\tnegative\t1\nunbeaten\tpositive\t1\nunbeaten\tsadness\t1\nunbeaten\tsurprise\t1\nunbeaten\ttrust\t0\nunbelief\tanger\t0\nunbelief\tanticipation\t0\nunbelief\tdisgust\t0\nunbelief\tfear\t0\nunbelief\tjoy\t0\nunbelief\tnegative\t1\nunbelief\tpositive\t0\nunbelief\tsadness\t0\nunbelief\tsurprise\t0\nunbelief\ttrust\t0\nunbelievable\tanger\t0\nunbelievable\tanticipation\t0\nunbelievable\tdisgust\t0\nunbelievable\tfear\t0\nunbelievable\tjoy\t0\nunbelievable\tnegative\t1\nunbelievable\tpositive\t0\nunbelievable\tsadness\t0\nunbelievable\tsurprise\t0\nunbelievable\ttrust\t0\nunbiased\tanger\t0\nunbiased\tanticipation\t0\nunbiased\tdisgust\t0\nunbiased\tfear\t0\nunbiased\tjoy\t0\nunbiased\tnegative\t0\nunbiased\tpositive\t1\nunbiased\tsadness\t0\nunbiased\tsurprise\t0\nunbiased\ttrust\t0\nunborn\tanger\t0\nunborn\tanticipation\t0\nunborn\tdisgust\t0\nunborn\tfear\t0\nunborn\tjoy\t0\nunborn\tnegative\t1\nunborn\tpositive\t0\nunborn\tsadness\t0\nunborn\tsurprise\t0\nunborn\ttrust\t0\nunbound\tanger\t0\nunbound\tanticipation\t0\nunbound\tdisgust\t0\nunbound\tfear\t0\nunbound\tjoy\t0\nunbound\tnegative\t0\nunbound\tpositive\t0\nunbound\tsadness\t0\nunbound\tsurprise\t0\nunbound\ttrust\t0\nunbounded\tanger\t0\nunbounded\tanticipation\t0\nunbounded\tdisgust\t0\nunbounded\tfear\t0\nunbounded\tjoy\t0\nunbounded\tnegative\t0\nunbounded\tpositive\t0\nunbounded\tsadness\t0\nunbounded\tsurprise\t0\nunbounded\ttrust\t0\nunbreakable\tanger\t0\nunbreakable\tanticipation\t0\nunbreakable\tdisgust\t0\nunbreakable\tfear\t0\nunbreakable\tjoy\t0\nunbreakable\tnegative\t0\nunbreakable\tpositive\t1\nunbreakable\tsadness\t0\nunbreakable\tsurprise\t0\nunbreakable\ttrust\t0\nunbridled\tanger\t1\nunbridled\tanticipation\t1\nunbridled\tdisgust\t0\nunbridled\tfear\t1\nunbridled\tjoy\t0\nunbridled\tnegative\t1\nunbridled\tpositive\t1\nunbridled\tsadness\t0\nunbridled\tsurprise\t1\nunbridled\ttrust\t0\nunbroken\tanger\t0\nunbroken\tanticipation\t0\nunbroken\tdisgust\t0\nunbroken\tfear\t0\nunbroken\tjoy\t0\nunbroken\tnegative\t0\nunbroken\tpositive\t1\nunbroken\tsadness\t0\nunbroken\tsurprise\t0\nunbroken\ttrust\t1\nuncanny\tanger\t0\nuncanny\tanticipation\t0\nuncanny\tdisgust\t0\nuncanny\tfear\t1\nuncanny\tjoy\t0\nuncanny\tnegative\t1\nuncanny\tpositive\t0\nuncanny\tsadness\t0\nuncanny\tsurprise\t1\nuncanny\ttrust\t0\nuncaring\tanger\t1\nuncaring\tanticipation\t0\nuncaring\tdisgust\t1\nuncaring\tfear\t0\nuncaring\tjoy\t0\nuncaring\tnegative\t1\nuncaring\tpositive\t0\nuncaring\tsadness\t1\nuncaring\tsurprise\t0\nuncaring\ttrust\t0\nuncertain\tanger\t1\nuncertain\tanticipation\t0\nuncertain\tdisgust\t1\nuncertain\tfear\t1\nuncertain\tjoy\t0\nuncertain\tnegative\t1\nuncertain\tpositive\t0\nuncertain\tsadness\t0\nuncertain\tsurprise\t1\nuncertain\ttrust\t0\nuncertainty\tanger\t0\nuncertainty\tanticipation\t0\nuncertainty\tdisgust\t0\nuncertainty\tfear\t0\nuncertainty\tjoy\t0\nuncertainty\tnegative\t0\nuncertainty\tpositive\t0\nuncertainty\tsadness\t0\nuncertainty\tsurprise\t0\nuncertainty\ttrust\t0\nunchallenged\tanger\t0\nunchallenged\tanticipation\t0\nunchallenged\tdisgust\t0\nunchallenged\tfear\t0\nunchallenged\tjoy\t0\nunchallenged\tnegative\t0\nunchallenged\tpositive\t0\nunchallenged\tsadness\t0\nunchallenged\tsurprise\t0\nunchallenged\ttrust\t0\nunchangeable\tanger\t0\nunchangeable\tanticipation\t0\nunchangeable\tdisgust\t0\nunchangeable\tfear\t0\nunchangeable\tjoy\t0\nunchangeable\tnegative\t1\nunchangeable\tpositive\t0\nunchangeable\tsadness\t0\nunchangeable\tsurprise\t0\nunchangeable\ttrust\t0\nunchanged\tanger\t0\nunchanged\tanticipation\t0\nunchanged\tdisgust\t0\nunchanged\tfear\t0\nunchanged\tjoy\t0\nunchanged\tnegative\t0\nunchanged\tpositive\t0\nunchanged\tsadness\t0\nunchanged\tsurprise\t0\nunchanged\ttrust\t0\nunclaimed\tanger\t0\nunclaimed\tanticipation\t0\nunclaimed\tdisgust\t0\nunclaimed\tfear\t0\nunclaimed\tjoy\t0\nunclaimed\tnegative\t0\nunclaimed\tpositive\t0\nunclaimed\tsadness\t0\nunclaimed\tsurprise\t0\nunclaimed\ttrust\t0\nuncle\tanger\t0\nuncle\tanticipation\t0\nuncle\tdisgust\t0\nuncle\tfear\t0\nuncle\tjoy\t0\nuncle\tnegative\t0\nuncle\tpositive\t0\nuncle\tsadness\t0\nuncle\tsurprise\t0\nuncle\ttrust\t0\nunclean\tanger\t0\nunclean\tanticipation\t0\nunclean\tdisgust\t1\nunclean\tfear\t0\nunclean\tjoy\t0\nunclean\tnegative\t1\nunclean\tpositive\t0\nunclean\tsadness\t0\nunclean\tsurprise\t0\nunclean\ttrust\t0\nuncomfortable\tanger\t0\nuncomfortable\tanticipation\t0\nuncomfortable\tdisgust\t0\nuncomfortable\tfear\t0\nuncomfortable\tjoy\t0\nuncomfortable\tnegative\t1\nuncomfortable\tpositive\t0\nuncomfortable\tsadness\t0\nuncomfortable\tsurprise\t0\nuncomfortable\ttrust\t0\nuncommon\tanger\t0\nuncommon\tanticipation\t0\nuncommon\tdisgust\t0\nuncommon\tfear\t0\nuncommon\tjoy\t0\nuncommon\tnegative\t0\nuncommon\tpositive\t0\nuncommon\tsadness\t0\nuncommon\tsurprise\t0\nuncommon\ttrust\t0\nuncommonly\tanger\t0\nuncommonly\tanticipation\t0\nuncommonly\tdisgust\t0\nuncommonly\tfear\t0\nuncommonly\tjoy\t0\nuncommonly\tnegative\t0\nuncommonly\tpositive\t0\nuncommonly\tsadness\t0\nuncommonly\tsurprise\t0\nuncommonly\ttrust\t0\nuncompromising\tanger\t0\nuncompromising\tanticipation\t0\nuncompromising\tdisgust\t0\nuncompromising\tfear\t0\nuncompromising\tjoy\t0\nuncompromising\tnegative\t0\nuncompromising\tpositive\t0\nuncompromising\tsadness\t0\nuncompromising\tsurprise\t0\nuncompromising\ttrust\t0\nunconcerned\tanger\t0\nunconcerned\tanticipation\t0\nunconcerned\tdisgust\t0\nunconcerned\tfear\t0\nunconcerned\tjoy\t0\nunconcerned\tnegative\t0\nunconcerned\tpositive\t0\nunconcerned\tsadness\t0\nunconcerned\tsurprise\t0\nunconcerned\ttrust\t0\nunconfirmed\tanger\t0\nunconfirmed\tanticipation\t0\nunconfirmed\tdisgust\t0\nunconfirmed\tfear\t0\nunconfirmed\tjoy\t0\nunconfirmed\tnegative\t0\nunconfirmed\tpositive\t0\nunconfirmed\tsadness\t0\nunconfirmed\tsurprise\t0\nunconfirmed\ttrust\t0\nunconnected\tanger\t0\nunconnected\tanticipation\t0\nunconnected\tdisgust\t0\nunconnected\tfear\t0\nunconnected\tjoy\t0\nunconnected\tnegative\t0\nunconnected\tpositive\t0\nunconnected\tsadness\t0\nunconnected\tsurprise\t0\nunconnected\ttrust\t0\nunconscionable\tanger\t0\nunconscionable\tanticipation\t0\nunconscionable\tdisgust\t1\nunconscionable\tfear\t0\nunconscionable\tjoy\t0\nunconscionable\tnegative\t1\nunconscionable\tpositive\t0\nunconscionable\tsadness\t0\nunconscionable\tsurprise\t0\nunconscionable\ttrust\t0\nunconscious\tanger\t0\nunconscious\tanticipation\t0\nunconscious\tdisgust\t0\nunconscious\tfear\t0\nunconscious\tjoy\t0\nunconscious\tnegative\t1\nunconscious\tpositive\t0\nunconscious\tsadness\t0\nunconscious\tsurprise\t0\nunconscious\ttrust\t0\nunconsciousness\tanger\t0\nunconsciousness\tanticipation\t0\nunconsciousness\tdisgust\t0\nunconsciousness\tfear\t0\nunconsciousness\tjoy\t0\nunconsciousness\tnegative\t0\nunconsciousness\tpositive\t0\nunconsciousness\tsadness\t0\nunconsciousness\tsurprise\t0\nunconsciousness\ttrust\t0\nunconstitutional\tanger\t0\nunconstitutional\tanticipation\t0\nunconstitutional\tdisgust\t0\nunconstitutional\tfear\t0\nunconstitutional\tjoy\t0\nunconstitutional\tnegative\t1\nunconstitutional\tpositive\t0\nunconstitutional\tsadness\t0\nunconstitutional\tsurprise\t0\nunconstitutional\ttrust\t0\nunconstrained\tanger\t0\nunconstrained\tanticipation\t0\nunconstrained\tdisgust\t0\nunconstrained\tfear\t0\nunconstrained\tjoy\t1\nunconstrained\tnegative\t0\nunconstrained\tpositive\t1\nunconstrained\tsadness\t0\nunconstrained\tsurprise\t0\nunconstrained\ttrust\t0\nuncontested\tanger\t0\nuncontested\tanticipation\t0\nuncontested\tdisgust\t0\nuncontested\tfear\t0\nuncontested\tjoy\t0\nuncontested\tnegative\t0\nuncontested\tpositive\t0\nuncontested\tsadness\t0\nuncontested\tsurprise\t0\nuncontested\ttrust\t0\nuncontrollable\tanger\t1\nuncontrollable\tanticipation\t1\nuncontrollable\tdisgust\t0\nuncontrollable\tfear\t0\nuncontrollable\tjoy\t0\nuncontrollable\tnegative\t1\nuncontrollable\tpositive\t0\nuncontrollable\tsadness\t0\nuncontrollable\tsurprise\t1\nuncontrollable\ttrust\t0\nuncontrolled\tanger\t0\nuncontrolled\tanticipation\t0\nuncontrolled\tdisgust\t0\nuncontrolled\tfear\t0\nuncontrolled\tjoy\t0\nuncontrolled\tnegative\t1\nuncontrolled\tpositive\t0\nuncontrolled\tsadness\t0\nuncontrolled\tsurprise\t0\nuncontrolled\ttrust\t0\nunconventional\tanger\t0\nunconventional\tanticipation\t0\nunconventional\tdisgust\t0\nunconventional\tfear\t0\nunconventional\tjoy\t0\nunconventional\tnegative\t0\nunconventional\tpositive\t0\nunconventional\tsadness\t0\nunconventional\tsurprise\t0\nunconventional\ttrust\t0\nunconvinced\tanger\t0\nunconvinced\tanticipation\t0\nunconvinced\tdisgust\t0\nunconvinced\tfear\t0\nunconvinced\tjoy\t0\nunconvinced\tnegative\t0\nunconvinced\tpositive\t0\nunconvinced\tsadness\t0\nunconvinced\tsurprise\t0\nunconvinced\ttrust\t0\nuncooked\tanger\t0\nuncooked\tanticipation\t0\nuncooked\tdisgust\t0\nuncooked\tfear\t0\nuncooked\tjoy\t0\nuncooked\tnegative\t0\nuncooked\tpositive\t0\nuncooked\tsadness\t0\nuncooked\tsurprise\t0\nuncooked\ttrust\t0\nuncorrelated\tanger\t0\nuncorrelated\tanticipation\t0\nuncorrelated\tdisgust\t0\nuncorrelated\tfear\t0\nuncorrelated\tjoy\t0\nuncorrelated\tnegative\t0\nuncorrelated\tpositive\t0\nuncorrelated\tsadness\t0\nuncorrelated\tsurprise\t0\nuncorrelated\ttrust\t0\nuncover\tanger\t0\nuncover\tanticipation\t0\nuncover\tdisgust\t0\nuncover\tfear\t0\nuncover\tjoy\t0\nuncover\tnegative\t0\nuncover\tpositive\t0\nuncover\tsadness\t0\nuncover\tsurprise\t1\nuncover\ttrust\t0\nuncritical\tanger\t0\nuncritical\tanticipation\t0\nuncritical\tdisgust\t0\nuncritical\tfear\t0\nuncritical\tjoy\t0\nuncritical\tnegative\t0\nuncritical\tpositive\t0\nuncritical\tsadness\t0\nuncritical\tsurprise\t0\nuncritica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isgust\t0\nunicorn\tfear\t0\nunicorn\tjoy\t0\nunicorn\tnegative\t0\nunicorn\tpositive\t0\nunicorn\tsadness\t0\nunicorn\tsurprise\t0\nunicorn\ttrust\t0\nunification\tanger\t0\nunification\tanticipation\t1\nunification\tdisgust\t0\nunification\tfear\t0\nunification\tjoy\t1\nunification\tnegative\t0\nunification\tpositive\t1\nunification\tsadness\t0\nunification\tsurprise\t0\nunification\ttrust\t1\nuniform\tanger\t0\nuniform\tanticipation\t0\nuniform\tdisgust\t0\nuniform\tfear\t0\nuniform\tjoy\t0\nuniform\tnegative\t0\nuniform\tpositive\t0\nuniform\tsadness\t0\nuniform\tsurprise\t0\nuniform\ttrust\t0\nuniformity\tanger\t0\nuniformity\tanticipation\t0\nuniformity\tdisgust\t0\nuniformity\tfear\t0\nuniformity\tjoy\t0\nuniformity\tnegative\t0\nuniformity\tpositive\t0\nuniformity\tsadness\t0\nuniformity\tsurprise\t0\nuniformity\ttrust\t0\nuniformly\tanger\t0\nuniformly\tanticipation\t0\nuniformly\tdisgust\t0\nuniformly\tfear\t0\nuniformly\tjoy\t0\nuniformly\tnegative\t0\nuniformly\tpositive\t1\nuniformly\tsadness\t0\nuniformly\tsurprise\t0\nuniformly\ttrust\t0\nunimaginable\tanger\t0\nunimaginable\tanticipation\t0\nunimaginable\tdisgust\t0\nunimaginable\tfear\t0\nunimaginable\tjoy\t0\nunimaginable\tnegative\t1\nunimaginable\tpositive\t1\nunimaginable\tsadness\t0\nunimaginable\tsurprise\t1\nunimaginable\ttrust\t0\nunimportant\tanger\t0\nunimportant\tanticipation\t0\nunimportant\tdisgust\t0\nunimportant\tfear\t0\nunimportant\tjoy\t0\nunimportant\tnegative\t1\nunimportant\tpositive\t0\nunimportant\tsadness\t1\nunimportant\tsurprise\t0\nunimportant\ttrust\t0\nunimpressed\tanger\t0\nunimpressed\tanticipation\t0\nunimpressed\tdisgust\t0\nunimpressed\tfear\t0\nunimpressed\tjoy\t0\nunimpressed\tnegative\t1\nunimpressed\tpositive\t0\nunimpressed\tsadness\t0\nunimpressed\tsurprise\t0\nunimpressed\ttrust\t0\nunimproved\tanger\t0\nunimproved\tanticipation\t0\nunimproved\tdisgust\t0\nunimproved\tfear\t0\nunimproved\tjoy\t0\nunimproved\tnegative\t1\nunimproved\tpositive\t0\nunimproved\tsadness\t0\nunimproved\tsurprise\t0\nunimproved\ttrust\t0\nuninfected\tanger\t0\nuninfected\tanticipation\t0\nuninfected\tdisgust\t0\nuninfected\tfear\t0\nuninfected\tjoy\t0\nuninfected\tnegative\t0\nuninfected\tpositive\t1\nuninfected\tsadness\t0\nuninfected\tsurprise\t0\nuninfected\ttrust\t0\nuninformed\tanger\t0\nuninformed\tanticipation\t0\nuninformed\tdisgust\t0\nuninformed\tfear\t0\nuninformed\tjoy\t0\nuninformed\tnegative\t1\nuninformed\tpositive\t0\nuninformed\tsadness\t0\nuninformed\tsurprise\t0\nuninformed\ttrust\t0\nuninhabited\tanger\t0\nuninhabited\tanticipation\t0\nuninhabited\tdisgust\t0\nuninhabited\tfear\t0\nuninhabited\tjoy\t0\nuninhabited\tnegative\t0\nuninhabited\tpositive\t0\nuninhabited\tsadness\t0\nuninhabited\tsurprise\t0\nuninhabited\ttrust\t0\nuninitiated\tanger\t0\nuninitiated\tanticipation\t0\nuninitiated\tdisgust\t0\nuninitiated\tfear\t0\nuninitiated\tjoy\t0\nuninitiated\tnegative\t1\nuninitiated\tpositive\t0\nuninitiated\tsadness\t0\nuninitiated\tsurprise\t0\nuninitiated\ttrust\t0\nuninspired\tanger\t0\nuninspired\tanticipation\t0\nuninspired\tdisgust\t0\nuninspired\tfear\t0\nuninspired\tjoy\t0\nuninspired\tnegative\t1\nuninspired\tpositive\t0\nuninspired\tsadness\t1\nuninspired\tsurprise\t0\nuninspired\ttrust\t0\nunintelligible\tanger\t0\nunintelligible\tanticipation\t0\nunintelligible\tdisgust\t0\nunintelligible\tfear\t0\nunintelligible\tjoy\t0\nunintelligible\tnegative\t1\nunintelligible\tpositive\t0\nunintelligible\tsadness\t0\nunintelligible\tsurprise\t0\nunintelligible\ttrust\t0\nunintended\tanger\t0\nunintended\tanticipation\t0\nunintended\tdisgust\t0\nunintended\tfear\t0\nunintended\tjoy\t0\nunintended\tnegative\t0\nunintended\tpositive\t0\nunintended\tsadness\t0\nunintended\tsurprise\t1\nunintended\ttrust\t0\nunintentional\tanger\t0\nunintentional\tanticipation\t0\nunintentional\tdisgust\t0\nunintentional\tfear\t0\nunintentional\tjoy\t0\nunintentional\tnegative\t0\nunintentional\tpositive\t0\nunintentional\tsadness\t0\nunintentional\tsurprise\t1\nunintentional\ttrust\t0\nunintentionally\tanger\t0\nunintentionally\tanticipation\t0\nunintentionally\tdisgust\t0\nunintentionally\tfear\t0\nunintentionally\tjoy\t0\nunintentionally\tnegative\t1\nunintentionally\tpositive\t0\nunintentionally\tsadness\t0\nunintentionally\tsurprise\t1\nunintentionally\ttrust\t0\nuninterested\tanger\t0\nuninterested\tanticipation\t0\nuninterested\tdisgust\t0\nuninterested\tfear\t0\nuninterested\tjoy\t0\nuninterested\tnegative\t1\nuninterested\tpositive\t0\nuninterested\tsadness\t1\nuninterested\tsurprise\t0\nuninterested\ttrust\t0\nuninteresting\tanger\t0\nuninteresting\tanticipation\t0\nuninteresting\tdisgust\t0\nuninteresting\tfear\t0\nuninteresting\tjoy\t0\nuninteresting\tnegative\t1\nuninteresting\tpositive\t0\nuninteresting\tsadness\t1\nuninteresting\tsurprise\t0\nuninteresting\ttrust\t0\nuninterrupted\tanger\t0\nuninterrupted\tanticipation\t0\nuninterrupted\tdisgust\t0\nuninterrupted\tfear\t0\nuninterrupted\tjoy\t0\nuninterrupted\tnegative\t0\nuninterrupted\tpositive\t0\nuninterrupted\tsadness\t0\nuninterrupted\tsurprise\t0\nuninterrupted\ttrust\t0\nuninvited\tanger\t0\nuninvited\tanticipation\t0\nuninvited\tdisgust\t0\nuninvited\tfear\t0\nuninvited\tjoy\t0\nuninvited\tnegative\t0\nuninvited\tpositive\t0\nuninvited\tsadness\t1\nuninvited\tsurprise\t0\nuninvited\ttrust\t0\nunion\tanger\t0\nunion\tanticipation\t0\nunion\tdisgust\t0\nunion\tfear\t0\nunion\tjoy\t0\nunion\tnegative\t0\nunion\tpositive\t0\nunion\tsadness\t0\nunion\tsurprise\t0\nunion\ttrust\t0\nunique\tanger\t0\nunique\tanticipation\t0\nunique\tdisgust\t0\nunique\tfear\t0\nunique\tjoy\t0\nunique\tnegative\t0\nunique\tpositive\t1\nunique\tsadness\t0\nunique\tsurprise\t1\nunique\ttrust\t0\nunison\tanger\t0\nunison\tanticipation\t0\nunison\tdisgust\t0\nunison\tfear\t0\nunison\tjoy\t0\nunison\tnegative\t0\nunison\tpositive\t1\nunison\tsadness\t0\nunison\tsurprise\t0\nunison\ttrust\t0\nunit\tanger\t0\nunit\tanticipation\t0\nunit\tdisgust\t0\nunit\tfear\t0\nunit\tjoy\t0\nunit\tnegative\t0\nunit\tpositive\t0\nunit\tsadness\t0\nunit\tsurprise\t0\nunit\ttrust\t0\nunitary\tanger\t0\nunitary\tanticipation\t0\nunitary\tdisgust\t0\nunitary\tfear\t0\nunitary\tjoy\t0\nunitary\tnegative\t0\nunitary\tpositive\t1\nunitary\tsadness\t0\nunitary\tsurprise\t0\nunitary\ttrust\t0\nunite\tanger\t0\nunite\tanticipation\t0\nunite\tdisgust\t0\nunite\tfear\t0\nunite\tjoy\t0\nunite\tnegative\t0\nunite\tpositive\t0\nunite\tsadness\t0\nunite\tsurprise\t0\nunite\ttrust\t0\nunited\tanger\t0\nunited\tanticipation\t0\nunited\tdisgust\t0\nunited\tfear\t0\nunited\tjoy\t0\nunited\tnegative\t0\nunited\tpositive\t1\nunited\tsadness\t0\nunited\tsurprise\t0\nunited\ttrust\t1\nunity\tanger\t0\nunity\tanticipation\t0\nunity\tdisgust\t0\nunity\tfear\t0\nunity\tjoy\t0\nunity\tnegative\t0\nunity\tpositive\t1\nunity\tsadness\t0\nunity\tsurprise\t0\nunity\ttrust\t1\nuniversal\tanger\t0\nuniversal\tanticipation\t0\nuniversal\tdisgust\t0\nuniversal\tfear\t0\nuniversal\tjoy\t0\nuniversal\tnegative\t0\nuniversal\tpositive\t0\nuniversal\tsadness\t0\nuniversal\tsurprise\t0\nuniversal\ttrust\t0\nuniversality\tanger\t0\nuniversality\tanticipation\t0\nuniversality\tdisgust\t0\nuniversality\tfear\t0\nuniversality\tjoy\t0\nuniversality\tnegative\t0\nuniversality\tpositive\t0\nuniversality\tsadness\t0\nuniversality\tsurprise\t0\nuniversality\ttrust\t0\nuniverse\tanger\t0\nuniverse\tanticipation\t0\nuniverse\tdisgust\t0\nuniverse\tfear\t0\nuniverse\tjoy\t0\nuniverse\tnegative\t0\nuniverse\tpositive\t0\nuniverse\tsadness\t0\nuniverse\tsurprise\t0\nuniverse\ttrust\t0\nuniversity\tanger\t0\nuniversity\tanticipation\t1\nuniversity\tdisgust\t0\nuniversity\tfear\t0\nuniversity\tjoy\t0\nuniversity\tnegative\t0\nuniversity\tpositive\t1\nuniversity\tsadness\t0\nuniversity\tsurprise\t0\nuniversity\ttrust\t0\nunjust\tanger\t1\nunjust\tanticipation\t0\nunjust\tdisgust\t0\nunjust\tfear\t0\nunjust\tjoy\t0\nunjust\tnegative\t1\nunjust\tpositive\t0\nunjust\tsadness\t0\nunjust\tsurprise\t0\nunjust\ttrust\t0\nunjustifiable\tanger\t1\nunjustifiable\tanticipation\t0\nunjustifiable\tdisgust\t1\nunjustifiable\tfear\t1\nunjustifiable\tjoy\t0\nunjustifiable\tnegative\t1\nunjustifiable\tpositive\t0\nunjustifiable\tsadness\t0\nunjustifiable\tsurprise\t0\nunjustifiable\ttrust\t0\nunjustified\tanger\t0\nunjustified\tanticipation\t0\nunjustified\tdisgust\t0\nunjustified\tfear\t0\nunjustified\tjoy\t0\nunjustified\tnegative\t1\nunjustified\tpositive\t0\nunjustified\tsadness\t0\nunjustified\tsurprise\t0\nunjustified\ttrust\t0\nunkind\tanger\t1\nunkind\tanticipation\t0\nunkind\tdisgust\t1\nunkind\tfear\t1\nunkind\tjoy\t0\nunkind\tnegative\t1\nunkind\tpositive\t0\nunkind\tsadness\t1\nunkind\tsurprise\t0\nunkind\ttrust\t0\nunknowable\tanger\t0\nunknowable\tanticipation\t0\nunknowable\tdisgust\t0\nunknowable\tfear\t0\nunknowable\tjoy\t0\nunknowable\tnegative\t0\nunknowable\tpositive\t0\nunknowable\tsadness\t0\nunknowable\tsurprise\t0\nunknowable\ttrust\t0\nunknown\tanger\t0\nunknown\tanticipation\t1\nunknown\tdisgust\t0\nunknown\tfear\t1\nunknown\tjoy\t0\nunknown\tnegative\t1\nunknown\tpositive\t0\nunknown\tsadness\t0\nunknown\tsurprise\t0\nunknown\ttrust\t0\nunlawful\tanger\t1\nunlawful\tanticipation\t0\nunlawful\tdisgust\t1\nunlawful\tfear\t1\nunlawful\tjoy\t0\nunlawful\tnegative\t1\nunlawful\tpositive\t0\nunlawful\tsadness\t1\nunlawful\tsurprise\t0\nunlawful\ttrust\t0\nunleash\tanger\t0\nunleash\tanticipation\t0\nunleash\tdisgust\t0\nunleash\tfear\t0\nunleash\tjoy\t0\nunleash\tnegative\t0\nunleash\tpositive\t0\nunleash\tsadness\t0\nunleash\tsurprise\t0\nunleash\ttrust\t0\nunlicensed\tanger\t0\nunlicensed\tanticipation\t0\nunlicensed\tdisgust\t0\nunlicensed\tfear\t0\nunlicensed\tjoy\t0\nunlicensed\tnegative\t1\nunlicensed\tpositive\t0\nunlicensed\tsadness\t0\nunlicensed\tsurprise\t0\nunlicensed\ttrust\t0\nunlike\tanger\t0\nunlike\tanticipation\t0\nunlike\tdisgust\t0\nunlike\tfear\t0\nunlike\tjoy\t0\nunlike\tnegative\t0\nunlike\tpositive\t0\nunlike\tsadness\t0\nunlike\tsurprise\t0\nunlike\ttrust\t0\nunlimited\tanger\t0\nunlimited\tanticipation\t0\nunlimited\tdisgust\t0\nunlimited\tfear\t0\nunlimited\tjoy\t0\nunlimited\tnegative\t0\nunlimited\tpositive\t1\nunlimited\tsadness\t0\nunlimited\tsurprise\t0\nunlimited\ttrust\t0\nunload\tanger\t0\nunload\tanticipation\t0\nunload\tdisgust\t0\nunload\tfear\t0\nunload\tjoy\t0\nunload\tnegative\t0\nunload\tpositive\t0\nunload\tsadness\t0\nunload\tsurprise\t0\nunload\ttrust\t0\nunloaded\tanger\t0\nunloaded\tanticipation\t0\nunloaded\tdisgust\t0\nunloaded\tfear\t0\nunloaded\tjoy\t0\nunloaded\tnegative\t0\nunloaded\tpositive\t0\nunloaded\tsadness\t0\nunloaded\tsurprise\t0\nunloaded\ttrust\t0\nunlock\tanger\t0\nunlock\tanticipation\t0\nunlock\tdisgust\t0\nunlock\tfear\t0\nunlock\tjoy\t0\nunlock\tnegative\t0\nunlock\tpositive\t0\nunlock\tsadness\t0\nunlock\tsurprise\t0\nunlock\ttrust\t0\nunlucky\tanger\t1\nunlucky\tanticipation\t0\nunlucky\tdisgust\t1\nunlucky\tfear\t1\nunlucky\tjoy\t0\nunlucky\tnegative\t1\nunlucky\tpositive\t0\nunlucky\tsadness\t1\nunlucky\tsurprise\t0\nunlucky\ttrust\t0\nunmanageable\tanger\t0\nunmanageable\tanticipation\t0\nunmanageable\tdisgust\t1\nunmanageable\tfear\t0\nunmanageable\tjoy\t0\nunmanageable\tnegative\t1\nunmanageable\tpositive\t0\nunmanageable\tsadness\t0\nunmanageable\tsurprise\t0\nunmanageable\ttrust\t0\nunmarked\tanger\t0\nunmarked\tanticipation\t0\nunmarked\tdisgust\t0\nunmarked\tfear\t0\nunmarked\tjoy\t0\nunmarked\tnegative\t0\nunmarked\tpositive\t0\nunmarked\tsadness\t0\nunmarked\tsurprise\t0\nunmarked\ttrust\t0\nunmarried\tanger\t0\nunmarried\tanticipation\t0\nunmarried\tdisgust\t0\nunmarried\tfear\t0\nunmarried\tjoy\t0\nunmarried\tnegative\t0\nunmarried\tpositive\t0\nunmarried\tsadness\t0\nunmarried\tsurprise\t0\nunmarried\ttrust\t0\nunmask\tanger\t0\nunmask\tanticipation\t0\nunmask\tdisgust\t0\nunmask\tfear\t0\nunmask\tjoy\t0\nunmask\tnegative\t0\nunmask\tpositive\t0\nunmask\tsadness\t0\nunmask\tsurprise\t0\nunmask\ttrust\t0\nunmatched\tanger\t0\nunmatched\tanticipation\t0\nunmatched\tdisgust\t0\nunmatched\tfear\t0\nunmatched\tjoy\t0\nunmatched\tnegative\t0\nunmatched\tpositive\t0\nunmatched\tsadness\t0\nunmatched\tsurprise\t0\nunmatched\ttrust\t0\nunmistakable\tanger\t0\nunmistakable\tanticipation\t0\nunmistakable\tdisgust\t0\nunmistakable\tfear\t0\nunmistakable\tjoy\t0\nunmistakable\tnegative\t0\nunmistakable\tpositive\t0\nunmistakable\tsadness\t0\nunmistakable\tsurprise\t0\nunmistakable\ttrust\t0\nunmitigated\tanger\t0\nunmitigated\tanticipation\t0\nunmitigated\tdisgust\t0\nunmitigated\tfear\t0\nunmitigated\tjoy\t0\nunmitigated\tnegative\t0\nunmitigated\tpositive\t0\nunmitigated\tsadness\t0\nunmitigated\tsurprise\t0\nunmitigated\ttrust\t0\nunmoved\tanger\t0\nunmoved\tanticipation\t0\nunmoved\tdisgust\t0\nunmoved\tfear\t0\nunmoved\tjoy\t0\nunmoved\tnegative\t0\nunmoved\tpositive\t0\nunmoved\tsadness\t0\nunmoved\tsurprise\t0\nunmoved\ttrust\t0\nunnamed\tanger\t0\nunnamed\tanticipation\t0\nunnamed\tdisgust\t0\nunnamed\tfear\t0\nunnamed\tjoy\t0\nunnamed\tnegative\t0\nunnamed\tpositive\t0\nunnamed\tsadness\t0\nunnamed\tsurprise\t0\nunnamed\ttrust\t0\nunnatural\tanger\t0\nunnatural\tanticipation\t0\nunnatural\tdisgust\t1\nunnatural\tfear\t1\nunnatural\tjoy\t0\nunnatural\tnegative\t1\nunnatural\tpositive\t0\nunnatural\tsadness\t0\nunnatural\tsurprise\t0\nunnatural\ttrust\t0\nunnecessary\tanger\t0\nunnecessary\tanticipation\t0\nunnecessary\tdisgust\t0\nunnecessary\tfear\t0\nunnecessary\tjoy\t0\nunnecessary\tnegative\t0\nunnecessary\tpositive\t0\nunnecessary\tsadness\t0\nunnecessary\tsurprise\t0\nunnecessary\ttrust\t0\nunneeded\tanger\t0\nunneeded\tanticipation\t0\nunneeded\tdisgust\t0\nunneeded\tfear\t0\nunneeded\tjoy\t0\nunneeded\tnegative\t0\nunneeded\tpositive\t0\nunneeded\tsadness\t0\nunneeded\tsurprise\t0\nunneeded\ttrust\t0\nunnoticed\tanger\t0\nunnoticed\tanticipation\t0\nunnoticed\tdisgust\t0\nunnoticed\tfear\t0\nunnoticed\tjoy\t0\nunnoticed\tnegative\t0\nunnoticed\tpositive\t0\nunnoticed\tsadness\t0\nunnoticed\tsurprise\t0\nunnoticed\ttrust\t0\nunnumbered\tanger\t0\nunnumbered\tanticipation\t0\nunnumbered\tdisgust\t0\nunnumbered\tfear\t0\nunnumbered\tjoy\t0\nunnumbered\tnegative\t0\nunnumbered\tpositive\t0\nunnumbered\tsadness\t0\nunnumbered\tsurprise\t0\nunnumbered\ttrust\t0\nunobserved\tanger\t0\nunobserved\tanticipation\t0\nunobserved\tdisgust\t0\nunobserved\tfear\t0\nunobserved\tjoy\t0\nunobserved\tnegative\t0\nunobserved\tpositive\t0\nunobserved\tsadness\t0\nunobserved\tsurprise\t0\nunobserved\ttrust\t0\nunobstructed\tanger\t0\nunobstructed\tanticipation\t0\nunobstructed\tdisgust\t0\nunobstructed\tfear\t0\nunobstructed\tjoy\t0\nunobstructed\tnegative\t0\nunobstructed\tpositive\t0\nunobstructed\tsadness\t0\nunobstructed\tsurprise\t0\nunobstructed\ttrust\t0\nunobtrusive\tanger\t0\nunobtrusive\tanticipation\t0\nunobtrusive\tdisgust\t0\nunobtrusive\tfear\t0\nunobtrusive\tjoy\t0\nunobtrusive\tnegative\t0\nunobtrusive\tpositive\t0\nunobtrusive\tsadness\t0\nunobtrusive\tsurprise\t0\nunobtrusive\ttrust\t0\nunoccupied\tanger\t0\nunoccupied\tanticipation\t0\nunoccupied\tdisgust\t0\nunoccupied\tfear\t0\nunoccupied\tjoy\t0\nunoccupied\tnegative\t0\nunoccupied\tpositive\t0\nunoccupied\tsadness\t0\nunoccupied\tsurprise\t0\nunoccupied\ttrust\t0\nunofficial\tanger\t0\nunofficial\tanticipation\t0\nunofficial\tdisgust\t0\nunofficial\tfear\t0\nunofficial\tjoy\t0\nunofficial\tnegative\t1\nunofficial\tpositive\t0\nunofficial\tsadness\t0\nunofficial\tsurprise\t0\nunofficial\ttrust\t0\nunopened\tanger\t0\nunopened\tanticipation\t0\nunopened\tdisgust\t0\nunopened\tfear\t0\nunopened\tjoy\t0\nunopened\tnegative\t0\nunopened\tpositive\t0\nunopened\tsadness\t0\nunopened\tsurprise\t0\nunopened\ttrust\t0\nunopposed\tanger\t0\nunopposed\tanticipation\t0\nunopposed\tdisgust\t0\nunopposed\tfear\t0\nunopposed\tjoy\t0\nunopposed\tnegative\t0\nunopposed\tpositive\t0\nunopposed\tsadness\t0\nunopposed\tsurprise\t0\nunopposed\ttrust\t0\nunordered\tanger\t0\nunordered\tanticipation\t0\nunordered\tdisgust\t0\nunordered\tfear\t0\nunordered\tjoy\t0\nunordered\tnegative\t0\nunordered\tpositive\t0\nunordered\tsadness\t0\nunordered\tsurprise\t0\nunordered\ttrust\t0\nunorganized\tanger\t0\nunorganized\tanticipation\t0\nunorganized\tdisgust\t0\nunorganized\tfear\t0\nunorganized\tjoy\t0\nunorganized\tnegative\t0\nunorganized\tpositive\t0\nunorganized\tsadness\t0\nunorganized\tsurprise\t0\nunorganized\ttrust\t0\nunorthodox\tanger\t0\nunorthodox\tanticipation\t0\nunorthodox\tdisgust\t0\nunorthodox\tfear\t0\nunorthodox\tjoy\t0\nunorthodox\tnegative\t0\nunorthodox\tpositive\t0\nunorthodox\tsadness\t0\nunorthodox\tsurprise\t0\nunorthodox\ttrust\t0\nunpack\tanger\t0\nunpack\tanticipation\t0\nunpack\tdisgust\t0\nunpack\tfear\t0\nunpack\tjoy\t0\nunpack\tnegative\t0\nunpack\tpositive\t0\nunpack\tsadness\t0\nunpack\tsurprise\t0\nunpack\ttrust\t0\nunpaid\tanger\t1\nunpaid\tanticipation\t0\nunpaid\tdisgust\t0\nunpaid\tfear\t0\nunpaid\tjoy\t0\nunpaid\tnegative\t1\nunpaid\tpositive\t0\nunpaid\tsadness\t1\nunpaid\tsurprise\t0\nunpaid\ttrust\t0\nunpleasant\tanger\t0\nunpleasant\tanticipation\t0\nunpleasant\tdisgust\t1\nunpleasant\tfear\t0\nunpleasant\tjoy\t0\nunpleasant\tnegative\t1\nunpleasant\tpositive\t0\nunpleasant\tsadness\t1\nunpleasant\tsurprise\t0\nunpleasant\ttrust\t0\nunpopular\tanger\t0\nunpopular\tanticipation\t0\nunpopular\tdisgust\t1\nunpopular\tfear\t0\nunpopular\tjoy\t0\nunpopular\tnegative\t1\nunpopular\tpositive\t0\nunpopular\tsadness\t1\nunpopular\tsurprise\t0\nunpopular\ttrust\t0\nunprecedented\tanger\t0\nunprecedented\tanticipation\t0\nunprecedented\tdisgust\t0\nunprecedented\tfear\t0\nunprecedented\tjoy\t0\nunprecedented\tnegative\t0\nunprecedented\tpositive\t0\nunprecedented\tsadness\t0\nunprecedented\tsurprise\t1\nunprecedented\ttrust\t0\nunpredictable\tanger\t0\nunpredictable\tanticipation\t0\nunpredictable\tdisgust\t0\nunpredictable\tfear\t0\nunpredictable\tjoy\t0\nunpredictable\tnegative\t1\nunpredictable\tpositive\t0\nunpredictable\tsadness\t0\nunpredictable\tsurprise\t1\nunpredictable\ttrust\t0\nunprepared\tanger\t0\nunprepared\tanticipation\t0\nunprepared\tdisgust\t0\nunprepared\tfear\t0\nunprepared\tjoy\t0\nunprepared\tnegative\t1\nunprepared\tpositive\t0\nunprepared\tsadness\t0\nunprepared\tsurprise\t0\nunprepared\ttrust\t0\nunpretentious\tanger\t0\nunpretentious\tanticipation\t0\nunpretentious\tdisgust\t0\nunpretentious\tfear\t0\nunpretentious\tjoy\t0\nunpretentious\tnegative\t0\nunpretentious\tpositive\t1\nunpretentious\tsadness\t0\nunpretentious\tsurprise\t0\nunpretentious\ttrust\t0\nunproductive\tanger\t0\nunproductive\tanticipation\t0\nunproductive\tdisgust\t0\nunproductive\tfear\t0\nunproductive\tjoy\t0\nunproductive\tnegative\t1\nunproductive\tpositive\t0\nunproductive\tsadness\t0\nunproductive\tsurprise\t0\nunproductive\ttrust\t0\nunprofitable\tanger\t0\nunprofitable\tanticipation\t0\nunprofitable\tdisgust\t0\nunprofitable\tfear\t0\nunprofitable\tjoy\t0\nunprofitable\tnegative\t1\nunprofitable\tpositive\t0\nunprofitable\tsadness\t0\nunprofitable\tsurprise\t0\nunprofitable\ttrust\t0\nunprotected\tanger\t0\nunprotected\tanticipation\t0\nunprotected\tdisgust\t0\nunprotected\tfear\t0\nunprotected\tjoy\t0\nunprotected\tnegative\t1\nunprotected\tpositive\t0\nunprotected\tsadness\t0\nunprotected\tsurprise\t0\nunprotected\ttrust\t0\nunproven\tanger\t0\nunproven\tanticipation\t0\nunproven\tdisgust\t0\nunproven\tfear\t0\nunproven\tjoy\t0\nunproven\tnegative\t0\nunproven\tpositive\t0\nunproven\tsadness\t0\nunproven\tsurprise\t0\nunproven\ttrust\t0\nunpublished\tanger\t0\nunpublished\tanticipation\t1\nunpublished\tdisgust\t0\nunpublished\tfear\t0\nunpublished\tjoy\t0\nunpublished\tnegative\t1\nunpublished\tpositive\t0\nunpublished\tsadness\t1\nunpublished\tsurprise\t0\nunpublished\ttrust\t0\nunquestionable\tanger\t0\nunquestionable\tanticipation\t0\nunquestionable\tdisgust\t0\nunquestionable\tfear\t0\nunquestionable\tjoy\t0\nunquestionable\tnegative\t0\nunquestionable\tpositive\t1\nunquestionable\tsadness\t0\nunquestiona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satisfied\ttrust\t0\nunsavory\tanger\t0\nunsavory\tanticipation\t0\nunsavory\tdisgust\t0\nunsavory\tfear\t0\nunsavory\tjoy\t0\nunsavory\tnegative\t1\nunsavory\tpositive\t0\nunsavory\tsadness\t0\nunsavory\tsurprise\t0\nunsavory\ttrust\t0\nunscathed\tanger\t0\nunscathed\tanticipation\t0\nunscathed\tdisgust\t0\nunscathed\tfear\t0\nunscathed\tjoy\t0\nunscathed\tnegative\t0\nunscathed\tpositive\t1\nunscathed\tsadness\t0\nunscathed\tsurprise\t0\nunscathed\ttrust\t0\nunscientific\tanger\t0\nunscientific\tanticipation\t0\nunscientific\tdisgust\t0\nunscientific\tfear\t0\nunscientific\tjoy\t0\nunscientific\tnegative\t0\nunscientific\tpositive\t0\nunscientific\tsadness\t0\nunscientific\tsurprise\t0\nunscientific\ttrust\t0\nunscrupulous\tanger\t0\nunscrupulous\tanticipation\t0\nunscrupulous\tdisgust\t0\nunscrupulous\tfear\t0\nunscrupulous\tjoy\t0\nunscrupulous\tnegative\t1\nunscrupulous\tpositive\t0\nunscrupulous\tsadness\t0\nunscrupulous\tsurprise\t0\nunscrupulous\ttrust\t0\nunseat\tanger\t0\nunseat\tanticipation\t0\nunseat\tdisgust\t0\nunseat\tfear\t0\nunseat\tjoy\t0\nunseat\tnegative\t0\nunseat\tpositive\t0\nunseat\tsadness\t1\nunseat\tsurprise\t0\nunseat\ttrust\t0\nunseen\tanger\t0\nunseen\tanticipation\t0\nunseen\tdisgust\t0\nunseen\tfear\t0\nunseen\tjoy\t0\nunseen\tnegative\t0\nunseen\tpositive\t0\nunseen\tsadness\t0\nunseen\tsurprise\t0\nunseen\ttrust\t0\nunselfish\tanger\t0\nunselfish\tanticipation\t0\nunselfish\tdisgust\t0\nunselfish\tfear\t0\nunselfish\tjoy\t0\nunselfish\tnegative\t0\nunselfish\tpositive\t1\nunselfish\tsadness\t0\nunselfish\tsurprise\t0\nunselfish\ttrust\t0\nunsettled\tanger\t1\nunsettled\tanticipation\t0\nunsettled\tdisgust\t1\nunsettled\tfear\t1\nunsettled\tjoy\t0\nunsettled\tnegative\t1\nunsettled\tpositive\t0\nunsettled\tsadness\t0\nunsettled\tsurprise\t0\nunsettled\ttrust\t0\nunsightly\tanger\t0\nunsightly\tanticipation\t0\nunsightly\tdisgust\t1\nunsightly\tfear\t0\nunsightly\tjoy\t0\nunsightly\tnegative\t1\nunsightly\tpositive\t0\nunsightly\tsadness\t0\nunsightly\tsurprise\t0\nunsightly\ttrust\t0\nunsophisticated\tanger\t0\nunsophisticated\tanticipation\t0\nunsophisticated\tdisgust\t0\nunsophisticated\tfear\t0\nunsophisticated\tjoy\t0\nunsophisticated\tnegative\t1\nunsophisticated\tpositive\t0\nunsophisticated\tsadness\t0\nunsophisticated\tsurprise\t0\nunsophisticated\ttrust\t0\nunspeakable\tanger\t0\nunspeakable\tanticipation\t0\nunspeakable\tdisgust\t0\nunspeakable\tfear\t1\nunspeakable\tjoy\t0\nunspeakable\tnegative\t1\nunspeakable\tpositive\t0\nunspeakable\tsadness\t0\nunspeakable\tsurprise\t0\nunspeakable\ttrust\t0\nunspecified\tanger\t0\nunspecified\tanticipation\t0\nunspecified\tdisgust\t0\nunspecified\tfear\t0\nunspecified\tjoy\t0\nunspecified\tnegative\t0\nunspecified\tpositive\t0\nunspecified\tsadness\t0\nunspecified\tsurprise\t0\nunspecified\ttrust\t0\nunstable\tanger\t0\nunstable\tanticipation\t0\nunstable\tdisgust\t0\nunstable\tfear\t1\nunstable\tjoy\t0\nunstable\tnegative\t1\nunstable\tpositive\t0\nunstable\tsadness\t0\nunstable\tsurprise\t1\nunstable\ttrust\t0\nunsteady\tanger\t0\nunsteady\tanticipation\t0\nunsteady\tdisgust\t0\nunsteady\tfear\t1\nunsteady\tjoy\t0\nunsteady\tnegative\t0\nunsteady\tpositive\t0\nunsteady\tsadness\t0\nunsteady\tsurprise\t0\nunsteady\ttrust\t0\nunsuccessful\tanger\t0\nunsuccessful\tanticipation\t0\nunsuccessful\tdisgust\t0\nunsuccessful\tfear\t0\nunsuccessful\tjoy\t0\nunsuccessful\tnegative\t1\nunsuccessful\tpositive\t0\nunsuccessful\tsadness\t1\nunsuccessful\tsurprise\t0\nunsuccessful\ttrust\t0\nunsuitable\tanger\t0\nunsuitable\tanticipation\t0\nunsuitable\tdisgust\t0\nunsuitable\tfear\t0\nunsuitable\tjoy\t0\nunsuitable\tnegative\t1\nunsuitable\tpositive\t0\nunsuitable\tsadness\t0\nunsuitable\tsurprise\t0\nunsuitable\ttrust\t0\nunsung\tanger\t0\nunsung\tanticipation\t0\nunsung\tdisgust\t0\nunsung\tfear\t0\nunsung\tjoy\t0\nunsung\tnegative\t1\nunsung\tpositive\t0\nunsung\tsadness\t0\nunsung\tsurprise\t0\nunsung\ttrust\t0\nunsupported\tanger\t0\nunsupported\tanticipation\t0\nunsupported\tdisgust\t0\nunsupported\tfear\t0\nunsupported\tjoy\t0\nunsupported\tnegative\t1\nunsupported\tpositive\t0\nunsupported\tsadness\t0\nunsupported\tsurprise\t0\nunsupported\ttrust\t0\nunsurpassed\tanger\t0\nunsurpassed\tanticipation\t1\nunsurpassed\tdisgust\t0\nunsurpassed\tfear\t1\nunsurpassed\tjoy\t1\nunsurpassed\tnegative\t0\nunsurpassed\tpositive\t1\nunsurpassed\tsadness\t0\nunsurpassed\tsurprise\t0\nunsurpassed\ttrust\t1\nunsuspecting\tanger\t0\nunsuspecting\tanticipation\t0\nunsuspecting\tdisgust\t0\nunsuspecting\tfear\t0\nunsuspecting\tjoy\t0\nunsuspecting\tnegative\t0\nunsuspecting\tpositive\t0\nunsuspecting\tsadness\t0\nunsuspecting\tsurprise\t1\nunsuspecting\ttrust\t0\nunsustainable\tanger\t0\nunsustainable\tanticipation\t0\nunsustainable\tdisgust\t0\nunsustainable\tfear\t0\nunsustainable\tjoy\t0\nunsustainable\tnegative\t1\nunsustainable\tpositive\t0\nunsustainable\tsadness\t0\nunsustainable\tsurprise\t0\nunsustainable\ttrust\t0\nunsweetened\tanger\t0\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egative\t0\nwaltz\tpositive\t0\nwaltz\tsadness\t0\nwaltz\tsurprise\t0\nwaltz\ttrust\t0\nwan\tanger\t0\nwan\tanticipation\t0\nwan\tdisgust\t0\nwan\tfear\t1\nwan\tjoy\t0\nwan\tnegative\t1\nwan\tpositive\t0\nwan\tsadness\t1\nwan\tsurprise\t0\nwan\ttrust\t0\nwand\tanger\t0\nwand\tanticipation\t0\nwand\tdisgust\t0\nwand\tfear\t0\nwand\tjoy\t0\nwand\tnegative\t0\nwand\tpositive\t0\nwand\tsadness\t0\nwand\tsurprise\t0\nwand\ttrust\t0\nwander\tanger\t0\nwander\tanticipation\t0\nwander\tdisgust\t0\nwander\tfear\t0\nwander\tjoy\t0\nwander\tnegative\t0\nwander\tpositive\t0\nwander\tsadness\t0\nwander\tsurprise\t0\nwander\ttrust\t0\nwanderer\tanger\t0\nwanderer\tanticipation\t0\nwanderer\tdisgust\t0\nwanderer\tfear\t0\nwanderer\tjoy\t0\nwanderer\tnegative\t0\nwanderer\tpositive\t0\nwanderer\tsadness\t0\nwanderer\tsurprise\t0\nwanderer\ttrust\t0\nwandering\tanger\t0\nwandering\tanticipation\t0\nwandering\tdisgust\t0\nwandering\tfear\t0\nwandering\tjoy\t0\nwandering\tnegative\t0\nwandering\tpositive\t0\nwandering\tsadness\t0\nwandering\tsurprise\t0\nwandering\ttrust\t0\nwane\tanger\t0\nwane\tanticipation\t0\nwane\tdisgust\t0\nwane\tfear\t0\nwane\tjoy\t0\nwane\tnegative\t1\nwane\tpositive\t0\nwane\tsadness\t1\nwane\tsurprise\t0\nwane\ttrust\t0\nwaning\tanger\t0\nwaning\tanticipation\t0\nwaning\tdisgust\t0\nwaning\tfear\t0\nwaning\tjoy\t0\nwaning\tnegative\t0\nwaning\tpositive\t0\nwaning\tsadness\t0\nwaning\tsurprise\t0\nwaning\ttrust\t0\nwanting\tanger\t0\nwanting\tanticipation\t0\nwanting\tdisgust\t0\nwanting\tfear\t0\nwanting\tjoy\t0\nwanting\tnegative\t1\nwanting\tpositive\t0\nwanting\tsadness\t1\nwanting\tsurprise\t0\nwanting\ttrust\t0\nwar\tanger\t0\nwar\tanticipation\t0\nwar\tdisgust\t0\nwar\tfear\t1\nwar\tjoy\t0\nwar\tnegative\t1\nwar\tpositive\t0\nwar\tsadness\t0\nwar\tsurprise\t0\nwar\ttrust\t0\nwarbler\tanger\t0\nwarbler\tanticipation\t0\nwarbler\tdisgust\t0\nwarbler\tfear\t0\nwarbler\tjoy\t0\nwarbler\tnegative\t0\nwarbler\tpositive\t0\nwarbler\tsadness\t0\nwarbler\tsurprise\t0\nwarbler\ttrust\t0\nward\tanger\t0\nward\tanticipation\t0\nward\tdisgust\t0\nward\tfear\t0\nward\tjoy\t0\nward\tnegative\t0\nward\tpositive\t0\nward\tsadness\t0\nward\tsurprise\t0\nward\ttrust\t0\nwarden\tanger\t1\nwarden\tanticipation\t0\nwarden\tdisgust\t0\nwarden\tfear\t1\nwarden\tjoy\t0\nwarden\tnegative\t1\nwarden\tpositive\t0\nwarden\tsadness\t0\nwarden\tsurprise\t0\nwarden\ttrust\t1\nwardrobe\tanger\t0\nwardrobe\tanticipation\t0\nwardrobe\tdisgust\t0\nwardrobe\tfear\t0\nwardrobe\tjoy\t0\nwardrobe\tnegative\t0\nwardrobe\tpositive\t0\nwardrobe\tsadness\t0\nwardrobe\tsurprise\t0\nwardrobe\ttrust\t0\nware\tanger\t0\nware\tanticipation\t0\nware\tdisgust\t0\nware\tfear\t1\nware\tjoy\t0\nware\tnegative\t1\nware\tpositive\t0\nware\tsadness\t0\nware\tsurprise\t0\nware\ttrust\t0\nwarehouse\tanger\t0\nwarehouse\tanticipation\t0\nwarehouse\tdisgust\t0\nwarehouse\tfear\t0\nwarehouse\tjoy\t0\nwarehouse\tnegative\t0\nwarehouse\tpositive\t0\nwarehouse\tsadness\t0\nwarehouse\tsurprise\t0\nwarehouse\ttrust\t0\nwarfare\tanger\t1\nwarfare\tanticipation\t0\nwarfare\tdisgust\t0\nwarfare\tfear\t1\nwarfare\tjoy\t0\nwarfare\tnegative\t1\nwarfare\tpositive\t0\nwarfare\tsadness\t1\nwarfare\tsurprise\t0\nwarfare\ttrust\t0\nwarlike\tanger\t1\nwarlike\tanticipation\t0\nwarlike\tdisgust\t0\nwarlike\tfear\t1\nwarlike\tjoy\t0\nwarlike\tnegative\t1\nwarlike\tpositive\t0\nwarlike\tsadness\t0\nwarlike\tsurprise\t0\nwarlike\ttrust\t0\nwarlock\tanger\t0\nwarlock\tanticipation\t0\nwarlock\tdisgust\t0\nwarlock\tfear\t1\nwarlock\tjoy\t0\nwarlock\tnegative\t0\nwarlock\tpositive\t0\nwarlock\tsadness\t0\nwarlock\tsurprise\t0\nwarlock\ttrust\t0\nwarming\tanger\t0\nwarming\tanticipation\t0\nwarming\tdisgust\t0\nwarming\tfear\t0\nwarming\tjoy\t0\nwarming\tnegative\t0\nwarming\tpositive\t0\nwarming\tsadness\t0\nwarming\tsurprise\t0\nwarming\ttrust\t0\nwarn\tanger\t0\nwarn\tanticipation\t1\nwarn\tdisgust\t0\nwarn\tfear\t1\nwarn\tjoy\t0\nwarn\tnegative\t1\nwarn\tpositive\t0\nwarn\tsadness\t0\nwarn\tsurprise\t1\nwarn\ttrust\t1\nwarned\tanger\t0\nwarned\tanticipation\t1\nwarned\tdisgust\t0\nwarned\tfear\t1\nwarned\tjoy\t0\nwarned\tnegative\t0\nwarned\tpositive\t0\nwarned\tsadness\t0\nwarned\tsurprise\t1\nwarned\ttrust\t0\nwarning\tanger\t0\nwarning\tanticipation\t0\nwarning\tdisgust\t0\nwarning\tfear\t1\nwarning\tjoy\t0\nwarning\tnegative\t0\nwarning\tpositive\t0\nwarning\tsadness\t0\nwarning\tsurprise\t0\nwarning\ttrust\t0\nwarp\tanger\t1\nwarp\tanticipation\t0\nwarp\tdisgust\t0\nwarp\tfear\t0\nwarp\tjoy\t0\nwarp\tnegative\t1\nwarp\tpositive\t0\nwarp\tsadness\t1\nwarp\tsurprise\t0\nwarp\ttrust\t0\nwarped\tanger\t0\nwarped\tanticipation\t0\nwarped\tdisgust\t0\nwarped\tfear\t0\nwarped\tjoy\t0\nwarped\tnegative\t1\nwarped\tpositive\t0\nwarped\tsadness\t0\nwarped\tsurprise\t0\nwarped\ttrust\t0\nwarrant\tanger\t0\nwarrant\tanticipation\t0\nwarrant\tdisgust\t0\nwarrant\tfear\t0\nwarrant\tjoy\t0\nwarrant\tnegative\t0\nwarrant\tpositive\t0\nwarrant\tsadness\t0\nwarrant\tsurprise\t0\nwarran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  },
  {
    "path": "NewsSentiment/knowledge/nrcemolex/converter.py",
    "content": "import os\nfrom collections import defaultdict, Counter\nfrom pathlib import Path\nimport csv\n\nfrom NewsSentiment.fxlogger import get_logger\nfrom NewsSentiment.diskdict import DiskDict\n\nEMOTION2INDEX = {\n    \"anger\": 0,\n    \"anticipation\": 1,\n    \"disgust\": 2,\n    \"fear\": 3,\n    \"joy\": 4,\n    \"negative\": 5,\n    \"positive\": 6,\n    \"sadness\": 7,\n    \"surprise\": 8,\n    \"trust\": 9,\n}\nTHIS_DIR = Path(os.path.dirname(os.path.realpath(__file__)))\nPATH_DICT_NRC_EMOLEX = THIS_DIR / \"NRC-Emotion-Lexicon-Wordlevel-v0.92.txt.ddict\"\n\nlogger = get_logger()\n\n\ndef convert_txt_to_dict():\n    path_dict = THIS_DIR / \"NRC-Emotion-Lexicon-Wordlevel-v0.92.txt\"\n\n    term2emotions = defaultdict(set)\n    emotion_counter = Counter()\n    with open(path_dict, \"r\") as csv_file:\n        csv_reader = csv.reader(csv_file, delimiter=\"\\t\")\n        for term, emotion, is_present in csv_reader:\n            if is_present == \"1\":\n                emotion_index = EMOTION2INDEX[emotion]\n                term2emotions[term].add(emotion_index)\n                emotion_counter[emotion] += 1\n            elif is_present == \"0\":\n                pass\n            else:\n                raise ValueError\n    logger.info(\"read %s terms\", len(term2emotions))\n    logger.info(\"emotion count:\\n%s\", emotion_counter.most_common())\n\n    logger.info(\"saving to %s...\", None)\n    ddict_emolex = DiskDict(PATH_DICT_NRC_EMOLEX)\n    ddict_emolex.update(term2emotions)\n    ddict_emolex.sync_to_disk()\n    logger.info(\"done\")\n\n\nif __name__ == \"__main__\":\n    convert_txt_to_dict()\n"
  },
  {
    "path": "NewsSentiment/knowledge/nrcemolex/nrcemolex.py",
    "content": "import torch\n\nfrom NewsSentiment.knowledge.knowledgeutils import find_key_original_or_lc\nfrom NewsSentiment.knowledge.nrcemolex.converter import PATH_DICT_NRC_EMOLEX, EMOTION2INDEX\nfrom NewsSentiment.diskdict import DiskDict\n\n__ddict_emolex = DiskDict(PATH_DICT_NRC_EMOLEX)\n__ddict_emolex_keys_lower = {k.lower(): v for k, v in __ddict_emolex.items()}\n__num_emotions = 10\nassert len(__ddict_emolex) == 6468\nassert len(EMOTION2INDEX) == __num_emotions\n\n\ndef get_num_nrc_emotions():\n    return __num_emotions\n\n\ndef get_nrc_emotions_as_tensor(term: str):\n    emotions = find_key_original_or_lc(__ddict_emolex, __ddict_emolex_keys_lower, term)\n    tensor_emotions = torch.zeros(__num_emotions, dtype=torch.long)\n    for emotion_index in emotions:\n        tensor_emotions[emotion_index] = 1\n    return tensor_emotions\n"
  },
  {
    "path": "NewsSentiment/knowledge/zeros/zerosknowledge.py",
    "content": "import torch\n\n\ndef get_num_zero_dimensions():\n    # while one dimension would suffice, using only one can cause (especially when using\n    # single_targets=True) that the batcher by pytorch removes the singleton dimension. specifically,\n    # with only one target per batch item, the size of the knowledge source will be 1, 150, 1, whereas the last dimension\n    # is removed during batching by pytorch. so to keep things simple, we just add a two here to avoid having a\n    # singleton dimension at the end\n    return 2\n\n\ndef get_zeros_as_tensor(term: str):\n    tensor_emotions = torch.zeros(get_num_zero_dimensions(), dtype=torch.long)\n    return tensor_emotions\n"
  },
  {
    "path": "NewsSentiment/layers/AggregatorForBert.py",
    "content": "import torch.nn as nn\nimport torch\n\n\nclass AggregatorForBert(nn.Module):\n    \"\"\"\n    According to https://huggingface.co/transformers/model_doc/bert.html#bertmodel we\n    should not (as in the original SPC version) the pooler_output but get the\n    last_hidden_state and \"averaging or pooling the sequence of hidden-states for the\n    whole input sequence\"\n    \"\"\"\n    def __init__(self, spc_lm_representation: str):\n        super(AggregatorForBert, self).__init__()\n        self.spc_lm_representation = spc_lm_representation\n\n    def forward(self, last_hidden_state, pooler_output, all_hidden_states):\n        if self.spc_lm_representation == \"pooler_output\":\n            prepared_output = pooler_output\n        elif self.spc_lm_representation == \"mean_last\":\n            prepared_output = last_hidden_state.mean(dim=1)\n        elif self.spc_lm_representation == \"mean_last_four\":\n            prepared_output = (\n                torch.stack(all_hidden_states[-4:]).mean(dim=0).mean(dim=1)\n            )\n        elif self.spc_lm_representation == \"mean_last_two\":\n            prepared_output = (\n                torch.stack(all_hidden_states[-2:]).mean(dim=0).mean(dim=1)\n            )\n        elif self.spc_lm_representation == \"mean_all\":\n            prepared_output = torch.stack(all_hidden_states).mean(dim=0).mean(dim=1)\n        elif self.spc_lm_representation == \"sum_last\":\n            prepared_output = last_hidden_state.sum(dim=1)\n        elif self.spc_lm_representation == \"sum_last_four\":\n            prepared_output = torch.stack(all_hidden_states[-4:]).sum(dim=0).sum(dim=1)\n        elif self.spc_lm_representation == \"sum_last_two\":\n            prepared_output = torch.stack(all_hidden_states[-2:]).sum(dim=0).sum(dim=1)\n        elif self.spc_lm_representation == \"sum_all\":\n            prepared_output = torch.stack(all_hidden_states).sum(dim=0).sum(dim=1)\n        return prepared_output\n"
  },
  {
    "path": "NewsSentiment/layers/__init__.py",
    "content": "# -*- coding: utf-8 -*-\n# file: __init__.py\n# author: songyouwei <youwei0314@gmail.com>\n# Copyright (C) 2018. All Rights Reserved."
  },
  {
    "path": "NewsSentiment/layers/attention.py",
    "content": "# -*- coding: utf-8 -*-\n# file: attention.py\n# author: songyouwei <youwei0314@gmail.com> for top two classes, huggingface for third (slightly\n# adapted by FH)\n# Copyright (C) 2020. All Rights Reserved.\n\nimport math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass Attention(nn.Module):\n    def __init__(\n        self,\n        embed_dim,\n        hidden_dim=None,\n        out_dim=None,\n        n_head=1,\n        score_function=\"dot_product\",\n        dropout=0,\n    ):\n        \"\"\" Attention Mechanism\n        :param embed_dim:\n        :param hidden_dim:\n        :param out_dim:\n        :param n_head: num of head (Multi-Head Attention)\n        :param score_function: scaled_dot_product / mlp (concat) / bi_linear (general dot)\n        :return (?, q_len, out_dim,)\n        \"\"\"\n        super(Attention, self).__init__()\n        if hidden_dim is None:\n            hidden_dim = embed_dim // n_head\n        if out_dim is None:\n            out_dim = embed_dim\n        self.embed_dim = embed_dim\n        self.hidden_dim = hidden_dim\n        self.n_head = n_head\n        self.score_function = score_function\n        self.w_k = nn.Linear(embed_dim, n_head * hidden_dim)\n        self.w_q = nn.Linear(embed_dim, n_head * hidden_dim)\n        self.proj = nn.Linear(n_head * hidden_dim, out_dim)\n        self.dropout = nn.Dropout(dropout)\n        if score_function == \"mlp\":\n            self.weight = nn.Parameter(torch.Tensor(hidden_dim * 2))\n        elif self.score_function == \"bi_linear\":\n            self.weight = nn.Parameter(torch.Tensor(hidden_dim, hidden_dim))\n        else:  # dot_product / scaled_dot_product\n            self.register_parameter(\"weight\", None)\n        self.reset_parameters()\n\n    def reset_parameters(self):\n        stdv = 1.0 / math.sqrt(self.hidden_dim)\n        if self.weight is not None:\n            self.weight.data.uniform_(-stdv, stdv)\n\n    def forward(self, k, q):\n        if len(q.shape) == 2:  # q_len missing\n            q = torch.unsqueeze(q, dim=1)\n        if len(k.shape) == 2:  # k_len missing\n            k = torch.unsqueeze(k, dim=1)\n        mb_size = k.shape[0]  # ?\n        k_len = k.shape[1]\n        q_len = q.shape[1]\n        # k: (?, k_len, embed_dim,)\n        # q: (?, q_len, embed_dim,)\n        # kx: (n_head*?, k_len, hidden_dim)\n        # qx: (n_head*?, q_len, hidden_dim)\n        # score: (n_head*?, q_len, k_len,)\n        # output: (?, q_len, out_dim,)\n        kx = self.w_k(k).view(mb_size, k_len, self.n_head, self.hidden_dim)\n        kx = kx.permute(2, 0, 1, 3).contiguous().view(-1, k_len, self.hidden_dim)\n        qx = self.w_q(q).view(mb_size, q_len, self.n_head, self.hidden_dim)\n        qx = qx.permute(2, 0, 1, 3).contiguous().view(-1, q_len, self.hidden_dim)\n        if self.score_function == \"dot_product\":\n            kt = kx.permute(0, 2, 1)\n            score = torch.bmm(qx, kt)\n        elif self.score_function == \"scaled_dot_product\":\n            kt = kx.permute(0, 2, 1)\n            qkt = torch.bmm(qx, kt)\n            score = torch.div(qkt, math.sqrt(self.hidden_dim))\n        elif self.score_function == \"mlp\":\n            kxx = torch.unsqueeze(kx, dim=1).expand(-1, q_len, -1, -1)\n            qxx = torch.unsqueeze(qx, dim=2).expand(-1, -1, k_len, -1)\n            kq = torch.cat((kxx, qxx), dim=-1)  # (n_head*?, q_len, k_len, hidden_dim*2)\n            score = torch.tanh(torch.matmul(kq, self.weight))\n        elif self.score_function == \"bi_linear\":\n            qw = torch.matmul(qx, self.weight)\n            kt = kx.permute(0, 2, 1)\n            score = torch.bmm(qw, kt)\n        else:\n            raise RuntimeError(\"invalid score_function\")\n        score = F.softmax(score, dim=-1)\n        output = torch.bmm(score, kx)  # (n_head*?, q_len, hidden_dim)\n        output = torch.cat(\n            torch.split(output, mb_size, dim=0), dim=-1\n        )  # (?, q_len, n_head*hidden_dim)\n        output = self.proj(output)  # (?, q_len, out_dim)\n        output = self.dropout(output)\n        return output, score\n\n\nclass NoQueryAttention(Attention):\n    \"\"\"q is a parameter\"\"\"\n\n    def __init__(\n        self,\n        embed_dim,\n        hidden_dim=None,\n        out_dim=None,\n        n_head=1,\n        score_function=\"dot_product\",\n        q_len=1,\n        dropout=0,\n    ):\n        super(NoQueryAttention, self).__init__(\n            embed_dim, hidden_dim, out_dim, n_head, score_function, dropout\n        )\n        self.q_len = q_len\n        self.q = nn.Parameter(torch.Tensor(q_len, embed_dim))\n        self.reset_q()\n\n    def reset_q(self):\n        stdv = 1.0 / math.sqrt(self.embed_dim)\n        self.q.data.uniform_(-stdv, stdv)\n\n    def forward(self, k, **kwargs):\n        mb_size = k.shape[0]\n        q = self.q.expand(mb_size, -1, -1)\n        return super(NoQueryAttention, self).forward(k, q)\n\n\nclass FXBertSelfAttention(nn.Module):\n    \"\"\"\n    Identical to the class BertSelfAttention by transformers by huggingface, but\n    can be used without the need to have a config instance of class BertConfig but\n    instead the required values can be passed on directly\n    \"\"\"\n    def __init__(self, hidden_size, num_attention_heads, attention_probs_dropout_prob=0.1):\n        super().__init__()\n        if hidden_size % num_attention_heads != 0:\n            raise ValueError(\n                \"The hidden size (%d) is not a multiple of the number of attention \"\n                \"heads (%d)\" % (hidden_size, num_attention_heads)\n            )\n\n        self.num_attention_heads = num_attention_heads\n        self.attention_head_size = int(hidden_size / num_attention_heads)\n        self.all_head_size = self.num_attention_heads * self.attention_head_size\n\n        self.query = nn.Linear(hidden_size, self.all_head_size)\n        self.key = nn.Linear(hidden_size, self.all_head_size)\n        self.value = nn.Linear(hidden_size, self.all_head_size)\n\n        self.dropout = nn.Dropout(attention_probs_dropout_prob)\n\n    def transpose_for_scores(self, x):\n        new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)\n        x = x.view(*new_x_shape)\n        return x.permute(0, 2, 1, 3)\n\n    def forward(\n            self,\n            hidden_states,\n            attention_mask=None,\n            head_mask=None,\n            encoder_hidden_states=None,\n            encoder_attention_mask=None,\n            output_attentions=False,\n    ):\n        mixed_query_layer = self.query(hidden_states)\n\n        # If this is instantiated as a cross-attention module, the keys\n        # and values come from an encoder; the attention mask needs to be\n        # such that the encoder's padding tokens are not attended to.\n        if encoder_hidden_states is not None:\n            mixed_key_layer = self.key(encoder_hidden_states)\n            mixed_value_layer = self.value(encoder_hidden_states)\n            attention_mask = encoder_attention_mask\n        else:\n            mixed_key_layer = self.key(hidden_states)\n            mixed_value_layer = self.value(hidden_states)\n\n        query_layer = self.transpose_for_scores(mixed_query_layer)\n        key_layer = self.transpose_for_scores(mixed_key_layer)\n        value_layer = self.transpose_for_scores(mixed_value_layer)\n\n        # Take the dot product between \"query\" and \"key\" to get the raw attention scores.\n        attention_scores = torch.matmul(query_layer, key_layer.transpose(-1, -2))\n        attention_scores = attention_scores / math.sqrt(self.attention_head_size)\n        if attention_mask is not None:\n            # Apply the attention mask is (precomputed for all layers in BertModel forward() function)\n            attention_scores = attention_scores + attention_mask\n\n        # Normalize the attention scores to probabilities.\n        attention_probs = nn.Softmax(dim=-1)(attention_scores)\n\n        # This is actually dropping out entire tokens to attend to, which might\n        # seem a bit unusual, but is taken from the original Transformer paper.\n        attention_probs = self.dropout(attention_probs)\n\n        # Mask heads if we want to\n        if head_mask is not None:\n            attention_probs = attention_probs * head_mask\n\n        context_layer = torch.matmul(attention_probs, value_layer)\n\n        context_layer = context_layer.permute(0, 2, 1, 3).contiguous()\n        new_context_layer_shape = context_layer.size()[:-2] + (self.all_head_size,)\n        context_layer = context_layer.view(*new_context_layer_shape)\n\n        outputs = (context_layer, attention_probs) if output_attentions else (context_layer,)\n        return outputs"
  },
  {
    "path": "NewsSentiment/layers/dynamic_rnn.py",
    "content": "# -*- coding: utf-8 -*-\n# file: dynamic_rnn.py\n# author: songyouwei <youwei0314@gmail.com>\n# Copyright (C) 2018. All Rights Reserved.\n\n\nimport torch\nimport torch.nn as nn\nimport numpy as np\n\nclass DynamicLSTM(nn.Module):\n    def __init__(self, input_size, hidden_size, num_layers=1, bias=True, batch_first=True, dropout=0,\n                 bidirectional=False, only_use_last_hidden_state=False, rnn_type = 'LSTM'):\n        \"\"\"\n        LSTM which can hold variable length sequence, use like TensorFlow's RNN(input, length...).\n\n        :param input_size:The number of expected features in the input x\n        :param hidden_size:The number of features in the hidden state h\n        :param num_layers:Number of recurrent layers.\n        :param bias:If False, then the layer does not use bias weights b_ih and b_hh. Default: True\n        :param batch_first:If True, then the input and output tensors are provided as (batch, seq, feature)\n        :param dropout:If non-zero, introduces a dropout layer on the outputs of each RNN layer except the last layer\n        :param bidirectional:If True, becomes a bidirectional RNN. Default: False\n        :param rnn_type: {LSTM, GRU, RNN}\n        \"\"\"\n        super(DynamicLSTM, self).__init__()\n        self.input_size = input_size\n        self.hidden_size = hidden_size\n        self.num_layers = num_layers\n        self.bias = bias\n        self.batch_first = batch_first\n        self.dropout = dropout\n        self.bidirectional = bidirectional\n        self.only_use_last_hidden_state = only_use_last_hidden_state\n        self.rnn_type = rnn_type\n        \n        if self.rnn_type == 'LSTM': \n            self.RNN = nn.LSTM(\n                input_size=input_size, hidden_size=hidden_size, num_layers=num_layers,\n                bias=bias, batch_first=batch_first, dropout=dropout, bidirectional=bidirectional)  \n        elif self.rnn_type == 'GRU':\n            self.RNN = nn.GRU(\n                input_size=input_size, hidden_size=hidden_size, num_layers=num_layers,\n                bias=bias, batch_first=batch_first, dropout=dropout, bidirectional=bidirectional)\n        elif self.rnn_type == 'RNN':\n            self.RNN = nn.RNN(\n                input_size=input_size, hidden_size=hidden_size, num_layers=num_layers,\n                bias=bias, batch_first=batch_first, dropout=dropout, bidirectional=bidirectional)\n        \n\n    def forward(self, x, x_len):\n        \"\"\"\n        sequence -> sort -> pad and pack ->process using RNN -> unpack ->unsort\n\n        :param x: sequence embedding vectors\n        :param x_len: numpy/tensor list\n        :return:\n        \"\"\"\n        \"\"\"sort\"\"\"\n        x_sort_idx = torch.sort(-x_len)[1].long()\n        x_unsort_idx = torch.sort(x_sort_idx)[1].long()\n        x_len = x_len[x_sort_idx]\n        x = x[x_sort_idx]\n        \"\"\"pack\"\"\"\n        x_emb_p = torch.nn.utils.rnn.pack_padded_sequence(x, x_len, batch_first=self.batch_first)\n        \n        # process using the selected RNN\n        if self.rnn_type == 'LSTM': \n            out_pack, (ht, ct) = self.RNN(x_emb_p, None)\n        else: \n            out_pack, ht = self.RNN(x_emb_p, None)\n            ct = None\n        \"\"\"unsort: h\"\"\"\n        ht = torch.transpose(ht, 0, 1)[\n            x_unsort_idx]  # (num_layers * num_directions, batch, hidden_size) -> (batch, ...)\n        ht = torch.transpose(ht, 0, 1)\n\n        if self.only_use_last_hidden_state:\n            return ht\n        else:\n            \"\"\"unpack: out\"\"\"\n            out = torch.nn.utils.rnn.pad_packed_sequence(out_pack, batch_first=self.batch_first)  # (sequence, lengths)\n            out = out[0]  #\n            out = out[x_unsort_idx]\n            \"\"\"unsort: out c\"\"\"\n            if self.rnn_type =='LSTM':\n                ct = torch.transpose(ct, 0, 1)[\n                    x_unsort_idx]  # (num_layers * num_directions, batch, hidden_size) -> (batch, ...)\n                ct = torch.transpose(ct, 0, 1)\n\n            return out, (ht, ct)\n"
  },
  {
    "path": "NewsSentiment/layers/point_wise_feed_forward.py",
    "content": "# -*- coding: utf-8 -*-\n# file: point_wise_feed_forward.py\n# author: songyouwei <youwei0314@gmail.com>\n# Copyright (C) 2018. All Rights Reserved.\n\nimport torch.nn as nn\n\n\nclass PositionwiseFeedForward(nn.Module):\n    ''' A two-feed-forward-layer module '''\n    def __init__(self, d_hid, d_inner_hid=None, dropout=0):\n        super(PositionwiseFeedForward, self).__init__()\n        if d_inner_hid is None:\n            d_inner_hid = d_hid\n        self.w_1 = nn.Conv1d(d_hid, d_inner_hid, 1)  # position-wise\n        self.w_2 = nn.Conv1d(d_inner_hid, d_hid, 1)  # position-wise\n        self.dropout = nn.Dropout(dropout)\n        self.relu = nn.ReLU()\n\n    def forward(self, x):\n        output = self.relu(self.w_1(x.transpose(1, 2)))\n        output = self.w_2(output).transpose(2, 1)\n        output = self.dropout(output)\n        return output\n"
  },
  {
    "path": "NewsSentiment/layers/pytorchnlpattention.py",
    "content": "import torch\nimport torch.nn as nn\n\n# from https://pytorchnlp.readthedocs.io/en/latest/_modules/torchnlp/nn/attention.html\nclass ClassicAttention(nn.Module):\n    \"\"\" Applies attention mechanism on the `context` using the `query`.\n\n    **Thank you** to IBM for their initial implementation of :class:`Attention`. Here is\n    their `License\n    <https://github.com/IBM/pytorch-seq2seq/blob/master/LICENSE>`__.\n\n    Args:\n        dimensions (int): Dimensionality of the query and context.\n        attention_type (str, optional): How to compute the attention score:\n\n            * dot: :math:`score(H_j,q) = H_j^T q`\n            * general: :math:`score(H_j, q) = H_j^T W_a q`\n\n    Example:\n\n         >>> attention = Attention(256)\n         >>> query = torch.randn(5, 1, 256)\n         >>> context = torch.randn(5, 5, 256)\n         >>> output, weights = attention(query, context)\n         >>> output.size()\n         torch.Size([5, 1, 256])\n         >>> weights.size()\n         torch.Size([5, 1, 5])\n    \"\"\"\n\n    def __init__(self, dimensions, attention_type=\"general\"):\n        super(ClassicAttention, self).__init__()\n\n        if attention_type not in [\"dot\", \"general\"]:\n            raise ValueError(\"Invalid attention type selected.\")\n\n        self.attention_type = attention_type\n        if self.attention_type == \"general\":\n            self.linear_in = nn.Linear(dimensions, dimensions, bias=False)\n\n        self.linear_out = nn.Linear(dimensions * 2, dimensions, bias=False)\n        self.softmax = nn.Softmax(dim=-1)\n        self.tanh = nn.Tanh()\n\n    def forward(self, query, context):\n        \"\"\"\n        Args:\n            query (:class:`torch.FloatTensor` [batch size, output length, dimensions]): Sequence of\n                queries to query the context.\n            context (:class:`torch.FloatTensor` [batch size, query length, dimensions]): Data\n                overwhich to apply the attention mechanism.\n\n        Returns:\n            :class:`tuple` with `output` and `weights`:\n            * **output** (:class:`torch.LongTensor` [batch size, output length, dimensions]):\n              Tensor containing the attended features.\n            * **weights** (:class:`torch.FloatTensor` [batch size, output length, query length]):\n              Tensor containing attention weights.\n        \"\"\"\n        batch_size, output_len, dimensions = query.size()\n        query_len = context.size(1)\n\n        if self.attention_type == \"general\":\n            query = query.reshape(batch_size * output_len, dimensions)\n            query = self.linear_in(query)\n            query = query.reshape(batch_size, output_len, dimensions)\n\n        # TODO: Include mask on PADDING_INDEX?\n\n        # (batch_size, output_len, dimensions) * (batch_size, query_len, dimensions) ->\n        # (batch_size, output_len, query_len)\n        attention_scores = torch.bmm(query, context.transpose(1, 2).contiguous())\n\n        # Compute weights across every context sequence\n        attention_scores = attention_scores.view(batch_size * output_len, query_len)\n        attention_weights = self.softmax(attention_scores)\n        attention_weights = attention_weights.view(batch_size, output_len, query_len)\n\n        # (batch_size, output_len, query_len) * (batch_size, query_len, dimensions) ->\n        # (batch_size, output_len, dimensions)\n        mix = torch.bmm(attention_weights, context)\n\n        # concat -> (batch_size * output_len, 2*dimensions)\n        combined = torch.cat((mix, query), dim=2)\n        combined = combined.view(batch_size * output_len, 2 * dimensions)\n\n        # Apply linear_out on every 2nd dimension of concat\n        # output -> (batch_size, output_len, dimensions)\n        output = self.linear_out(combined).view(batch_size, output_len, dimensions)\n        output = self.tanh(output)\n\n        return output, attention_weights\n"
  },
  {
    "path": "NewsSentiment/layers/squeeze_embedding.py",
    "content": "# -*- coding: utf-8 -*-\n# file: squeeze_embedding.py\n# author: songyouwei <youwei0314@gmail.com>\n# Copyright (C) 2018. All Rights Reserved.\n\n\nimport torch\nimport torch.nn as nn\nimport numpy as np\n\nclass SqueezeEmbedding(nn.Module):\n    \"\"\"\n    Squeeze sequence embedding length to the longest one in the batch\n    \"\"\"\n    def __init__(self, batch_first=True):\n        super(SqueezeEmbedding, self).__init__()\n        self.batch_first = batch_first\n\n    def forward(self, x, x_len):\n        \"\"\"\n        sequence -> sort -> pad and pack -> unpack ->unsort\n        :param x: sequence embedding vectors\n        :param x_len: numpy/tensor list\n        :return:\n        \"\"\"\n        \"\"\"sort\"\"\"\n        x_sort_idx = torch.sort(-x_len)[1].long()\n        x_unsort_idx = torch.sort(x_sort_idx)[1].long()\n        x_len = x_len[x_sort_idx]\n        x = x[x_sort_idx]\n        \"\"\"pack\"\"\"\n        x_emb_p = torch.nn.utils.rnn.pack_padded_sequence(x, x_len, batch_first=self.batch_first)\n        \"\"\"unpack: out\"\"\"\n        out = torch.nn.utils.rnn.pad_packed_sequence(x_emb_p, batch_first=self.batch_first)  # (sequence, lengths)\n        out = out[0]  #\n        \"\"\"unsort\"\"\"\n        out = out[x_unsort_idx]\n        return out\n"
  },
  {
    "path": "NewsSentiment/losses/__init__.py",
    "content": ""
  },
  {
    "path": "NewsSentiment/losses/crossentropycrossweight.py",
    "content": "import torch\nimport torch.nn as nn\n\n# CrossEntropyLoss with additional cross weight loss for two targets\nfrom NewsSentiment.SentimentClasses import SentimentClasses\n\n\nclass CrossEntropyLoss_CrossWeight(nn.Module):\n    def __init__(self, device, ignore_index, weight=None, crossloss_weight=0.2):\n        super(CrossEntropyLoss_CrossWeight, self).__init__()\n        self.device = device\n        self.class_loss = nn.CrossEntropyLoss(weight=weight, ignore_index=ignore_index,)\n        # cosine similarity by default\n        self.cross_weight_loss = nn.CosineSimilarity(dim=2)\n        self.crossloss_weight = crossloss_weight\n        self.crossentropyloss_weight = 1.0 - crossloss_weight\n        self.ignore_index = ignore_index\n\n    def forward(\n        self,\n        predictions: torch.Tensor,\n        true_labels: torch.Tensor,\n        cross_weight: torch.Tensor,\n        target_mask: torch.Tensor,\n    ):\n        \"\"\"\n        Calculate k-dimensional cross entropy loss by comparing predictions and\n        true_labels. Additionally, calculates a cross_weight loss that maximizes the\n        differences between the weights compared between both targets.\n\n        :param predictions: shape: (batch, polarities e.g. 3, targets ie 2)\n        :param true_labels: shape: (batch, targets)\n        :param cross_weight:shape: (batch, targets, seqlen, bertdim)\n        :return:\n        prediction size earlier was batch polarities\n        \"\"\"\n        batch_size, num_classes, num_targets = predictions.size()\n        bert_dim = cross_weight.shape[3]\n\n        # calculate regular cross entropy loss\n        classification_loss = self.class_loss(predictions, true_labels)\n\n        # calculate cross-weight loss\n        # we must not calc the cross weight loss for batch item of two targets,\n        # where 1 or 2 is a fill up target, i.e., the true value is\n        # SentimentClasses.FILLUP_POLARITY_VALUE\n        # get all batch items where the first target is fill up\n        is_ignored_a = true_labels[:, 0]\n        is_ignored_a = is_ignored_a == SentimentClasses.FILLUP_POLARITY_VALUE\n        # get all batch items where the second is\n        is_ignored_b = true_labels[:, 1]\n        is_ignored_b = is_ignored_b == SentimentClasses.FILLUP_POLARITY_VALUE\n        # logical or both lists to one\n        is_ignored_batch_item = is_ignored_a | is_ignored_b\n        # select only those batch items where no target\n        is_not_ignored_batch_item = ~is_ignored_batch_item\n        target_mask = target_mask[is_not_ignored_batch_item, :, :]\n        count_non_ignored_batch_items = target_mask.shape[0]\n\n        # if we have identical targets (=target masks) set cross weight loss to 0\n        target_mask_a = target_mask[:, 0, :]\n        target_mask_b = target_mask[:, 1, :]\n        diff_target_mask = target_mask_a - target_mask_b\n        diff_target_mask = diff_target_mask.sum(dim=1)\n        # shape: batch\n        # diff target mask, will be 0 if the two targets in one batched item are\n        # identical, and 1 if they are different\n        is_different_target_per_two_batch_items = diff_target_mask != 0\n\n        # only selecting different targets effectively zeros out values of identical\n        # targets\n        cross_weight = cross_weight[is_different_target_per_two_batch_items]\n\n        # if there is not at least a single batch item with different targets, shape[0]\n        # will be 0. we use this to test for this condition and if all targets over all\n        # batch items are identical, we skip the cross weight part\n        count_different_targets = cross_weight.shape[0]\n        if count_different_targets == 0:\n            cross_weight_loss = 0\n        else:\n            assert count_different_targets >= 1\n            seq_len = cross_weight.shape[2]\n            weight_a = cross_weight[:, 0, :, :]\n            # weight_b = cross_weight[:, 1, :, :]\n            weight_b = weight_a\n\n            # we add the negative sign, since we actually want to maximize the distance\n            # between both vectors\n            cross_weight_similarity = self.cross_weight_loss(weight_a, weight_b)\n            # cross_weight_similarity will be -1 for absolutely dissimilar values\n            # 0 for unrelated and +1 for identical values\n            # normalize between 0 and 1\n            cross_weight_similarity = (cross_weight_similarity + 1) / 2\n            # 0 = dissimilar, 1 = identical\n            # mean over seq len\n            cross_weight_loss = cross_weight_similarity.mean(dim=1)\n            # at this point we have for each batch item its loss (0 if dissimilar\n            # targets, 1 if identical target in the batch item)\n            # finally, compute the single loss: sum\n            cross_weight_loss = cross_weight_loss.sum()\n            # normalize (divide by number of batch items; note that this can be different\n            # from the number of different targets in the batch)\n            cross_weight_loss = cross_weight_loss / count_non_ignored_batch_items\n\n        # total_loss\n        total_loss = (\n            self.crossentropyloss_weight * classification_loss\n            + self.crossloss_weight * cross_weight_loss\n        )\n\n        return total_loss\n"
  },
  {
    "path": "NewsSentiment/losses/crossentropylosslsr.py",
    "content": "# adapted from ABSA-PyTorch\nimport torch\nimport torch.nn as nn\n\n# CrossEntropyLoss for Label Smoothing Regularization\nfrom NewsSentiment.SentimentClasses import SentimentClasses\n\n\nclass CrossEntropyLoss_LSR(nn.Module):\n    def __init__(self, device, smoothing_value=0.2, weight=None):\n        super(CrossEntropyLoss_LSR, self).__init__()\n        self.smoothing_value = smoothing_value\n        self.device = device\n        self.logSoftmax = nn.LogSoftmax(dim=1)\n        self.weight = weight\n\n    def _create_smooth_one_hot_for_true_targets(\n        self, labels, batch_size, num_classes, num_targets\n    ):\n        \"\"\"\n        Produces a smooth one hot encoded tensor where all \"false\" scalars are set to\n        base_prob, and all \"true\" scalars set to base_prob + 1 - smoothing_value.\n        Effectively, for example for three classes, this results in:\n        False classes: 0.03 (0.3333*0.1=baseprob)\n        True classes: 0.03 + 1 - 0.1 = 0.93\n        :param labels: the true classes\n        :param batch_size:\n        :param num_classes:\n        :return:\n        \"\"\"\n        # prior label distribution is set uniform (see Sec 3.5,\n        # https://arxiv.org/pdf/1902.09314.pdf )\n        prior_distribution = 1.0 / float(num_classes)\n        # calculate base probability\n        base_prob = self.smoothing_value * prior_distribution\n        # initialize 0 tensor\n        one_hot_label = torch.zeros(\n            batch_size, num_classes, num_targets, device=self.device\n        )\n        # set probability of all classes in all batches and targets to the base prob\n        # (in normal one hot encoding, this would be 0 instead)\n        one_hot_label = one_hot_label + base_prob\n\n        if self.weight is not None:\n            raise NotImplementedError(\n                \"test this first!!! currently untested with multi tsc\"\n            )\n            one_hot_label = one_hot_label * self.weight\n\n        # iterate over each single item of the batch\n        for batch_index in range(batch_size):\n            for target_index in range(num_targets):\n                # get the class index\n                class_index = labels[batch_index, target_index].item()\n                if class_index == SentimentClasses.FILLUP_POLARITY_VALUE:\n                    # cant set the one hot encoded here, since there is no \"true\" class\n                    # need to ignore this later\n                    pass\n                else:\n                    # set the class probability\n                    one_hot_label[batch_index, class_index, target_index] += (\n                        1.0 - self.smoothing_value\n                    )\n\n        return one_hot_label\n\n    def forward(\n        self, predictions: torch.Tensor, labels: torch.Tensor, size_average=True\n    ):\n        \"\"\"\n        Calculate k-dimensional cross entropy loss\n        :param predictions: shape: (batch, polarities e.g. 3, targets e.g. 5)\n        :param labels: shape: (batch, targets)\n        :param size_average:\n        :return:\n        prediction size earlier was batch polarities\n        \"\"\"\n        batch_size, num_classes, num_targets = predictions.size()\n        # calculate log of probability of each class (of each batch and target)\n        pre_logsoftmax = self.logSoftmax(predictions)\n\n        smooth_one_hot_for_true_targets = self._create_smooth_one_hot_for_true_targets(\n            labels, batch_size, num_classes, num_targets\n        ).to(self.device)\n\n        # ignore those comparison where labels has a fillup value (=to be ignored)\n        mask_nonfillup = labels != SentimentClasses.FILLUP_POLARITY_VALUE\n        # shape is batch, targets\n        # shape should be batch, classes, targets\n        mask_nonfillup = mask_nonfillup.unsqueeze(1).repeat(1, num_classes, 1)\n        # convert to 1 for True and 0 for False\n        mask_nonfillup = mask_nonfillup.to(torch.int)\n        # multiply so that scalars to be ignored are set to 0 (resulting in 0 loss for\n        # those scalars, i.e., targets)\n        # notes: categorical cross entropy loss does not directly punish on a low level\n        # those predictions (scalars) that belong to incorrect classes (defined by true\n        # or here, labels) but is only calculated by comparing the one true class (\n        # defined by true, or here, labels) where it has a 1 (one hot encoded). since\n        # the probability is 100% of all classes (also the output of the neural network)\n        # the loss still punishes wrong predictions, i.e., if the class probability\n        # should be 100% but is only 25% or 70%, the loss will be non-zero)\n        # as a consequence, when there is no right class in \"true\", there cannot be a\n        # loss. so, the multiplication below, which sets all fillup-targets to 0, has\n        # the expected effect (no loss can result from fill up values, as all their\n        # class probabilities are set to 0)\n        smooth_one_hot_for_true_targets = (\n            smooth_one_hot_for_true_targets * mask_nonfillup\n        )\n\n        # multiply\n        loss = -smooth_one_hot_for_true_targets * pre_logsoftmax\n\n        # aggregate loss to scalar over classes\n        loss = torch.sum(loss, dim=1)\n        # aggregate loss to scalar over targets\n        loss = torch.sum(loss, dim=1)\n\n        if size_average:\n            return torch.mean(loss)\n        else:\n            return torch.sum(loss)\n"
  },
  {
    "path": "NewsSentiment/losses/crossentropylosswithconfidence.py",
    "content": "import torch.nn as nn\nimport torch\n\n\nclass CrossEntropyLossWithConfidence(nn.Module):\n    def __init__(self, weight, ignore_index):\n        super(CrossEntropyLossWithConfidence, self).__init__()\n        self.crossentropyloss = nn.CrossEntropyLoss(\n            weight=weight, ignore_index=ignore_index\n        )\n        self.loss_for_confidence = nn.HuberLoss()\n        self.w_classes = 0.5\n\n    def forward(self, predictions: torch.Tensor, labels: torch.Tensor):\n        # get the prediction components\n        class_preds = predictions[:, 0:3, :]\n        confidence_preds = predictions[:, 3:4, :].squeeze(dim=1)\n\n        # calc the regular class-based loss\n        class_loss = self.crossentropyloss(class_preds, labels)\n\n        # now calc the confidence-based loss\n        confidence_loss = 0\n\n        # get the predicted classes\n        predicted_classes = class_preds.argmax(dim=1)\n        # and compare with the correct classes\n        is_correct = torch.eq(predicted_classes, labels)\n        is_correct_as_float = is_correct.float()\n        # calc the confidence loss\n        confidence_loss = self.loss_for_confidence(\n            confidence_preds, is_correct_as_float\n        )\n\n        # calc the total loss\n        total_loss = (\n            self.w_classes * class_loss + (1 - self.w_classes) * confidence_loss\n        )\n\n        return total_loss\n"
  },
  {
    "path": "NewsSentiment/losses/seq2seqloss.py",
    "content": "import torch\nimport torch.nn as nn\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\n\n\nclass SequenceLoss(nn.Module):\n    \"\"\"\n    Input to this loss are sequences, see models/multitargets/seq2seq.py\n    \"\"\"\n\n    def __init__(self, device, weight):\n        super(SequenceLoss, self).__init__()\n        self.device = device\n        self.weight = weight\n        self.actual_loss = nn.CrossEntropyLoss(\n            weight=self.weight, ignore_index=SentimentClasses.FILLUP_POLARITY_VALUE,\n        )\n\n        assert self.weight is None, \"not implemented, weight must be None\"\n\n    def forward(\n        self,\n        predictions: torch.Tensor,\n        true_classes: torch.Tensor,\n        true_target_mask: torch.Tensor,\n    ):\n        \"\"\"\n        :param predictions:         shape: batch, numclasses, seqlen\n        :param true_classes:        shape: batch, targets\n        :param true_target_mask:    shape: batch, targets, seqlen\n        :return:\n        \"\"\"\n        batch_size = predictions.shape[0]\n        num_classes = predictions.shape[1]\n        seq_len = predictions.shape[2]\n\n        # create true_sequence, shape: batch, seqlen\n        true_sequence = (\n            torch.ones([batch_size, seq_len], dtype=torch.int64, device=self.device)\n            * SentimentClasses.FILLUP_POLARITY_VALUE\n        )\n        # update individual scalars\n        for batch_index in range(batch_size):\n            for target_index in range(true_target_mask.shape[1]):\n                # get the sentiment class of this target in this batch\n                true_sentiment_class = true_classes[batch_index, target_index].item()\n                # if the true_sentiment_class is FILLUP_POLARITY_VALUE, ignore (no need\n                # to update because we initialized the whole true_sequence with\n                # FILLUP_POLARITY_VALUE\n                if true_sentiment_class == SentimentClasses.FILLUP_POLARITY_VALUE:\n                    continue\n\n                # if not FILLUP_POLARITY_VALUE, update the true_sequence\n                # iterate all tokens\n                for seq_index in range(seq_len):\n                    # determine if at the current token there is a target\n                    is_target = true_target_mask[\n                        batch_index, target_index, seq_index\n                    ].item()\n\n                    if is_target == 1:\n                        # there is a target\n                        # we should update the scalar in true_sequence at the\n                        # corresponding part (thereby disregarding the target dimension,\n                        # since all targets are merged into one dimension). ensure, that\n                        # -100 is still there (if there is another value, this means\n                        # that we have overlapping targets)\n                        prev_value = true_sequence[batch_index, seq_index].item()\n                        if prev_value == SentimentClasses.FILLUP_POLARITY_VALUE:\n                            # the previous value is FILLUP_POLARITY_VALUE, so there is\n                            # no target at this token already. so, we can update\n                            true_sequence[batch_index, seq_index] = true_sentiment_class\n                        else:\n                            # there is already a target class -> overlapping targets\n                            # this can happen for probably two reasons:\n                            # 1) there are actually different targets in the data that\n                            #    overlap\n                            # 2) we duplicated a target in FXDataset\n                            # either way, for now, if the value to be set is identical\n                            # to the one already present, we continue, otherwise throw\n                            # an error\n                            if prev_value == true_sentiment_class:\n                                pass\n                            else:\n                                raise ValueError(\n                                    f\"tried to update true_sequence[{batch_index},{seq_index}]={prev_value}\"\n                                )\n\n                    elif is_target == 0:\n                        # no target\n                        # since we initialized the true_sequence tensor with -100\n                        # scalars, there's not need to update the value for non-target\n                        # nodes\n                        pass\n                    else:\n                        raise ValueError(\n                            f\"true_target_mask must be either 0 or 1, is: {is_target}\"\n                        )\n\n        loss = self.actual_loss(predictions, true_sequence)\n        return loss\n"
  },
  {
    "path": "NewsSentiment/models/FXBaseModel.py",
    "content": "import os\nfrom copy import copy\n\nimport torch.nn as nn\n\nfrom abc import abstractmethod\n\nfrom transformers import (\n    XLNetModel,\n    AlbertModel,\n    BertModel,\n    RobertaModel,\n    PreTrainedModel,\n)\nfrom functools import wraps\n\nfrom NewsSentiment.download import Download\n\n\nclass FXBaseModel(PreTrainedModel):\n    def __init__(self, *args, **kwargs):\n        super().__init__(*args, **kwargs)\n\n    @staticmethod\n    @abstractmethod\n    def get_language_models():\n        return\n\n    @staticmethod\n    @abstractmethod\n    def get_input_field_ids():\n        return\n\n    def invoke_language_model(self, lm, input_ids, token_type_ids=None):\n        type_lm = type(lm)\n        if type_lm == XLNetModel:\n            last_hidden_state, mems, all_hidden_states = lm(\n                input_ids=input_ids, token_type_ids=token_type_ids,\n            )\n        elif type_lm in [AlbertModel, BertModel, RobertaModel]:\n            if token_type_ids is None:\n                last_hidden_state, pooler_output, hidden_states = lm(\n                    input_ids=input_ids,\n                )\n            else:\n                # last_hidden_state, pooler_output, hidden_states = lm(\n                #    input_ids=input_ids, token_type_ids=token_type_ids\n                # )\n                model_results = lm(input_ids=input_ids, token_type_ids=token_type_ids)\n                last_hidden_state = model_results.last_hidden_state\n                pooler_output = model_results.pooler_output\n                hidden_states = model_results.hidden_states\n        else:\n            raise NotImplementedError\n\n        return last_hidden_state\n\n\ndef provide_pretrained(version, pretrained_url):\n    \"\"\"\n    Usage:\n\n        @provide_pretrained(\"v1.0.0\", \"https://example.com/link/to/state_dict\")\n        class Example(nn.Module):\n            pass\n    \"\"\"\n\n    def decorator(model_class):\n        # The actual decorator to use before the class\n        wraps(model_class)\n\n        wrapper = __get_pretrained_wrapper_class(model_class)\n        wrapper._provide_pretrained_versions[version] = pretrained_url\n\n        return wrapper\n\n    return decorator\n\n\ndef default_pretrained(version):\n    \"\"\"\n    Set the version which should be used as the default version and will be used when running with --pretrained.\n\n    Usage:\n\n        @default_pretrained(\"v1.0.0\")\n        @provide_pretrained(\"v1.0.0\", \"https://example.com/link/to/state_dict\")\n        class Example(nn.Module):\n            pass\n    \"\"\"\n\n    def decorator(model_class):\n        # The actual decorator to use before the class\n        wraps(model_class)\n\n        wrapper = __get_pretrained_wrapper_class(model_class)\n        wrapper._provide_pretrained_default = version\n\n        return wrapper\n\n    return decorator\n\n\ndef model_includes_pretrained(model):\n    \"\"\"\n    Checks if a model-class includes the methods to load pretrained models.\n\n    Arguments:\n        model Model-class to check.\n\n    Returns:\n        True if it includes the functionality.\n    \"\"\"\n    return hasattr(model, \"has_pretrained_state_dict\") and hasattr(\n        model, \"get_pretrained_state_dict\"\n    )\n\n\n__pretrained_wrapper_classes = set()\n\n\ndef __get_pretrained_wrapper_class(base_class):\n    if base_class in __pretrained_wrapper_classes:\n        return base_class\n\n    class PretrainedWrapper(base_class):\n        _provide_pretrained_default = None\n        _provide_pretrained_versions = {}\n\n        def __init__(self, *args, **kwargs):\n            super().__init__(*args, **kwargs)\n\n        @classmethod\n        def has_pretrained_state_dict(cls, version=None):\n            version = version or cls._provide_pretrained_default\n            return version in cls._provide_pretrained_versions\n\n        @classmethod\n        def get_pretrained_state_dict(\n            cls, version=None, download_if_not_exists=True, **kwargs\n        ):\n            path = Download.model_path(cls, version)\n            if os.path.isfile(path):\n                if download_if_not_exists:\n                    Download.download(cls, version, False)\n                else:\n                    raise FileNotFoundError(\"State dict not found\")\n            return cls.load_state_dict(path, **kwargs)\n\n        @classmethod\n        def get_pretrained_versions(cls):\n            return copy(cls._provide_pretrained_versions)\n\n        @classmethod\n        def get_pretrained_source(cls, version=None):\n            return cls._provide_pretrained_versions[\n                version or cls._provide_pretrained_default\n            ]\n\n        @classmethod\n        def get_pretrained_default_version(cls):\n            return cls._provide_pretrained_default\n\n    __pretrained_wrapper_classes.add(PretrainedWrapper)\n    return PretrainedWrapper\n"
  },
  {
    "path": "NewsSentiment/models/FXEnsemble.py",
    "content": "from abc import ABC\nfrom argparse import Namespace\nfrom typing import List, Dict\nimport torch.nn as nn\nimport torch\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass FXEnsemble(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (\n            BERT_BASE_UNCASED,\n            ROBERTA_BASE,\n            XLNET_BASE_CASED,\n        )\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (ROBERTA_BASE, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (ROBERTA_BASE, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (XLNET_BASE_CASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (XLNET_BASE_CASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super().__init__()\n\n        # language models\n        self.bert = transformer_models[BERT_BASE_UNCASED]\n        self.roberta = transformer_models[ROBERTA_BASE]\n        self.xlnet = transformer_models[XLNET_BASE_CASED]\n        self.num_models = 3\n\n        # params\n        assert (\n            self.bert.config.hidden_size\n            == self.roberta.config.hidden_size\n            == self.xlnet.config.hidden_size\n        )\n        self.sequence_length = opt.max_seq_len\n        self.hidden_size = self.bert.config.hidden_size\n\n        # other neural network components\n        self.dropout = nn.Dropout(opt.dropout)\n        self.target_dependent_text_combiner = nn.Linear(\n            self.hidden_size * self.num_models, opt.polarities_dim\n        )\n\n    def _combine_text_out_with_target_mask(\n        self, batch_size, text_last_hidden_state, target_mask\n    ):\n        roberta_target_mask = target_mask.reshape((batch_size, 1, self.sequence_length))\n        roberta_target_dependent_text = torch.bmm(\n            roberta_target_mask, text_last_hidden_state\n        )\n        roberta_target_dependent_text = roberta_target_dependent_text.reshape(\n            (batch_size, self.hidden_size)\n        )\n        return roberta_target_dependent_text\n\n    def forward(self, inputs: List):\n        # alternatively, we could also use this\n        # FXDataset.get_all_inputs_for_model(input, self)\n        bert_text_ids = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        bert_target_mask = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n        roberta_text_ids = FXDataset.get_input_by_params(\n            inputs, ROBERTA_BASE, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        roberta_target_mask = FXDataset.get_input_by_params(\n            inputs, ROBERTA_BASE, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n        xlnet_text_ids = FXDataset.get_input_by_params(\n            inputs, XLNET_BASE_CASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        xlnet_target_mask = FXDataset.get_input_by_params(\n            inputs, XLNET_BASE_CASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n\n        # get variables\n        batch_size = bert_text_ids.shape[0]\n\n        # dev notes:\n        # batch_size = 4, sequence_length = 150, hidden_size = 768\n\n        # bert_text_out returns list with following elements\n        # 0: last_hidden_state (batch_size, sequence_length, hidden_size)\n        # 1: pooler_output (batch_size, hidden_size)\n        # 2: hidden_states (batch_size, sequence_length, hidden_size)\n        (\n            bert_text_last_hidden_state,\n            bert_text_pooler_output,\n            bert_text_hidden_states,\n        ) = self.bert(bert_text_ids)\n        # roberta_text_out returns same output as bert\n        (\n            roberta_text_last_hidden_state,\n            roberta_text_pooler_output,\n            roberta_text_hidden_states,\n        ) = self.roberta(roberta_text_ids)\n        # xlnet_text_out returns list with following elements\n        # 0: last_hidden_state (batch_size, sequence_length, hidden_size)\n        # does not exist - (1: mems, a list of length config.n_layers)\n        # 2: hidden_states (batch_size, sequence_length, hidden_size)\n        xlnet_text_last_hidden_state, xlnet_text_hidden_states = self.xlnet(\n            xlnet_text_ids\n        )\n\n        # incorporate target masks with (for now) last layer's states\n        # *_target_dependent_text_out will be of shape (batch_size, hidden_size)\n        bert_target_dependent_text_out = self._combine_text_out_with_target_mask(\n            batch_size, bert_text_last_hidden_state, bert_target_mask\n        )\n        roberta_target_dependent_text_out = self._combine_text_out_with_target_mask(\n            batch_size, roberta_text_last_hidden_state, roberta_target_mask\n        )\n        xlnet_target_dependent_text_out = self._combine_text_out_with_target_mask(\n            batch_size, xlnet_text_last_hidden_state, xlnet_target_mask\n        )\n\n        # cat outputs\n        cat_target_dependent_text_out = torch.cat(\n            [\n                bert_target_dependent_text_out,\n                roberta_target_dependent_text_out,\n                xlnet_target_dependent_text_out,\n            ],\n            dim=1,\n        )\n\n        # dropout for better learning\n        cat_target_dependent_text_out = self.dropout(cat_target_dependent_text_out)\n\n        # combine and get 3 dimensions\n        logits = self.target_dependent_text_combiner(cat_target_dependent_text_out)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/__init__.py",
    "content": ""
  },
  {
    "path": "NewsSentiment/models/ensemble.py",
    "content": "from argparse import Namespace\nfrom typing import List, Dict\nfrom NewsSentiment.consts import *\nimport torch.nn as nn\nimport torch\n\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\nfrom NewsSentiment.models.singletarget.td_bert import TD_BERT\n\n\nclass EnsembleTopA(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (get_default_lm(),)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            # tdbert\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            # hosseinia\n            (get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS),\n            # while we use text-then-target as bert input, we can use text targetmask and text knowledge source mask\n            # because it is identical to a hypothetical text-then-target target mask or text-then-target knowledge\n            # source mask (we would not highlight the target in the 2nd component in the corresponding mask)\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super().__init__()\n        from models.singletarget.stancedetectionpaper import StanceDetectionHosseinia\n\n        # submodels models\n        self.td_bert = TD_BERT(transformer_models, opt)\n        self.hosseinia = StanceDetectionHosseinia(transformer_models, opt)\n\n        # ensemble related\n        self.hosseinia_dense = nn.Linear(\n            self.hosseinia.language_model.config.hidden_size * 3 * 2 * 2,\n            self.hosseinia.language_model.config.hidden_size\n        )\n        self.ensemble_combiner = nn.Linear(\n            self.hosseinia.language_model.config.hidden_size * 2,\n            opt.polarities_dim\n        )\n\n    def forward(self, inputs: List):\n        # shape: batch, bertdim\n        td_bert_out = self.td_bert(inputs, is_return_ensemble_values=True)\n        # shape: batch, 3 * 2 * 2 * bertdim\n        hosseinia_out = self.hosseinia(inputs, is_return_ensemble_values=True)\n\n        # to ensure that both models have more or less similar impact on the result, apply a dense layer to hosseinia\n        # so that its new shape is: batch, bertdim\n        hosseinia_out = self.hosseinia_dense(hosseinia_out)\n\n        # combine\n        combined_out = torch.cat((td_bert_out, hosseinia_out), dim=1)\n\n        logits = self.ensemble_combiner(combined_out)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/ensembleb.py",
    "content": "from argparse import Namespace\nfrom typing import List, Dict\nfrom NewsSentiment.consts import *\nimport torch.nn as nn\nimport torch\n\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\nfrom NewsSentiment.models.singletarget.td_bert import TD_BERT\n\n\nclass EnsembleTopB(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (get_default_lm(),)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            # tdbert\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            # hosseinia\n            (get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS),\n            # while we use text-then-target as bert input, we can use text targetmask and text knowledge source mask\n            # because it is identical to a hypothetical text-then-target target mask or text-then-target knowledge\n            # source mask (we would not highlight the target in the 2nd component in the corresponding mask)\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super().__init__()\n        from models.singletarget.knowledgesourceshosseiniatdbert import KnowledgeSourcesHosseiniaTdBert\n\n        # submodels models\n        self.td_bert = TD_BERT(transformer_models, opt)\n        self.hosseiniatdbert = KnowledgeSourcesHosseiniaTdBert(transformer_models, opt)\n\n        # ensemble related\n        self.ensemble_combiner = nn.Linear(\n            self.hosseiniatdbert.language_model.config.hidden_size * 2,\n            opt.polarities_dim\n        )\n\n    def forward(self, inputs: List):\n        # shape: batch, bertdim\n        td_bert_out = self.td_bert(inputs, is_return_ensemble_values=True)\n        # shape: batch, 3 * 2 * 2 * bertdim\n        hosseinia_out = self.hosseiniatdbert(inputs, is_return_ensemble_values=True)\n\n        # combine\n        combined_out = torch.cat((td_bert_out, hosseinia_out), dim=1)\n\n        logits = self.ensemble_combiner(combined_out)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/multitargets/__init__.py",
    "content": ""
  },
  {
    "path": "NewsSentiment/models/multitargets/contrasting.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass Contrasting(FXBaseModel):\n    \"\"\"\n    This model returns a sequence that only contains the hidden states of those output\n    nodes that represent a word piece of the target phrase. All other hidden states are\n    set to 0. The length of the output sequence is opt.max_seq_len\n\n    From a conceptual perspective, TD-BERT is in some aspects similar (e.g., only the\n    output of target-phrase-related nodes is used), but in other aspects not similar or\n    it is not quite clear how the authors of TD-BERT implemented them. An email I sent\n    to them was not answered yet.\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(Contrasting, self).__init__()\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.dropout = nn.Dropout(opt.dropout)\n\n        self.contrasting_weight_dense = nn.Linear(opt.max_seq_len, opt.max_seq_len,)\n        self.dense = nn.Linear(\n            self.language_model.config.hidden_size, opt.polarities_dim\n        )\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_targets_mask = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n        assert text_bert_indices.shape[1] == 2, \"contrasting requires two targets\"\n\n        # target a\n        a_text_bert_indices = text_bert_indices[:, 0, :]\n        a_text_bert_indices_targets_mask = text_bert_indices_targets_mask[:, 0, :]\n\n        # target b\n        b_text_bert_indices = text_bert_indices[:, 1, :]\n        b_text_bert_indices_targets_mask = text_bert_indices_targets_mask[:, 1, :]\n\n        # bert\n        (\n            a_last_hidden_states,\n            a_pooler_output,\n            a_all_hidden_states,\n        ) = self.language_model(input_ids=a_text_bert_indices)\n        (\n            b_last_hidden_states,\n            b_pooler_output,\n            b_all_hidden_states,\n        ) = self.language_model(input_ids=b_text_bert_indices)\n        stacked_bert_outs_ab = torch.stack(\n            (a_last_hidden_states, b_last_hidden_states), dim=1\n        )\n        # stacked_bert_outs_ab\n        stacked_bert_outs_ab = self.dropout(stacked_bert_outs_ab)\n        # shape: batch, 2, seqlen, bertdim\n\n        # create weight\n        cross_weight = self.contrasting_weight_dense(text_bert_indices_targets_mask)\n        cross_weight = cross_weight.unsqueeze(3).repeat(\n            1, 1, 1, stacked_bert_outs_ab.shape[3]\n        )\n        cross_weight = self.dropout(cross_weight)\n        # shape: batch, 2, seqlen\n\n        weighted_stacked_bert_outs_ab = stacked_bert_outs_ab * cross_weight\n\n        # sum\n        weighted_stacked_bert_outs_ab = weighted_stacked_bert_outs_ab.sum(dim=2)\n\n        # dense\n        logits = self.dense(weighted_stacked_bert_outs_ab)\n\n        return logits, cross_weight\n"
  },
  {
    "path": "NewsSentiment/models/multitargets/random_multi.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass RandomMulti(FXBaseModel):\n    \"\"\"\n\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        \"\"\"\n        All architecture assumes that at least one model is used so we just require\n        bert here for compatibility.\n        :return:\n        \"\"\"\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(RandomMulti, self).__init__()\n        self.num_classes = opt.polarities_dim\n\n    def forward(self, inputs):\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        batch_size = text_bert_indices.shape[0]\n        num_targets = text_bert_indices.shape[1]\n\n        # get a random tensor\n        logits = torch.rand(batch_size, num_targets, self.num_classes)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/multitargets/seq2seq.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch.nn as nn\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass SeqTwoSeq(FXBaseModel):\n    \"\"\"\n    Outputs the class probabilities for each token. So, the output will be:\n    (batch, seqlen (150), classnum (3))\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (get_default_lm(),)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(SeqTwoSeq, self).__init__()\n        self.language_model = transformer_models[get_default_lm()]\n        self.dropout = nn.Dropout(opt.dropout)\n        # https://pytorch.org/docs/stable/nn.html#linear supports multi-dimensional\n        # input; only the last dimension has to be specified for Linear creation\n\n        self.attentionlike_dense = nn.Bilinear(\n            self.language_model.config.hidden_size,\n            FXDataset.NUM_MAX_TARGETS_PER_ITEM,\n            SentimentClasses.get_num_classes(),\n        )\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_targets_mask = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n        # prepare inputs\n        # for text only, we do not need target specific information, i.e., all text\n        # vectors are identical. also, bert, can\n        # only process one sequence of size max_seq_len (more specifically, a tensor\n        # of size batch_size x max_seq_ken). thus, we select only the first element from\n        # the second dimension (the dimensions are: batch, targets, hidden_states)\n        text_bert_indices = text_bert_indices[:, 0, :]\n        # apply bert\n        last_hidden_states = self.invoke_language_model(\n            lm=self.language_model,\n            input_ids=text_bert_indices,\n        )\n        # shape: batch, seqlen, bertdim\n        last_hidden_states = self.dropout(last_hidden_states)\n\n        # stack hidden states with target mask\n        # hidden:       batch,  seqlen, bertdim -> stay\n        # targetmask:   batch, target, seqlen, -> batch, seqlen, target\n        text_bert_indices_targets_mask = text_bert_indices_targets_mask.permute(\n            0, 2, 1\n        ).contiguous()\n\n        sequence_logits = self.attentionlike_dense(\n            last_hidden_states, text_bert_indices_targets_mask\n        )\n\n        return sequence_logits\n"
  },
  {
    "path": "NewsSentiment/models/multitargets/seq2seq_without_targetmask.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch.nn as nn\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass SeqTwoSeqWithoutTargetMask(FXBaseModel):\n    \"\"\"\n    Outputs the class probabilities for each token. So, the output will be:\n    (batch, seqlen (150), classnum (3))\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(SeqTwoSeqWithoutTargetMask, self).__init__()\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.dropout = nn.Dropout(opt.dropout)\n        # https://pytorch.org/docs/stable/nn.html#linear supports multi-dimensional\n        # input; only the last dimension has to be specified for Linear creation\n\n        self.attentionlike_dense = nn.Linear(\n            self.language_model.config.hidden_size,\n            SentimentClasses.get_num_classes(),\n        )\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n\n        # prepare inputs\n        # for text only, we do not need target specific information, i.e., all text\n        # vectors are identical. also, bert, can\n        # only process one sequence of size max_seq_len (more specifically, a tensor\n        # of size batch_size x max_seq_ken). thus, we select only the first element from\n        # the second dimension (the dimensions are: batch, targets, hidden_states)\n        text_bert_indices = text_bert_indices[:, 0, :]\n        # apply bert\n        last_hidden_states, pooler_output, all_hidden_states = self.language_model(\n            input_ids=text_bert_indices\n        )\n        # shape: batch, seqlen, bertdim\n        last_hidden_states = self.dropout(last_hidden_states)\n\n        sequence_logits = self.attentionlike_dense(last_hidden_states)\n\n        return sequence_logits\n"
  },
  {
    "path": "NewsSentiment/models/multitargets/tdbertlikemultitarget.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass TDBertLikeMultiTarget(FXBaseModel):\n    \"\"\"\n    This model returns a sequence that only contains the hidden states of those output\n    nodes that represent a word piece of the target phrase. All other hidden states are\n    set to 0. The length of the output sequence is opt.max_seq_len\n\n    From a conceptual perspective, TD-BERT is in some aspects similar (e.g., only the\n    output of target-phrase-related nodes is used), but in other aspects not similar or\n    it is not quite clear how the authors of TD-BERT implemented them. An email I sent\n    to them was not answered yet.\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            # (\n            #     BERT_BASE_UNCASED,\n            #     FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES,\n            # ),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(TDBertLikeMultiTarget, self).__init__()\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.dropout = nn.Dropout(opt.dropout)\n        self.dense = nn.Linear(\n            self.language_model.config.hidden_size, opt.polarities_dim\n        )\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_targets_mask = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n        # text_bert_indices_nrc_emolex = FXDataset.get_input_by_params(\n        #     inputs,\n        #     BERT_BASE_UNCASED,\n        #     FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES,\n        # )\n        # prepare inputs\n        # for text only, we do not need target specific information, i.e., all text\n        # vectors are identical. also, bert, can\n        # only process one sequence of size max_seq_len (more specifically, a tensor\n        # of size batch_size x max_seq_ken). thus, we select only the first element from\n        # the second dimension (the dimensions are: batch, targets, hidden_states)\n        text_bert_indices = text_bert_indices[:, 0, :]\n        # apply bert\n        last_hidden_states, pooler_output, all_hidden_states = self.language_model(\n            input_ids=text_bert_indices\n        )\n        # element-wise multiplication with target mask\n        # align the dimensions of the tensors\n        # last_hidden_states.shape = 4,150,768; should be 4,5,150,768\n        # insert a new singleton dimension after the first dimension\n        # new shape: 4,1,150,768\n        last_hidden_states = last_hidden_states.unsqueeze(1)\n        # repeat k times along the new 2nd dimension, where k is the target size\n        last_hidden_states = last_hidden_states.repeat(\n            1, text_bert_indices_targets_mask.shape[1], 1, 1\n        )\n        # text_bert_indices_targets_mask.shape = 4,5,150; should be 4,5,150,768\n        # insert singleton simension after the three already existing dimensions\n        text_bert_indices_targets_mask = text_bert_indices_targets_mask.unsqueeze(3)\n        text_bert_indices_targets_mask = text_bert_indices_targets_mask.repeat(\n            1, 1, 1, last_hidden_states.shape[3]\n        )\n\n        last_hidden_states_only_targets = (\n            last_hidden_states * text_bert_indices_targets_mask\n        )\n\n        # similar to TD-BERT, perform max pooling TODO not implemented yet, instead:\n        # for now, retrieve only the values of the target's output tokens and then\n        # calculate the mean:\n        # (batchsize, targetsize, 150, 768) -> (batchsize, targetsize, 768)\n        # get the positions of target nodes. note that we cannot simply take the mean\n        # as it would divide by the number of the sequence length, whereas the effective\n        # length is only of size k, where k is the number of non-zero scalars in the\n        # input mask (since we are only interested in those values)\n        last_hidden_states_aggregated_per_target = last_hidden_states_only_targets.sum(\n            dim=2\n        )\n        # get the sum for each (batch, hidden states) (sum over the sequence length\n        # dim)\n        denominator_for_mean = text_bert_indices_targets_mask.sum(dim=2)\n        # divide for each (batch, hidden states) by the denominator to get the mean\n        last_hidden_states_aggregated_per_target = (\n            last_hidden_states_aggregated_per_target / denominator_for_mean\n        )\n        # dropout before dense layer, as in most other tsc models\n        last_hidden_states_aggregated_per_target = self.dropout(\n            last_hidden_states_aggregated_per_target\n        )\n        # dense layer\n        logits = self.dense(last_hidden_states_aggregated_per_target)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/multitargets/tdbertlikemultitarget_dense.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass TDBertLikeMultiTargetDense(FXBaseModel):\n    \"\"\"\n    This model returns a sequence that only contains the hidden states of those output\n    nodes that represent a word piece of the target phrase. All other hidden states are\n    set to 0. The length of the output sequence is opt.max_seq_len\n\n    From a conceptual perspective, TD-BERT is in some aspects similar (e.g., only the\n    output of target-phrase-related nodes is used), but in other aspects not similar or\n    it is not quite clear how the authors of TD-BERT implemented them. An email I sent\n    to them was not answered yet.\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(TDBertLikeMultiTargetDense, self).__init__()\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.dropout = nn.Dropout(opt.dropout)\n        self.dense = nn.Bilinear(\n            self.language_model.config.hidden_size,\n            FXDataset.NUM_MAX_TARGETS_PER_ITEM,\n            FXDataset.NUM_MAX_TARGETS_PER_ITEM,\n        )\n        self.dense2 = nn.Linear(opt.max_seq_len, opt.polarities_dim)\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_targets_mask = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n        # prepare inputs\n        # for text only, we do not need target specific information, i.e., all text\n        # vectors are identical. also, bert, can\n        # only process one sequence of size max_seq_len (more specifically, a tensor\n        # of size batch_size x max_seq_ken). thus, we select only the first element from\n        # the second dimension (the dimensions are: batch, targets, hidden_states)\n        text_bert_indices = text_bert_indices[:, 0, :]\n        # apply bert\n        last_hidden_states, pooler_output, all_hidden_states = self.language_model(\n            input_ids=text_bert_indices\n        )\n\n        # dropout\n        last_hidden_states = self.dropout(last_hidden_states)\n\n        # shapes:\n        # last_hidden_states:                   batch, seqlen, bertdim\n        # text_bert_indices_targets_mask:       batch, target, seqlen\n        # new text_bert_indices_targets_mask:   batch, seqlen, target\n        text_bert_indices_targets_mask = text_bert_indices_targets_mask.permute(\n            0, 2, 1\n        ).clone()\n\n        logits = self.dense(last_hidden_states, text_bert_indices_targets_mask)\n        logits = logits.permute(0, 2, 1)\n        logits = self.dense2(logits)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/__init__.py",
    "content": ""
  },
  {
    "path": "NewsSentiment/models/singletarget/aen.py",
    "content": "# adapted from absa-pytorch\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\n\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.layers.attention import Attention\nfrom NewsSentiment.layers.point_wise_feed_forward import PositionwiseFeedForward\nfrom NewsSentiment.layers.squeeze_embedding import SqueezeEmbedding\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.fxlogger import get_logger\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\nlogger = get_logger()\n\n\nclass AEN_Base(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(AEN_Base, self).__init__()\n        logger.info(\"creating AEN_Base\")\n        self.device = opt.device\n\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.name = \"aen_bert\"\n        self.lm_representation = \"last\"\n        embed_dim = self.language_model.config.hidden_size\n\n        self.squeeze_embedding = SqueezeEmbedding()\n        self.dropout = nn.Dropout(opt.dropout)\n        hidden_dim = embed_dim  # or should this be 300, as mentioned in the paper\n\n        self.attn_k = Attention(\n            embed_dim,\n            out_dim=hidden_dim,\n            n_head=8,\n            score_function=\"mlp\",\n            dropout=opt.dropout,\n        )\n        self.attn_q = Attention(\n            embed_dim,\n            out_dim=hidden_dim,\n            n_head=8,\n            score_function=\"mlp\",\n            dropout=opt.dropout,\n        )\n        self.ffn_c = PositionwiseFeedForward(hidden_dim, dropout=opt.dropout)\n        self.ffn_t = PositionwiseFeedForward(hidden_dim, dropout=opt.dropout)\n\n        self.attn_s1 = Attention(\n            hidden_dim, n_head=8, score_function=\"mlp\", dropout=opt.dropout\n        )\n\n        self.dense = nn.Linear(hidden_dim * 3, opt.polarities_dim)\n\n    def apply_lm(self, _input, _input_attention=None):\n        if self.name in [\"aen_bert\", \"aen_roberta\"]:\n            last_hidden, _, all_hidden = self.language_model(\n                input_ids=_input, attention_mask=_input_attention\n            )\n        elif self.name == \"aen_distilbert\":\n            last_hidden, all_hidden = self.language_model(\n                input_ids=_input, attention_mask=_input_attention\n            )\n        else:\n            raise Exception(\"unknown model name\")\n\n        if self.lm_representation == \"last\":\n            return last_hidden\n        elif self.lm_representation == \"sum_last_four\":\n            last_four = all_hidden[-4:]  # list of four, each has shape: 16, 80, 768\n            last_four_stacked = torch.stack(last_four)  # shape: 4, 16, 80, 768\n            sum_last_four = torch.sum(last_four_stacked, dim=0)\n            return sum_last_four\n        elif self.lm_representation == \"mean_last_four\":\n            last_four = all_hidden[-4:]  # list of four, each has shape: 16, 80, 768\n            last_four_stacked = torch.stack(last_four)  # shape: 4, 16, 80, 768\n            mean_last_four = torch.mean(last_four_stacked, dim=0)\n            return mean_last_four\n        elif self.lm_representation == \"sum_last_two\":\n            last_two = all_hidden[-2:]\n            last_two_stacked = torch.stack(last_two)\n            sum_last_two = torch.sum(last_two_stacked, dim=0)\n            return sum_last_two\n        elif self.lm_representation == \"mean_last_two\":\n            last_two = all_hidden[-2:]\n            last_two_stacked = torch.stack(last_two)\n            mean_last_two = torch.mean(last_two_stacked, dim=0)\n            return mean_last_two\n        elif self.lm_representation == \"sum_all\":\n            all_stacked = torch.stack(all_hidden)\n            sum_all = torch.sum(all_stacked, dim=0)\n            return sum_all\n        elif self.lm_representation == \"mean_all\":\n            all_stacked = torch.stack(all_hidden)\n            mean_all = torch.mean(all_stacked, dim=0)\n            return mean_all\n\n    def forward(self, inputs):\n        context = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        target = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n        context_len = torch.sum(context != 0, dim=-1)\n        target_len = torch.sum(target != 0, dim=-1)\n\n        context = self.squeeze_embedding(context, context_len)\n        # context_attention = self.squeeze_embedding(context_attention, context_len)\n        context = self.apply_lm(context)\n        context = self.dropout(context)\n\n        target = self.squeeze_embedding(target, target_len)\n        # target_attention = self.squeeze_embedding(target_attention, target_len)\n        target = self.apply_lm(target)\n        target = self.dropout(target)\n\n        hc, _ = self.attn_k(context, context)\n        hc = self.ffn_c(hc)\n\n        ht, _ = self.attn_q(context, target)\n        ht = self.ffn_t(ht)\n\n        s1, _ = self.attn_s1(hc, ht)\n\n        context_len = torch.tensor(context_len, dtype=torch.float).to(self.device)\n        target_len = torch.tensor(target_len, dtype=torch.float).to(self.device)\n\n        hc_mean = torch.div(\n            torch.sum(hc, dim=1), context_len.view(context_len.size(0), 1)\n        )\n        ht_mean = torch.div(\n            torch.sum(ht, dim=1), target_len.view(target_len.size(0), 1)\n        )\n        s1_mean = torch.div(\n            torch.sum(s1, dim=1), context_len.view(context_len.size(0), 1)\n        )\n\n        x = torch.cat((hc_mean, s1_mean, ht_mean), dim=-1)\n        out = self.dense(x)\n\n        return out\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/grutscsingle.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\nfrom transformers import PretrainedConfig\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset, FXEasyTokenizer\nfrom NewsSentiment.models.FXBaseModel import (\n    FXBaseModel,\n    provide_pretrained,\n    default_pretrained,\n)\n\n\n@default_pretrained(\"v1.0.0\")\n@provide_pretrained(\n    \"v1.0.0\", \"https://github.com/fhamborg/NewsMTSC/releases/download/v1.0.0/grutsc\"\n)\nclass GRUTSCSingle(FXBaseModel):\n    \"\"\"\n    Inspired from https://arxiv.org/pdf/2006.00052.pdf\n    Differences:\n    - instead of question (\"Is the ACLU good for USA?\") then text (1 or more sentences),\n      we use text then target (and no question, similar to BERT-SPC)\n    - no vader\n    - additionally we can flexibly use any knowledge source as well as multiple\n    - we have one large matrix for all concatenated knowledge source embeddings, whereas\n      in the original paper they use individual, smaller matrices for each knowledge\n      source embedding\n    - target mask (mostly useful for BERT)\n    - fine-tuning LM enabled\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (get_default_lm(),)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (\n                get_default_lm(),\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n            ),\n            # while we use text-then-target as bert input, we can use text targetmask\n            # and text knowledge source mask because it is identical to a hypothetical\n            # text-then-target target mask or text-then-target knowledge source mask\n            # (we would not highlight the target in the 2nd component in the\n            # corresponding mask)\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (\n                get_default_lm(),\n                FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES,\n            ),\n        ]\n\n    def __init__(\n        self, transformer_models: Dict, opt: Namespace, config: PretrainedConfig\n    ):\n        super().__init__(config)\n        self.language_model = transformer_models[get_default_lm()]\n        self.ks_embeddings_dense = nn.Linear(\n            FXEasyTokenizer.NUM_CATEGORIES_OF_SELECTED_KNOWLEDGE_SOURCES,\n            self.language_model.config.hidden_size,\n        )\n        if get_default_lm() == BERT_BASE_UNCASED:\n            self.is_use_targetmask = True\n        else:\n            self.is_use_targetmask = False\n\n        num_input_embeddings = 2\n        if self.is_use_targetmask:\n            num_input_embeddings = 3\n\n        self.gru = nn.GRU(\n            self.language_model.config.hidden_size * num_input_embeddings,\n            self.language_model.config.hidden_size * num_input_embeddings,\n            bidirectional=True,\n            batch_first=True,\n        )\n        self.dropout = nn.Dropout(opt.dropout)\n        num_output_dim = opt.polarities_dim\n        if opt.is_return_confidence:\n            num_output_dim += 1\n\n        self.dense = nn.Linear(\n            # 3 inputs (original last gru out, mean, max), 2 inputs to gru (bert and\n            # knowledge embedding), 2 (because bidirectional gru)\n            self.language_model.config.hidden_size * 3 * num_input_embeddings * 2,\n            num_output_dim,\n        )\n\n    def forward(self, inputs, is_return_ensemble_values: bool = False):\n        # get inputs\n        text_target_bert_indices = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_target_bert_segments_ids = FXDataset.get_input_by_params(\n            inputs,\n            get_default_lm(),\n            FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n        )\n        text_bert_indices_target_mask = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n        text_bert_indices_selected_knowledge_sources = FXDataset.get_input_by_params(\n            inputs,\n            get_default_lm(),\n            FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_SELECTED_KNOWLEDGE_SOURCES,\n        )\n\n        # apply bert\n        last_hidden_states = self.invoke_language_model(\n            lm=self.language_model,\n            input_ids=text_target_bert_indices,\n            token_type_ids=text_target_bert_segments_ids,\n        )\n        # shape: batch, seqlen, hiddendim\n\n        # apply knowledge embedding\n        knowledge_embedded = self.ks_embeddings_dense(\n            text_bert_indices_selected_knowledge_sources.float()\n        )\n        # shape: batch, seqlen, hiddendim\n\n        if self.is_use_targetmask:\n            # repeat\n            target_mask = text_bert_indices_target_mask.unsqueeze(dim=2).repeat(\n                1, 1, knowledge_embedded.shape[2]\n            )\n            # shape: batch, seqlen, hiddendim\n\n            # concat (called x_t in paper)\n            bert_and_knowledge = torch.cat(\n                (last_hidden_states, knowledge_embedded, target_mask), dim=2\n            )\n            # batch x seq x bert+knowledge+targetmask\n        else:\n            # concat (called x_t in paper)\n            bert_and_knowledge = torch.cat(\n                (last_hidden_states, knowledge_embedded), dim=2\n            )\n            # batch x seq x bert+knowledge\n\n        # apply gru (result called z_t in paper)\n        gru_all_hidden, gru_last_hidden = self.gru(\n            bert_and_knowledge,\n            torch.zeros(\n                2,\n                bert_and_knowledge.shape[0],\n                self.language_model.config.hidden_size * 2,\n            ).to(self.device),\n        )\n        # all hidden shape: batch x seq x 4*hidden (contains hidden states for each\n        # part of the input seq)\n        # last hidden shap: numdir x batch x 2*hidden (contains hidden states for last\n        # part of input seq)\n\n        # gru_last_hidden_own = gru_all_hidden[:,-1:,]\n        # get both directions\n        gru_last_hidden_dir0 = gru_last_hidden[0, :, :]\n        gru_last_hidden_dir1 = gru_last_hidden[1, :, :]\n        # shape each: batch x 2*hidden\n        gru_last_hidden_stacked = torch.cat(\n            (gru_last_hidden_dir0, gru_last_hidden_dir1), dim=1\n        )\n        # batch x 4*hidden\n\n        # pooling\n        # according to original paper: \"max-pooling returns a vector with maximum\n        # weights across all hidden states of input tokens for each dimension. in this\n        # way, the input tokens with higher weights will be engaged for stance\n        # prediction.\"\n        gru_avg = torch.mean(gru_all_hidden, dim=1)\n        gru_max, _ = torch.max(gru_all_hidden, dim=1)\n\n        # concat (called \"u\" in original paper)\n        gru_complete_concatted = torch.cat(\n            (gru_last_hidden_stacked, gru_avg, gru_max), dim=1\n        )\n\n        if is_return_ensemble_values:\n            return gru_complete_concatted\n        else:\n            # dense\n            logits = self.dense(gru_complete_concatted)\n\n            return logits\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/lcf.py",
    "content": "# adapted from https://github.com/yangheng95/LCF-ABSA\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\n# from transformers.modeling_bert import BertPooler, BertSelfAttention\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass GlobalContext(nn.Module):\n    def __init__(self, global_context_seqs_per_doc):\n        super(GlobalContext, self).__init__()\n        self.global_context_seqs_per_doc = global_context_seqs_per_doc\n\n    def forward(self, inputs):\n        pass\n\n\nclass SelfAttention(nn.Module):\n    def __init__(self, config, opt):\n        super(SelfAttention, self).__init__()\n        self.opt = opt\n        self.config = config\n        self.SA = None # BertSelfAttention(config)\n        self.tanh = torch.nn.Tanh()\n\n    def forward(self, inputs):\n        zero_tensor = torch.tensor(\n            np.zeros((inputs.size(0), 1, 1, self.opt.max_seq_len), dtype=np.float32),\n            dtype=torch.float32,\n        ).to(self.opt.device)\n        SA_out = self.SA(inputs, zero_tensor)\n        return self.tanh(SA_out[0])\n\n\nclass LCF_BERT(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (\n                BERT_BASE_UNCASED,\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n            ),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(LCF_BERT, self).__init__()\n\n        bert = transformer_models[BERT_BASE_UNCASED]\n        self.bert_spc = bert\n        self.opt = opt\n\n        # self.bert_local = copy.deepcopy(bert)  # Uncomment the line to use dual Bert\n        self.bert_local = (\n            bert  # Default to use single Bert and reduce memory requirements\n        )\n        self.dropout = nn.Dropout(self.opt.dropout)\n        # while the paper describes 3 self attentions, the original implementation by the authors\n        # uses only one. we stick with the original implementation.\n        # answer by the author: the version found PyTorch-ABSA repository and below is better than what was\n        # described in the paper (cf. https://github.com/yangheng95/LC-ABSA/issues/10#issuecomment-670301603)\n        # self.bert_local_SA = SelfAttention(bert.config, self.opt)\n        # self.bert_global_SA = SelfAttention(bert.config, self.opt)\n        self.linear_double = nn.Linear(\n            bert.config.hidden_size * 2, bert.config.hidden_size\n        )\n        self.bert_SA = SelfAttention(bert.config, self.opt)\n        self.linear_single = nn.Linear(bert.config.hidden_size, bert.config.hidden_size)\n        self.bert_pooler = None # BertPooler(bert.config)\n\n        self.dense = nn.Linear(bert.config.hidden_size, self.opt.polarities_dim)\n\n    def feature_dynamic_mask(self, text_local_indices, aspect_indices):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        mask_len = self.opt.SRD\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            asp_len = np.count_nonzero(asps[asp_i]) - 2\n            try:\n                asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n            except:\n                continue\n            if asp_begin >= mask_len:\n                mask_begin = asp_begin - mask_len\n            else:\n                mask_begin = 0\n            for i in range(mask_begin):\n                masked_text_raw_indices[text_i][i] = np.zeros(\n                    (self.bert_local.config.hidden_size), dtype=np.float\n                )\n            for j in range(asp_begin + asp_len + mask_len, self.opt.max_seq_len):\n                masked_text_raw_indices[text_i][j] = np.zeros(\n                    (self.bert_local.config.hidden_size), dtype=np.float\n                )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def feature_dynamic_weighted(self, text_local_indices, aspect_indices):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            asp_len = np.count_nonzero(asps[asp_i]) - 2\n            try:\n                asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                asp_avg_index = (asp_begin * 2 + asp_len) / 2\n            except:\n                continue\n            distances = np.zeros(np.count_nonzero(texts[text_i]), dtype=np.float32)\n            for i in range(1, np.count_nonzero(texts[text_i]) - 1):\n                if abs(i - asp_avg_index) + asp_len / 2 > self.opt.SRD:\n                    distances[i] = 1 - (\n                        abs(i - asp_avg_index) + asp_len / 2 - self.opt.SRD\n                    ) / np.count_nonzero(texts[text_i])\n                else:\n                    distances[i] = 1\n            for i in range(len(distances)):\n                masked_text_raw_indices[text_i][i] = (\n                    masked_text_raw_indices[text_i][i] * distances[i]\n                )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def forward(self, inputs):\n        text_target_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS,\n        )\n\n        text_target_bert_segments_ids = FXDataset.get_input_by_params(\n            inputs,\n            BERT_BASE_UNCASED,\n            FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n        )\n        text_local_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        aspect_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n\n        # apply bert and dropout\n        bert_spc_out, _, _ = self.bert_spc(\n            text_target_bert_indices, text_target_bert_segments_ids\n        )\n        bert_spc_out = self.dropout(bert_spc_out)\n\n        bert_local_out, _, _ = self.bert_local(text_local_indices)\n        bert_local_out = self.dropout(bert_local_out)\n\n        if self.opt.local_context_focus == \"cdm\":\n            masked_local_text_vec = self.feature_dynamic_mask(\n                text_local_indices, aspect_indices\n            )\n            bert_local_out = torch.mul(bert_local_out, masked_local_text_vec)\n        elif self.opt.local_context_focus == \"cdw\":\n            weighted_text_local_features = self.feature_dynamic_weighted(\n                text_local_indices, aspect_indices\n            )\n            bert_local_out = torch.mul(bert_local_out, weighted_text_local_features)\n\n        # attention\n        # bert_local_out = self.bert_local_SA(bert_local_out)\n        # bert_spc_out = self.bert_global_SA(bert_spc_out)\n\n        # cat\n        out_cat = torch.cat((bert_local_out, bert_spc_out), dim=-1)\n\n        # \"interactive learning layer\"\n        mean_pool = self.linear_double(out_cat)\n        self_attention_out = self.bert_SA(mean_pool)\n        pooled_out = self.bert_pooler(self_attention_out)\n\n        dense_out = self.dense(pooled_out)\n        return dense_out\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/lcf2.py",
    "content": "# adapted from https://github.com/yangheng95/LC-ABSA/blob/c945a94e0f86116c5578245aa9ad36c46c7b9c4a/models/lc_apc/lcf_bert.py\n# according to\nimport copy\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\n# from transformers.modeling_bert import BertPooler, BertSelfAttention\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.layers.attention import FXBertSelfAttention\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass GlobalContext(nn.Module):\n    def __init__(self, global_context_seqs_per_doc):\n        super(GlobalContext, self).__init__()\n        self.global_context_seqs_per_doc = global_context_seqs_per_doc\n\n    def forward(self, inputs):\n        pass\n\n\nclass SelfAttention(nn.Module):\n    def __init__(self, config, opt):\n        super(SelfAttention, self).__init__()\n        self.opt = opt\n        self.config = config\n        self.SA = FXBertSelfAttention(\n            hidden_size=config.hidden_size,\n            num_attention_heads=config.num_attention_heads,\n            attention_probs_dropout_prob=0.1,\n        )\n        self.tanh = torch.nn.Tanh()\n\n    def forward(self, inputs):\n        zero_tensor = torch.tensor(\n            np.zeros((inputs.size(0), 1, 1, self.opt.max_seq_len), dtype=np.float32),\n            dtype=torch.float32,\n        ).to(self.opt.device)\n        SA_out = self.SA(inputs, zero_tensor)\n        return self.tanh(SA_out[0])\n\n\nclass LCF_BERT2Dual(FXBaseModel):\n    \"\"\"\n    While lcf.py:LCF_BERT is the implementation as implemented in PyTorch-ABSA repository, this implementation here\n    (LCF_BERT2Dual) is following the implementation as in the author's repository, which according to\n    https://github.com/yangheng95/LC-ABSA/issues/10#issuecomment-670301603 has seen some more improvements compared to\n    the version from PyTorch-ABSA\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (get_default_lm(),)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (\n                get_default_lm(),\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n            ),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(LCF_BERT2Dual, self).__init__()\n\n        bert = transformer_models[get_default_lm()]\n\n        self.bert4global = bert\n        # note that we use a second bert here, which should slightly improve performance\n        # cf. https://github.com/yangheng95/LC-ABSA/#tips\n        # self.bert4local = copy.deepcopy(bert)\n        # we can't do this on scc because even for batch size = only 16 we run out of\n        # memory. because of that, we use the same bert for both local and global\n        # (just as in lcf.py)\n        self.bert4local = bert\n        self.opt = opt\n        self.dropout = nn.Dropout(self.opt.dropout)\n        self.bert_SA = SelfAttention(bert.config, self.opt)\n        self.linear2 = nn.Linear(bert.config.hidden_size * 2, bert.config.hidden_size)\n        # self.linear3 = nn.Linear(bert.config.hidden_size * 3, bert.config.hidden_size)\n        self.bert_pooler = None # BertPooler(bert.config)\n        self.dense = nn.Linear(bert.config.hidden_size, self.opt.polarities_dim)\n\n    def feature_dynamic_mask(self, text_local_indices, aspect_indices):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        mask_len = self.opt.SRD\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert4local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            asp_len = np.count_nonzero(asps[asp_i]) - 2\n            try:\n                asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n            except:\n                continue\n            if asp_begin >= mask_len:\n                mask_begin = asp_begin - mask_len\n            else:\n                mask_begin = 0\n            for i in range(mask_begin):\n                masked_text_raw_indices[text_i][i] = np.zeros(\n                    (self.bert4local.config.hidden_size), dtype=np.float\n                )\n            for j in range(asp_begin + asp_len + mask_len, self.opt.max_seq_len):\n                masked_text_raw_indices[text_i][j] = np.zeros(\n                    (self.bert4local.config.hidden_size), dtype=np.float\n                )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def feature_dynamic_weighted(self, text_local_indices, aspect_indices):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert4local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            asp_len = np.count_nonzero(asps[asp_i]) - 2\n            try:\n                asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                asp_avg_index = (asp_begin * 2 + asp_len) / 2\n            except:\n                continue\n            distances = np.zeros(np.count_nonzero(texts[text_i]), dtype=np.float32)\n            for i in range(1, np.count_nonzero(texts[text_i]) - 1):\n                if abs(i - asp_avg_index) + asp_len / 2 > self.opt.SRD:\n                    distances[i] = 1 - (\n                        abs(i - asp_avg_index) + asp_len / 2 - self.opt.SRD\n                    ) / np.count_nonzero(texts[text_i])\n                else:\n                    distances[i] = 1\n            for i in range(len(distances)):\n                masked_text_raw_indices[text_i][i] = (\n                    masked_text_raw_indices[text_i][i] * distances[i]\n                )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def forward(self, inputs):\n        text_target_bert_indices = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS,\n        )\n        text_target_bert_segments_ids = FXDataset.get_input_by_params(\n            inputs,\n            get_default_lm(),\n            FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n        )\n        text_local_indices = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        aspect_indices = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n\n        # bert\n        global_context_features = self.invoke_language_model(\n            self.bert4global,\n            input_ids=text_target_bert_indices,\n            token_type_ids=text_target_bert_segments_ids,\n        )\n        local_context_features = self.invoke_language_model(\n            self.bert4local, text_local_indices\n        )\n\n        # mask\n        if self.opt.local_context_focus == \"cdm\":\n            lcf_matrix = self.feature_dynamic_mask(text_local_indices, aspect_indices)\n        elif self.opt.local_context_focus == \"cdw\":\n            lcf_matrix = self.feature_dynamic_weighted(\n                text_local_indices, aspect_indices\n            )\n\n        # LCF layer\n        lcf_features = torch.mul(local_context_features, lcf_matrix)\n        lcf_features = self.bert_SA(lcf_features)\n\n        cat_features = torch.cat((lcf_features, global_context_features), dim=-1)\n        cat_features = self.linear2(cat_features)\n        cat_features = self.dropout(cat_features)\n\n        pooled_out = self.bert_pooler(cat_features)\n        dense_out = self.dense(pooled_out)\n\n        return dense_out\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/lcfs.py",
    "content": "# adapted from https://github.com/yangheng95/LCF-ABSA and\n# https://github.com/StevePhan101/LCFS-BERT/\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\n# from transformers.modeling_bert import BertPooler, BertSelfAttention\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass PointwiseFeedForward(nn.Module):\n    \"\"\"\n    A two-feed-forward-layer module\n    \"\"\"\n\n    def __init__(self, d_hid, d_inner_hid=None, d_out=None, dropout=0):\n        super(PointwiseFeedForward, self).__init__()\n        if d_inner_hid is None:\n            d_inner_hid = d_hid\n        if d_out is None:\n            d_out = d_inner_hid\n        self.w_1 = nn.Conv1d(d_hid, d_inner_hid, 1)  # position-wise\n        self.w_2 = nn.Conv1d(d_inner_hid, d_out, 1)  # position-wise\n        self.dropout = nn.Dropout(dropout)\n        self.relu = nn.ReLU()\n\n    def forward(self, x):\n        output = self.relu(self.w_1(x.transpose(1, 2)))\n        output = self.w_2(output).transpose(2, 1)\n        output = self.dropout(output)\n        return output\n\n\nclass SelfAttention(nn.Module):\n    def __init__(self, config, opt):\n        super(SelfAttention, self).__init__()\n        self.opt = opt\n        self.config = config\n        self.SA = None # BertSelfAttention(config)\n        self.tanh = torch.nn.Tanh()\n\n    def forward(self, inputs):\n        zero_tensor = torch.tensor(\n            np.zeros((inputs.size(0), 1, 1, self.opt.max_seq_len), dtype=np.float32),\n            dtype=torch.float32,\n        ).to(self.opt.device)\n        SA_out = self.SA(inputs, zero_tensor)\n        return self.tanh(SA_out[0])\n\n\nclass LCFS_BERT(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (\n                BERT_BASE_UNCASED,\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n            ),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (BERT_BASE_UNCASED, FIELD_SYNTAX_HOP_DISTANCE_TO_TARGET),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(LCFS_BERT, self).__init__()\n\n        bert = transformer_models[BERT_BASE_UNCASED]\n        self.bert_spc = bert\n        self.opt = opt\n\n        # self.bert_local = copy.deepcopy(bert)  # Uncomment the line to use dual Bert\n        self.bert_local = (\n            bert  # Default to use single Bert and reduce memory requirements\n        )\n        self.dropout = nn.Dropout(self.opt.dropout)\n        self.bert_SA = SelfAttention(bert.config, self.opt)\n\n        # self.linear_double = nn.Linear(\n        #    bert.config.hidden_size * 2, bert.config.hidden_size\n        # )\n        self.mean_pooling_double = PointwiseFeedForward(\n            bert.config.hidden_size * 2,\n            bert.config.hidden_size,\n            bert.config.hidden_size,\n        )\n        self.linear_single = nn.Linear(bert.config.hidden_size, bert.config.hidden_size)\n        self.bert_pooler = None # BertPooler(bert.config)\n\n        self.dense = nn.Linear(bert.config.hidden_size, self.opt.polarities_dim)\n\n    def feature_dynamic_mask(self, text_local_indices, aspect_indices, distances_input):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        if distances_input is not None:\n            distances_input = distances_input.cpu().numpy()\n        mask_len = self.opt.SRD\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            if distances_input is None:\n                # this should never be reached\n                asp_len = np.count_nonzero(asps[asp_i]) - 2\n                try:\n                    asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                except:\n                    continue\n                if asp_begin >= mask_len:\n                    mask_begin = asp_begin - mask_len\n                else:\n                    mask_begin = 0\n                for i in range(mask_begin):\n                    masked_text_raw_indices[text_i][i] = np.zeros(\n                        (self.bert_local.config.hidden_size), dtype=np.float\n                    )\n                for j in range(asp_begin + asp_len + mask_len, self.opt.max_seq_len):\n                    masked_text_raw_indices[text_i][j] = np.zeros(\n                        (self.bert_local.config.hidden_size), dtype=np.float\n                    )\n                else:\n                    distances_i = distances_input[text_i]\n                for i, dist in enumerate(distances_i):\n                    # iterate the distances and set the mask to 0 for those that have a\n                    # too large distance\n                    if dist > mask_len:\n                        masked_text_raw_indices[text_i][i] = np.zeros(\n                            (self.bert_local.config.hidden_size), dtype=np.float\n                        )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def feature_dynamic_weighted(\n        self, text_local_indices, aspect_indices, distances_input\n    ):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        if distances_input is not None:\n            distances_input = distances_input.cpu().numpy()\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        mask_len = self.opt.SRD\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            if distances_input is None:\n                asp_len = np.count_nonzero(asps[asp_i]) - 2\n                try:\n                    asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                    asp_avg_index = (asp_begin * 2 + asp_len) / 2\n                except:\n                    continue\n                distances = np.zeros(np.count_nonzero(texts[text_i]), dtype=np.float32)\n                for i in range(1, np.count_nonzero(texts[text_i]) - 1):\n                    if abs(i - asp_avg_index) + asp_len / 2 > self.opt.SRD:\n                        distances[i] = 1 - (\n                            abs(i - asp_avg_index) + asp_len / 2 - self.opt.SRD\n                        ) / np.count_nonzero(texts[text_i])\n                    else:\n                        distances[i] = 1\n                for i in range(len(distances)):\n                    masked_text_raw_indices[text_i][i] = (\n                        masked_text_raw_indices[text_i][i] * distances[i]\n                    )\n            else:\n                distances_i = distances_input[text_i]  # distances of batch i-th\n                for i, dist in enumerate(distances_i):\n                    if dist > mask_len:\n                        distances_i[i] = 1 - (dist - mask_len) / np.count_nonzero(\n                            texts[text_i]\n                        )\n                    else:\n                        distances_i[i] = 1\n\n                for i in range(len(distances_i)):\n                    masked_text_raw_indices[text_i][i] = (\n                        masked_text_raw_indices[text_i][i] * distances_i[i]\n                    )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def forward(self, inputs):\n        text_target_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS,\n        )\n\n        text_target_bert_segments_ids = FXDataset.get_input_by_params(\n            inputs,\n            BERT_BASE_UNCASED,\n            FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n        )\n        text_local_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        aspect_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n        syntax_hop_distance_to_target = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_SYNTAX_HOP_DISTANCE_TO_TARGET\n        )\n\n        bert_spc_out, _, _ = self.bert_spc(\n            text_target_bert_indices, text_target_bert_segments_ids\n        )\n\n        bert_local_out, _, _ = self.bert_local(text_local_indices)\n\n        if self.opt.local_context_focus == \"cdm\":\n            masked_local_text_vec = self.feature_dynamic_mask(\n                text_local_indices, aspect_indices, syntax_hop_distance_to_target\n            )\n            bert_local_out = torch.mul(bert_local_out, masked_local_text_vec)\n\n        elif self.opt.local_context_focus == \"cdw\":\n            weighted_text_local_features = self.feature_dynamic_weighted(\n                text_local_indices, aspect_indices, syntax_hop_distance_to_target\n            )\n            bert_local_out = torch.mul(bert_local_out, weighted_text_local_features)\n\n        out_cat = torch.cat((bert_local_out, bert_spc_out), dim=-1)\n        mean_pool = self.mean_pooling_double(out_cat)\n        self_attention_out = self.bert_SA(mean_pool)\n        pooled_out = self.bert_pooler(self_attention_out)\n\n        dense_out = self.dense(pooled_out)\n        return dense_out\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/lcfst.py",
    "content": "# adapted from https://github.com/yangheng95/LCF-ABSA and\n# https://github.com/StevePhan101/LCFS-BERT/\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\n\n# from transformers.modeling_bert import BertPooler, BertSelfAttention\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass PointwiseFeedForward(nn.Module):\n    \"\"\"\n    A two-feed-forward-layer module\n    \"\"\"\n\n    def __init__(self, d_hid, d_inner_hid=None, d_out=None, dropout=0):\n        super(PointwiseFeedForward, self).__init__()\n        if d_inner_hid is None:\n            d_inner_hid = d_hid\n        if d_out is None:\n            d_out = d_inner_hid\n        self.w_1 = nn.Conv1d(d_hid, d_inner_hid, 1)  # position-wise\n        self.w_2 = nn.Conv1d(d_inner_hid, d_out, 1)  # position-wise\n        self.dropout = nn.Dropout(dropout)\n        self.relu = nn.ReLU()\n\n    def forward(self, x):\n        output = self.relu(self.w_1(x.transpose(1, 2)))\n        output = self.w_2(output).transpose(2, 1)\n        output = self.dropout(output)\n        return output\n\n\nclass SelfAttention(nn.Module):\n    def __init__(self, config, opt):\n        super(SelfAttention, self).__init__()\n        self.opt = opt\n        self.config = config\n        self.SA = None  # BertSelfAttention(config)\n        self.tanh = torch.nn.Tanh()\n\n    def forward(self, inputs):\n        zero_tensor = torch.tensor(\n            np.zeros((inputs.size(0), 1, 1, self.opt.max_seq_len), dtype=np.float32),\n            dtype=torch.float32,\n        ).to(self.opt.device)\n        SA_out = self.SA(inputs, zero_tensor)\n        return self.tanh(SA_out[0])\n\n\nclass LCFST_BERT(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (\n                BERT_BASE_UNCASED,\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n            ),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (BERT_BASE_UNCASED, FIELD_SYNTAX_HOP_DISTANCE_TO_TARGET),\n            (BERT_BASE_UNCASED, FIELD_SYNTAX_DEPENDENCY_MATRIX),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(LCFST_BERT, self).__init__()\n\n        bert = transformer_models[BERT_BASE_UNCASED]\n        self.bert_spc = bert\n        self.opt = opt\n\n        # self.bert_local = copy.deepcopy(bert)  # Uncomment the line to use dual Bert\n        self.bert_local = (\n            bert  # Default to use single Bert and reduce memory requirements\n        )\n        self.dropout = nn.Dropout(self.opt.dropout)\n        self.bert_SA = SelfAttention(bert.config, self.opt)\n\n        self.dependency_tree_to_attention_vector = nn.Linear(opt.max_seq_len, 1)\n        # perform the softmax along each batch (dim 0)\n        self.softmax = nn.Softmax(dim=0)\n\n        # self.linear_double = nn.Linear(\n        #    bert.config.hidden_size * 2, bert.config.hidden_size\n        # )\n        self.mean_pooling_double = PointwiseFeedForward(\n            bert.config.hidden_size * 3,\n            bert.config.hidden_size,\n            bert.config.hidden_size,\n        )\n        self.linear_single = nn.Linear(bert.config.hidden_size, bert.config.hidden_size)\n        self.bert_pooler = None  # BertPooler(bert.config)\n\n        self.dense = nn.Linear(bert.config.hidden_size, self.opt.polarities_dim)\n\n    def feature_dynamic_mask(self, text_local_indices, aspect_indices, distances_input):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        if distances_input is not None:\n            distances_input = distances_input.cpu().numpy()\n        mask_len = self.opt.SRD\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            if distances_input is None:\n                # this should never be reached\n                asp_len = np.count_nonzero(asps[asp_i]) - 2\n                try:\n                    asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                except:\n                    continue\n                if asp_begin >= mask_len:\n                    mask_begin = asp_begin - mask_len\n                else:\n                    mask_begin = 0\n                for i in range(mask_begin):\n                    masked_text_raw_indices[text_i][i] = np.zeros(\n                        (self.bert_local.config.hidden_size), dtype=np.float\n                    )\n                for j in range(asp_begin + asp_len + mask_len, self.opt.max_seq_len):\n                    masked_text_raw_indices[text_i][j] = np.zeros(\n                        (self.bert_local.config.hidden_size), dtype=np.float\n                    )\n                else:\n                    distances_i = distances_input[text_i]\n                for i, dist in enumerate(distances_i):\n                    # iterate the distances and set the mask to 0 for those that have a\n                    # too large distance\n                    if dist > mask_len:\n                        masked_text_raw_indices[text_i][i] = np.zeros(\n                            (self.bert_local.config.hidden_size), dtype=np.float\n                        )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def feature_dynamic_weighted(\n        self, text_local_indices, aspect_indices, distances_input\n    ):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        if distances_input is not None:\n            distances_input = distances_input.cpu().numpy()\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        mask_len = self.opt.SRD\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            if distances_input is None:\n                asp_len = np.count_nonzero(asps[asp_i]) - 2\n                try:\n                    asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                    asp_avg_index = (asp_begin * 2 + asp_len) / 2\n                except:\n                    continue\n                distances = np.zeros(np.count_nonzero(texts[text_i]), dtype=np.float32)\n                for i in range(1, np.count_nonzero(texts[text_i]) - 1):\n                    if abs(i - asp_avg_index) + asp_len / 2 > self.opt.SRD:\n                        distances[i] = 1 - (\n                            abs(i - asp_avg_index) + asp_len / 2 - self.opt.SRD\n                        ) / np.count_nonzero(texts[text_i])\n                    else:\n                        distances[i] = 1\n                for i in range(len(distances)):\n                    masked_text_raw_indices[text_i][i] = (\n                        masked_text_raw_indices[text_i][i] * distances[i]\n                    )\n            else:\n                distances_i = distances_input[text_i]  # distances of batch i-th\n                for i, dist in enumerate(distances_i):\n                    if dist > mask_len:\n                        distances_i[i] = 1 - (dist - mask_len) / np.count_nonzero(\n                            texts[text_i]\n                        )\n                    else:\n                        distances_i[i] = 1\n\n                for i in range(len(distances_i)):\n                    masked_text_raw_indices[text_i][i] = (\n                        masked_text_raw_indices[text_i][i] * distances_i[i]\n                    )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def forward(self, inputs):\n        text_target_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS,\n        )\n        text_target_bert_segments_ids = FXDataset.get_input_by_params(\n            inputs,\n            BERT_BASE_UNCASED,\n            FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n        )\n        text_local_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        aspect_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n        syntax_hop_distance_to_target = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_SYNTAX_HOP_DISTANCE_TO_TARGET\n        )\n        syntax_dependency_matrix = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_SYNTAX_DEPENDENCY_MATRIX\n        )\n\n        # apply bert\n        bert_spc_out, _, _ = self.bert_spc(\n            text_target_bert_indices, text_target_bert_segments_ids\n        )\n        bert_local_out, _, _ = self.bert_local(text_local_indices)\n\n        # perform LCFS masking (better than LCF masking)\n        if self.opt.local_context_focus == \"cdm\":\n            masked_local_text_vec = self.feature_dynamic_mask(\n                text_local_indices, aspect_indices, syntax_hop_distance_to_target\n            )\n            bert_local_out_weighted_syntax_distance = torch.mul(\n                bert_local_out, masked_local_text_vec\n            )\n        elif self.opt.local_context_focus == \"cdw\":\n            weighted_text_local_features = self.feature_dynamic_weighted(\n                text_local_indices, aspect_indices, syntax_hop_distance_to_target\n            )\n            bert_local_out_weighted_syntax_distance = torch.mul(\n                bert_local_out, weighted_text_local_features\n            )\n        else:\n            raise NotImplementedError\n\n        # perform dependency weight vector weighting (\"masking\")\n        dependency_weight_vector = self.dependency_tree_to_attention_vector(\n            syntax_dependency_matrix\n        )\n        # we need to have some normalization because the other vectors that are stacked later are all yielded\n        # by normalized weighting vectors. besides the implementation below, we for now simply use softmax, but\n        # cf https://stats.stackexchange.com/questions/481798\n        dependency_weight_vector_normalized = self.softmax(dependency_weight_vector)\n        # since softmax sums to 1 in each batch item, we multiply this with the seqlen to match the \"power\" of the\n        # other things that are later stacked (there, each weight scalar of the vector that is multiplied\n        # with the bert output is between 0 and 1, whereas after softmax they all sum to 1)\n        seqlen = text_target_bert_indices.shape[1]\n        dependency_weight_vector_normalized = (\n            dependency_weight_vector_normalized * seqlen\n        )\n\n        # we linearly normalize the dependency weight vector because its values will currently be just any float\n        # we do this because the other (two) components that are concatenated later are either original bert's output\n        # or bert's output multiplied with a weight mask (each scalar between 0 and 1), so we do the same here\n        # shape: batch, seq, 1\n        # for each batch item, it should be normalized independently of the other batch items so that each of scalar\n        # in the batch item is between 0 and 1\n        # perform sigmoid first to handle very large and very small values. after this values will be between 0 and 1\n        # dependency_weight_vector = self.sigmoid(dependency_weight_vector)\n        # dependency_weight_vector_min_batch_wise, _ = dependency_weight_vector.min(dim=1, keepdim=True)\n        # dependency_weight_vector_max_batch_wise, _ = dependency_weight_vector.max(dim=1, keepdim=True)\n        # actual linear normalization\n        # dependency_weight_vector_normalized = dependency_weight_vector-dependency_weight_vector_min_batch_wise\n        # dependency_weight_vector_normalized = dependency_weight_vector_normalized / (\n        #        dependency_weight_vector_max_batch_wise - dependency_weight_vector_min_batch_wise\n        # )\n        # repeat for scalar wise multiplication\n        dependency_weight_vector_normalized = dependency_weight_vector_normalized.repeat(\n            1, 1, bert_local_out.shape[2]\n        )\n\n        # multiply with bert\n        bert_local_out_weighted_dependency_tree = torch.mul(\n            bert_local_out, dependency_weight_vector_normalized\n        )\n\n        out_cat = torch.cat(\n            (\n                bert_local_out_weighted_syntax_distance,\n                bert_local_out_weighted_dependency_tree,\n                bert_spc_out,\n            ),\n            dim=-1,\n        )\n        mean_pool = self.mean_pooling_double(out_cat)\n        self_attention_out = self.bert_SA(mean_pool)\n        pooled_out = self.bert_pooler(self_attention_out)\n\n        dense_out = self.dense(pooled_out)\n        return dense_out\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/lcft.py",
    "content": "# adapted from https://github.com/yangheng95/LCF-ABSA\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\n\n# from transformers.modeling_bert import BertPooler, BertSelfAttention\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass PointwiseFeedForward(nn.Module):\n    \"\"\"\n    A two-feed-forward-layer module\n    \"\"\"\n\n    def __init__(self, d_hid, d_inner_hid=None, d_out=None, dropout=0):\n        super(PointwiseFeedForward, self).__init__()\n        if d_inner_hid is None:\n            d_inner_hid = d_hid\n        if d_out is None:\n            d_out = d_inner_hid\n        self.w_1 = nn.Conv1d(d_hid, d_inner_hid, 1)  # position-wise\n        self.w_2 = nn.Conv1d(d_inner_hid, d_out, 1)  # position-wise\n        self.dropout = nn.Dropout(dropout)\n        self.relu = nn.ReLU()\n\n    def forward(self, x):\n        output = self.relu(self.w_1(x.transpose(1, 2)))\n        output = self.w_2(output).transpose(2, 1)\n        output = self.dropout(output)\n        return output\n\n\nclass SelfAttention(nn.Module):\n    def __init__(self, config, opt):\n        super(SelfAttention, self).__init__()\n        self.opt = opt\n        self.config = config\n        self.SA = None  # BertSelfAttention(config)\n        self.tanh = torch.nn.Tanh()\n\n    def forward(self, inputs):\n        zero_tensor = torch.tensor(\n            np.zeros((inputs.size(0), 1, 1, self.opt.max_seq_len), dtype=np.float32),\n            dtype=torch.float32,\n        ).to(self.opt.device)\n        SA_out = self.SA(inputs, zero_tensor)\n        return self.tanh(SA_out[0])\n\n\nclass LCFT_BERT(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (\n                BERT_BASE_UNCASED,\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n            ),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n            (BERT_BASE_UNCASED, FIELD_SYNTAX_DEPENDENCY_MATRIX),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(LCFT_BERT, self).__init__()\n\n        bert = transformer_models[BERT_BASE_UNCASED]\n        self.bert_spc = bert\n        self.opt = opt\n\n        # self.bert_local = copy.deepcopy(bert)  # Uncomment the line to use dual Bert\n        self.bert_local = (\n            bert  # Default to use single Bert and reduce memory requirements\n        )\n        self.dropout = nn.Dropout(self.opt.dropout)\n        self.bert_SA = SelfAttention(bert.config, self.opt)\n\n        self.dependency_tree_to_attention_vector = nn.Linear(opt.max_seq_len, 1)\n        # perform the softmax along each batch (dim 0)\n        self.softmax = nn.Softmax(dim=0)\n\n        # self.linear_double = nn.Linear(\n        #    bert.config.hidden_size * 2, bert.config.hidden_size\n        # )\n        self.mean_pooling_double = PointwiseFeedForward(\n            bert.config.hidden_size * 2,\n            bert.config.hidden_size,\n            bert.config.hidden_size,\n        )\n        self.linear_single = nn.Linear(bert.config.hidden_size, bert.config.hidden_size)\n        self.bert_pooler = None  # BertPooler(bert.config)\n\n        self.dense = nn.Linear(bert.config.hidden_size, self.opt.polarities_dim)\n\n    def feature_dynamic_mask(self, text_local_indices, aspect_indices, distances_input):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        if distances_input is not None:\n            distances_input = distances_input.cpu().numpy()\n        mask_len = self.opt.SRD\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            if distances_input is None:\n                # this should never be reached\n                asp_len = np.count_nonzero(asps[asp_i]) - 2\n                try:\n                    asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                except:\n                    continue\n                if asp_begin >= mask_len:\n                    mask_begin = asp_begin - mask_len\n                else:\n                    mask_begin = 0\n                for i in range(mask_begin):\n                    masked_text_raw_indices[text_i][i] = np.zeros(\n                        (self.bert_local.config.hidden_size), dtype=np.float\n                    )\n                for j in range(asp_begin + asp_len + mask_len, self.opt.max_seq_len):\n                    masked_text_raw_indices[text_i][j] = np.zeros(\n                        (self.bert_local.config.hidden_size), dtype=np.float\n                    )\n                else:\n                    distances_i = distances_input[text_i]\n                for i, dist in enumerate(distances_i):\n                    # iterate the distances and set the mask to 0 for those that have a\n                    # too large distance\n                    if dist > mask_len:\n                        masked_text_raw_indices[text_i][i] = np.zeros(\n                            (self.bert_local.config.hidden_size), dtype=np.float\n                        )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def feature_dynamic_weighted(\n        self, text_local_indices, aspect_indices, distances_input\n    ):\n        texts = text_local_indices.cpu().numpy()\n        asps = aspect_indices.cpu().numpy()\n        if distances_input is not None:\n            distances_input = distances_input.cpu().numpy()\n        masked_text_raw_indices = np.ones(\n            (\n                text_local_indices.size(0),\n                self.opt.max_seq_len,\n                self.bert_local.config.hidden_size,\n            ),\n            dtype=np.float32,\n        )\n        mask_len = self.opt.SRD\n        for text_i, asp_i in zip(range(len(texts)), range(len(asps))):\n            if distances_input is None:\n                asp_len = np.count_nonzero(asps[asp_i]) - 2\n                try:\n                    asp_begin = np.argwhere(texts[text_i] == asps[asp_i][1])[0][0]\n                    asp_avg_index = (asp_begin * 2 + asp_len) / 2\n                except:\n                    continue\n                distances = np.zeros(np.count_nonzero(texts[text_i]), dtype=np.float32)\n                for i in range(1, np.count_nonzero(texts[text_i]) - 1):\n                    if abs(i - asp_avg_index) + asp_len / 2 > self.opt.SRD:\n                        distances[i] = 1 - (\n                            abs(i - asp_avg_index) + asp_len / 2 - self.opt.SRD\n                        ) / np.count_nonzero(texts[text_i])\n                    else:\n                        distances[i] = 1\n                for i in range(len(distances)):\n                    masked_text_raw_indices[text_i][i] = (\n                        masked_text_raw_indices[text_i][i] * distances[i]\n                    )\n            else:\n                distances_i = distances_input[text_i]  # distances of batch i-th\n                for i, dist in enumerate(distances_i):\n                    if dist > mask_len:\n                        distances_i[i] = 1 - (dist - mask_len) / np.count_nonzero(\n                            texts[text_i]\n                        )\n                    else:\n                        distances_i[i] = 1\n\n                for i in range(len(distances_i)):\n                    masked_text_raw_indices[text_i][i] = (\n                        masked_text_raw_indices[text_i][i] * distances_i[i]\n                    )\n        masked_text_raw_indices = torch.from_numpy(masked_text_raw_indices)\n        return masked_text_raw_indices.to(self.opt.device)\n\n    def forward(self, inputs):\n        text_target_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS,\n        )\n        text_target_bert_segments_ids = FXDataset.get_input_by_params(\n            inputs,\n            BERT_BASE_UNCASED,\n            FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n        )\n        text_local_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        aspect_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n        syntax_dependency_matrix = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_SYNTAX_DEPENDENCY_MATRIX\n        )\n\n        # apply bert\n        bert_spc_out, _, _ = self.bert_spc(\n            text_target_bert_indices, text_target_bert_segments_ids\n        )\n        bert_local_out, _, _ = self.bert_local(text_local_indices)\n\n        # perform dependency weight vector weighting (\"masking\")\n        dependency_weight_vector = self.dependency_tree_to_attention_vector(\n            syntax_dependency_matrix\n        )\n        # we need to have some normalization because the other vectors that are stacked later are all yielded\n        # by normalized weighting vectors. besides the implementation below, we for now simply use softmax, but\n        # cf https://stats.stackexchange.com/questions/481798\n        dependency_weight_vector_normalized = self.softmax(dependency_weight_vector)\n        # since softmax sums to 1 in each batch item, we multiply this with the seqlen to match the \"power\" of the\n        # other things that are later stacked (there, each weight scalar of the vector that is multiplied\n        # with the bert output is between 0 and 1, whereas after softmax they all sum to 1)\n        seqlen = text_target_bert_indices.shape[1]\n        dependency_weight_vector_normalized = (\n            dependency_weight_vector_normalized * seqlen\n        )\n\n        # we linearly normalize the dependency weight vector because its values will currently be just any float\n        # we do this because the other (two) components that are concatenated later are either original bert's output\n        # or bert's output multiplied with a weight mask (each scalar between 0 and 1), so we do the same here\n        # shape: batch, seq, 1\n        # for each batch item, it should be normalized independently of the other batch items so that each of scalar\n        # in the batch item is between 0 and 1\n        # perform sigmoid first to handle very large and very small values. after this values will be between 0 and 1\n        # dependency_weight_vector = self.sigmoid(dependency_weight_vector)\n        # dependency_weight_vector_min_batch_wise, _ = dependency_weight_vector.min(dim=1, keepdim=True)\n        # dependency_weight_vector_max_batch_wise, _ = dependency_weight_vector.max(dim=1, keepdim=True)\n        # actual linear normalization\n        # dependency_weight_vector_normalized = dependency_weight_vector-dependency_weight_vector_min_batch_wise\n        # dependency_weight_vector_normalized = dependency_weight_vector_normalized / (\n        #        dependency_weight_vector_max_batch_wise - dependency_weight_vector_min_batch_wise\n        # )\n        # repeat for scalar wise multiplication\n        dependency_weight_vector_normalized = dependency_weight_vector_normalized.repeat(\n            1, 1, bert_local_out.shape[2]\n        )\n\n        # multiply with bert\n        bert_local_out_weighted_dependency_tree = torch.mul(\n            bert_local_out, dependency_weight_vector_normalized\n        )\n\n        out_cat = torch.cat(\n            (bert_local_out_weighted_dependency_tree, bert_spc_out,), dim=-1,\n        )\n        mean_pool = self.mean_pooling_double(out_cat)\n        self_attention_out = self.bert_SA(mean_pool)\n        pooled_out = self.bert_pooler(self_attention_out)\n\n        dense_out = self.dense(pooled_out)\n        return dense_out\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/notargetcls.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.layers.AggregatorForBert import AggregatorForBert\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass NoTargetClsBert(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(NoTargetClsBert, self).__init__()\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.aggregator_for_bert = AggregatorForBert(opt.spc_lm_representation)\n        self.dropout = nn.Dropout(opt.dropout)\n        self.dense = nn.Linear(\n            self.language_model.config.hidden_size, opt.polarities_dim\n        )\n\n    def forward(self, inputs):\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n\n        last_hidden_state, pooler_output, all_hidden_states = self.language_model(\n            input_ids=text_bert_indices\n        )\n        prepared_output = self.aggregator_for_bert(\n            last_hidden_state, pooler_output, all_hidden_states\n        )\n\n        prepared_output = self.dropout(prepared_output)\n        logits = self.dense(prepared_output)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/random_single.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass RandomSingle(FXBaseModel):\n    \"\"\"\n\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        \"\"\"\n        All architecture assumes that at least one model is used so we just require\n        bert here for compatibility.\n        :return:\n        \"\"\"\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(RandomSingle, self).__init__()\n        self.num_classes = opt.polarities_dim\n\n    def forward(self, inputs):\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        batch_size = text_bert_indices.shape[0]\n        num_targets = text_bert_indices.shape[1]\n\n        # get a random tensor\n        logits = torch.rand(batch_size, num_targets, self.num_classes)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/spc.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.layers.AggregatorForBert import AggregatorForBert\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass SPC_Base(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (get_default_lm(),)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS),\n            (\n                get_default_lm(),\n                FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n            ),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(SPC_Base, self).__init__()\n        self.language_model = transformer_models[get_default_lm()]\n        self.aggregator_for_bert = AggregatorForBert(opt.spc_lm_representation)\n        self.dropout = nn.Dropout(opt.dropout)\n        self.dense = nn.Linear(\n            self.language_model.config.hidden_size, opt.polarities_dim\n        )\n\n    def forward(self, inputs):\n        text_target_bert_indices = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_target_bert_segments_ids = FXDataset.get_input_by_params(\n            inputs,\n            get_default_lm(),\n            FIELD_TEXT_THEN_TARGET_IDS_WITH_SPECIAL_TOKENS_SEGMENT_IDS,\n        )\n\n        last_hidden_state = self.invoke_language_model(\n            lm=self.language_model,\n            input_ids=text_target_bert_indices,\n            token_type_ids=text_target_bert_segments_ids,\n        )\n        # the following two variables can only be derived for some model, whereas invoke_language_model currently\n        # returns only one last_hidden_state.\n        assert self.aggregator_for_bert.spc_lm_representation == \"mean_last\"\n        pooler_output, all_hidden_states = None, None\n        prepared_output = self.aggregator_for_bert(\n            last_hidden_state, pooler_output, all_hidden_states\n        )\n        prepared_output = self.dropout(prepared_output)\n        logits = self.dense(prepared_output)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/td_bert.py",
    "content": "# this file re-implements TD-BERT by Gao Zhengjie et al.\n# while this file aims to be conceptually identical to TD-BERT, one technical difference is that we do not calculate\n# the target mask within the model (here) but do this step as part of the dataset processing. in case there are strong\n# performance differences between original TD-BERT and this implementation, this technical difference might be worth\n# exploring whether it actually yields an identical implementation.\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass TD_BERT(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (get_default_lm(),)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(TD_BERT, self).__init__()\n        self.opt = opt\n        self.language_model = transformer_models[get_default_lm()]\n        self.dropout = nn.Dropout(opt.dropout)\n        self.fc = nn.Linear(self.language_model.config.hidden_size, opt.polarities_dim)\n\n    def forward(self, inputs, is_return_ensemble_values: bool = False):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_target_mask = FXDataset.get_input_by_params(\n            inputs, get_default_lm(), FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n\n        # apply bert\n        last_hidden_states = self.invoke_language_model(\n            lm=self.language_model,\n            input_ids=text_bert_indices,\n        )\n\n        # element-wise multiplication with target mask\n        # unsqueeze, cf. https://stackoverflow.com/q/62559382\n        text_bert_indices_target_mask_unsqueezed = text_bert_indices_target_mask.unsqueeze(\n            -1\n        )\n        last_hidden_states_only_target = (\n                last_hidden_states * text_bert_indices_target_mask_unsqueezed\n        )\n\n        # as in TD-BERT, perform max pooling\n        last_hidden_states_only_target_aggregated, _ = last_hidden_states_only_target.max(\n            dim=1\n        )\n\n        # dropout before dense layer, as in most other tsc models\n        last_hidden_states_only_target_aggregated = self.dropout(\n            last_hidden_states_only_target_aggregated\n        )\n\n        if is_return_ensemble_values:\n            return last_hidden_states_only_target_aggregated\n        else:\n            # dense layer\n            logits = self.fc(last_hidden_states_only_target_aggregated)\n            # removed tanh, which was invoked in original tdbert. for training, we dont\n            # need it to properly compute the loss. we would, however, need softmax during\n            # inferring to have the probabilities of all mutually exclusive classes\n            # to sum up to 1\n            return logits\n\n\n\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/td_bert_qa.py",
    "content": "# this file re-implements TD-BERT-QA by Gao Zhengjie et al.\nfrom argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass TD_BERT_QA_MUL(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(TD_BERT_QA_MUL, self).__init__()\n        self.opt = opt\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.dropout = nn.Dropout(opt.dropout)\n        self.fc = nn.Linear(self.language_model.config.hidden_size, opt.polarities_dim)  # 全连接层 bbfc\n        self.bn = nn.BatchNorm1d(self.language_model.config.hidden_size)\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_target_mask = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n\n        # apply bert\n        last_hidden_states, pooler_output, all_hidden_states = self.language_model(\n            input_ids=text_bert_indices\n        )\n\n        # element-wise multiplication with target mask\n        # unsqueeze, cf. https://stackoverflow.com/q/62559382\n        text_bert_indices_target_mask_unsqueezed = text_bert_indices_target_mask.unsqueeze(\n            -1\n        )\n        last_hidden_states_only_target = (\n                last_hidden_states * text_bert_indices_target_mask_unsqueezed\n        )\n\n        # as in TD-BERT, perform max pooling\n        last_hidden_states_only_target_aggregated, _ = last_hidden_states_only_target.max(\n            dim=1\n        )\n\n        target_in_sent_embed = self.bn(last_hidden_states_only_target_aggregated)\n        target_in_sent_embed = target_in_sent_embed.mul(pooler_output)\n        cat = self.dropout(target_in_sent_embed)\n\n        logits = self.fc(cat)\n        # removed tanh, which was invoked in original tdbert. for training, we dont\n        # need it to properly compute the loss. we would, however, need softmax during\n        # inferring to have the probabilities of all mutually exclusive classes\n        # to sum up to 1\n\n        return logits\n\n\nclass TD_BERT_QA_CON(FXBaseModel):\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(TD_BERT_QA_CON, self).__init__()\n        self.opt = opt\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.dropout = nn.Dropout(opt.dropout)\n        self.fc = nn.Linear(self.language_model.config.hidden_size*2, opt.polarities_dim)  # 全连接层 bbfc\n        self.bn = nn.BatchNorm1d(self.language_model.config.hidden_size)\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_target_mask = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n\n        # apply bert\n        last_hidden_states, pooler_output, all_hidden_states = self.language_model(\n            input_ids=text_bert_indices\n        )\n\n        # element-wise multiplication with target mask\n        # unsqueeze, cf. https://stackoverflow.com/q/62559382\n        text_bert_indices_target_mask_unsqueezed = text_bert_indices_target_mask.unsqueeze(\n            -1\n        )\n        last_hidden_states_only_target = (\n                last_hidden_states * text_bert_indices_target_mask_unsqueezed\n        )\n\n        # as in TD-BERT, perform max pooling\n        last_hidden_states_only_target_aggregated, _ = last_hidden_states_only_target.max(\n            dim=1\n        )\n\n        # not entirely sure whether this is as in original tdbertqa-con, because the code does not exist in the repo\n        # (seems to be part of the commented lines in there)\n        pooler_output = self.bn(pooler_output)\n\n        cat = torch.cat([pooler_output, last_hidden_states_only_target_aggregated], dim=1)\n        cat = self.dropout(cat)\n        logits = self.fc(cat)\n        # removed tanh, which was invoked in original tdbert. for training, we dont\n        # need it to properly compute the loss. we would, however, need softmax during\n        # inferring to have the probabilities of all mutually exclusive classes\n        # to sum up to 1\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/models/singletarget/tdbertlikesingle.py",
    "content": "from argparse import Namespace\nfrom typing import Dict\n\nimport torch\nimport torch.nn as nn\n\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset\nfrom NewsSentiment.models.FXBaseModel import FXBaseModel\n\n\nclass TDBertLikeSingle(FXBaseModel):\n    \"\"\"\n    This model returns uses a target mask for a single target to obtain only the hidden\n    states of those last layer nodes that correspond to a wordpiece of the target\n    phrase. Then aggregation, dropout and a dense layer is applied to retrieve the\n    3-class logits.\n\n    From a conceptual perspective, TD-BERT is in some aspects similar (e.g., only the\n    output of target-phrase-related nodes is used), but in other aspects not similar,\n    e.g., we don't use max pooling but a mean on all non-0 target nodes. In other cases,\n    it is not quite clear how the authors of TD-BERT implemented them. An email I sent\n    to them was not answered yet.\n    \"\"\"\n\n    @staticmethod\n    def get_language_models():\n        return (BERT_BASE_UNCASED,)\n\n    @staticmethod\n    def get_input_field_ids():\n        return [\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS),\n            (BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK),\n        ]\n\n    def __init__(self, transformer_models: Dict, opt: Namespace):\n        super(TDBertLikeSingle, self).__init__()\n        self.language_model = transformer_models[BERT_BASE_UNCASED]\n        self.dropout = nn.Dropout(opt.dropout)\n        self.dense = nn.Linear(\n            self.language_model.config.hidden_size, opt.polarities_dim\n        )\n\n    def forward(self, inputs):\n        # get inputs\n        text_bert_indices = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS\n        )\n        text_bert_indices_target_mask = FXDataset.get_input_by_params(\n            inputs, BERT_BASE_UNCASED, FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK\n        )\n\n        # apply bert\n        last_hidden_states, pooler_output, all_hidden_states = self.language_model(\n            input_ids=text_bert_indices\n        )\n\n        # element-wise multiplication with target mask\n        # unsqueeze, cf. https://stackoverflow.com/q/62559382\n        text_bert_indices_target_mask_unsqueezed = text_bert_indices_target_mask.unsqueeze(\n            -1\n        )\n        last_hidden_states_only_target = (\n            last_hidden_states * text_bert_indices_target_mask_unsqueezed\n        )\n\n        # similar to TD-BERT, perform max pooling TODO not implemented yet, instead:\n        # for now, retrieve only the values of the target's output tokens and then\n        # calculate the mean: (batchsize, 150, 768) -> (batchsize, 768)\n        # get the positions of target nodes. note that we cannot simply take the mean\n        # as it would divide by the number of the sequence length, whereas the effective\n        # length is only of size k, where k is the number of non-zero scalars in the\n        # input mask (since we are only interested in those values)\n        last_hidden_states_only_target_aggregated = last_hidden_states_only_target.sum(\n            dim=1\n        )\n        # get the sum for each (batch, hidden states) (sum over the sequence length\n        # dim)\n        denominator_for_mean = text_bert_indices_target_mask_unsqueezed.sum(dim=1)\n        # divide for each (batch, hidden states) by the denominator to get the mean\n        last_hidden_states_only_target_aggregated = (\n            last_hidden_states_only_target_aggregated / denominator_for_mean\n        )\n        # dropout before dense layer, as in most other tsc models\n        last_hidden_states_only_target_aggregated = self.dropout(\n            last_hidden_states_only_target_aggregated\n        )\n        # dense layer\n        logits = self.dense(last_hidden_states_only_target_aggregated)\n\n        return logits\n"
  },
  {
    "path": "NewsSentiment/plotter_utils.py",
    "content": "import os\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn.metrics import confusion_matrix\n\nfrom NewsSentiment.fxlogger import get_logger\n\nlogger = get_logger()\n\n\ndef create_save_plotted_confusion_matrix(conf_matrix, expected_labels, basepath):\n    ax, title = plot_confusion_matrix(conf_matrix, expected_labels, normalize=False)\n    filepath = os.path.join(basepath, 'stats.png')\n    plt.savefig(filepath, bbox_inches='tight')\n    logger.debug(\"created confusion matrices in path: {}\".format(filepath))\n\n\ndef plot_confusion_matrix(cm, classes, normalize=False, title=None, cmap=plt.cm.Blues):\n    \"\"\"\n    This function prints and plots the confusion matrix. Normalization can be applied by setting `normalize=True`.\n    based on https://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html#sphx-glr-auto-examples-model-selection-plot-confusion-matrix-py\n    \"\"\"\n    if not title:\n        if normalize:\n            title = 'Normalized confusion matrix'\n        else:\n            title = 'Confusion matrix, without normalization'\n\n    if normalize:\n        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n        logger.debug(\"Normalized confusion matrix\")\n    else:\n        logger.debug('Confusion matrix, without normalization')\n\n    logger.debug(cm)\n\n    fig, ax = plt.subplots()\n    im = ax.imshow(cm, interpolation='nearest', cmap=cmap)\n    ax.figure.colorbar(im, ax=ax)\n    # We want to show all ticks...\n    ax.set(xticks=np.arange(cm.shape[1]),\n           yticks=np.arange(cm.shape[0]),\n           # ... and label them with the respective list entries\n           xticklabels=classes, yticklabels=classes,\n           title=title,\n           ylabel='True label',\n           xlabel='Predicted label')\n\n    # Rotate the tick labels and set their alignment.\n    plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n             rotation_mode=\"anchor\")\n\n    # Loop over data dimensions and create text annotations.\n    fmt = '.2f' if normalize else 'd'\n    thresh = cm.max() / 2.\n    for i in range(cm.shape[0]):\n        for j in range(cm.shape[1]):\n            ax.text(j, i, format(cm[i, j], fmt),\n                    ha=\"center\", va=\"center\",\n                    color=\"white\" if cm[i, j] > thresh else \"black\")\n    fig.tight_layout()\n\n    return ax, title\n\n\nif __name__ == '__main__':\n    y_true = [\"cat\", \"ant\", \"cat\", \"cat\", \"ant\", \"bird\"]\n    y_pred = [\"ant\", \"ant\", \"cat\", \"cat\", \"ant\", \"cat\"]\n    confmat = confusion_matrix(y_true, y_pred, labels=[\"ant\", \"bird\", \"cat\"])\n\n    create_save_plotted_confusion_matrix(confmat, [\"ant\", \"bird\", \"cat\"], '.')\n"
  },
  {
    "path": "NewsSentiment/pretrained_models/.gitignore",
    "content": "# Ignore everything in this directory\n*\n# Except this file\n!.gitignore\n!state_dicts\n"
  },
  {
    "path": "NewsSentiment/pretrained_models/state_dicts/.gitignore",
    "content": "# Ignore everything in this directory\n*\n# Except this file\n!.gitignore\n"
  },
  {
    "path": "NewsSentiment/results/.gitignore",
    "content": "# Ignore everything in this directory\n*\n# Except this file\n!.gitignore\n"
  },
  {
    "path": "NewsSentiment/train.py",
    "content": "import argparse\nimport math\nimport os\nimport random\nimport sys\nimport time\nfrom collections import Counter\nfrom typing import Iterable\nimport logging\n\nimport numpy\nimport torch\nimport torch.nn as nn\nfrom jsonlines import jsonlines\nfrom torch.utils.data import DataLoader\nfrom transformers import (\n    BertModel,\n    XLNetModel,\n    RobertaModel,\n    PreTrainedModel,\n    BertTokenizer,\n    RobertaTokenizer,\n    XLNetTokenizer,\n    AlbertTokenizer,\n    AlbertModel,\n    PreTrainedTokenizer,\n)\n\nfrom NewsSentiment.SentimentClasses import SentimentClasses\nfrom NewsSentiment.consts import *\nfrom NewsSentiment.dataset import FXDataset, RandomOversampler, FXEasyTokenizer\nfrom NewsSentiment.download import Download\nfrom NewsSentiment.earlystopping import EarlyStopping\nfrom NewsSentiment.evaluator import Evaluator\nfrom NewsSentiment.fxlogger import get_logger\nfrom NewsSentiment.knowledge.bingliuopinion.bingliuopinion import (\n    get_num_bingliu_polarities,\n)\nfrom NewsSentiment.knowledge.mpqasubjectivity.mpqasubjectivity import (\n    get_num_mpqa_subjectivity_polarities,\n)\nfrom NewsSentiment.knowledge.nrcemolex.nrcemolex import get_num_nrc_emotions\nfrom NewsSentiment.knowledge.zeros.zerosknowledge import get_num_zero_dimensions\nfrom NewsSentiment.losses.crossentropycrossweight import CrossEntropyLoss_CrossWeight\nfrom NewsSentiment.losses.crossentropylosslsr import CrossEntropyLoss_LSR\nfrom NewsSentiment.losses.crossentropylosswithconfidence import (\n    CrossEntropyLossWithConfidence,\n)\nfrom NewsSentiment.losses.seq2seqloss import SequenceLoss\nfrom NewsSentiment.models.FXEnsemble import FXEnsemble\nfrom NewsSentiment.models.multitargets.contrasting import Contrasting\nfrom NewsSentiment.models.multitargets.random_multi import RandomMulti\nfrom NewsSentiment.models.multitargets.seq2seq import SeqTwoSeq\nfrom NewsSentiment.models.multitargets.seq2seq_without_targetmask import (\n    SeqTwoSeqWithoutTargetMask,\n)\nfrom NewsSentiment.models.multitargets.tdbertlikemultitarget import (\n    TDBertLikeMultiTarget,\n)\nfrom NewsSentiment.models.multitargets.tdbertlikemultitarget_dense import (\n    TDBertLikeMultiTargetDense,\n)\nfrom NewsSentiment.models.singletarget.aen import AEN_Base\nfrom NewsSentiment.models.singletarget.grutscsingle import GRUTSCSingle\nfrom NewsSentiment.models.singletarget.lcf import LCF_BERT\nfrom NewsSentiment.models.singletarget.lcf2 import LCF_BERT2Dual\nfrom NewsSentiment.models.singletarget.lcfs import LCFS_BERT\nfrom NewsSentiment.models.singletarget.lcfst import LCFST_BERT\nfrom NewsSentiment.models.singletarget.lcft import LCFT_BERT\nfrom NewsSentiment.models.singletarget.notargetcls import NoTargetClsBert\nfrom NewsSentiment.models.singletarget.random_single import RandomSingle\nfrom NewsSentiment.models.singletarget.spc import SPC_Base\nfrom NewsSentiment.models.singletarget.td_bert import TD_BERT\nfrom NewsSentiment.models.singletarget.td_bert_qa import TD_BERT_QA_MUL, TD_BERT_QA_CON\nfrom NewsSentiment.models.singletarget.tdbertlikesingle import TDBertLikeSingle\nfrom NewsSentiment.plotter_utils import create_save_plotted_confusion_matrix\n\nlogger = get_logger()\n\nTRANSFORMER_MODELS_INFO = {\n    BERT_BASE_UNCASED: {\"tokenizer_class\": BertTokenizer, \"model_class\": BertModel},\n    ROBERTA_BASE: {\"tokenizer_class\": RobertaTokenizer, \"model_class\": RobertaModel},\n    XLNET_BASE_CASED: {\"tokenizer_class\": XLNetTokenizer, \"model_class\": XLNetModel},\n    ALBERT_XXLARGE: {\"tokenizer_class\": AlbertTokenizer, \"model_class\": AlbertModel},\n    ALBERT_BASE: {\"tokenizer_class\": AlbertTokenizer, \"model_class\": AlbertModel},\n}\n\nOWN_MODELNAME2CLASS = {\n    # class output\n    \"lcf_bert\": LCF_BERT,\n    \"lcf_bert2\": LCF_BERT2Dual,\n    \"lcfs_bert\": LCFS_BERT,\n    \"lcft_bert\": LCFT_BERT,\n    \"lcfst_bert\": LCFST_BERT,\n    \"spc_bert\": SPC_Base,\n    \"aen_bert\": AEN_Base,\n    \"tdbert\": TD_BERT,\n    \"tdbert-qa-mul\": TD_BERT_QA_MUL,\n    \"tdbert-qa-con\": TD_BERT_QA_CON,\n    \"tdbertlikesingle\": TDBertLikeSingle,\n    \"tdbertlikemulti\": TDBertLikeMultiTarget,\n    \"tdbertlikemulti_dense\": TDBertLikeMultiTargetDense,\n    \"contrasting\": Contrasting,\n    \"grutsc\": GRUTSCSingle,\n    # sequence output\n    \"seq2seq\": SeqTwoSeq,\n    \"seq2seq_withouttargetmask\": SeqTwoSeqWithoutTargetMask,\n    # other baselines\n    \"notargetclsbert\": NoTargetClsBert,\n    \"random_multi\": RandomMulti,\n    \"random_single\": RandomSingle,\n    # misc\n    \"fxensemble\": FXEnsemble,\n}\n\n\nclass Instructor:\n    def __init__(self, opt):\n        self.opt = opt\n\n        self.transformer_tokenizers = {}\n        self.transformer_models = {}\n\n        own_model_class = OWN_MODELNAME2CLASS[opt.own_model_name]\n\n        # create transformer models\n        for pretrained_weights_name in own_model_class.get_language_models():\n            self.create_transformer_model(pretrained_weights_name)\n        logger.info(\"initialized transformer tokenizers and models\")\n\n        # setup own tokenizer\n        self.own_tokenizer = FXEasyTokenizer(\n            self.transformer_tokenizers,\n            self.opt.max_seq_len,\n            self.opt.knowledgesources,\n            self.opt.is_use_natural_target_phrase_for_spc,\n        )\n\n        self.trainset = None\n        self.devset = None\n        self.testset = None\n        self.all_datasets = None\n\n        if self.opt.training_mode:\n            self.load_datasets()\n\n        # get model config (currently supports only a single language model)\n        assert len(self.transformer_models) == 1\n        transformer_model_config = list(self.transformer_models.values())[0].config\n        assert len(self.transformer_tokenizers) == 1\n        transformer_tokenizer = list(self.transformer_tokenizers.values())[0]\n\n        # setup own model\n        own_model_object = own_model_class(\n            transformer_models=self.transformer_models,\n            opt=self.opt,\n            config=transformer_model_config,\n        )\n        own_model_object = own_model_object.to(self.opt.device)\n        if self.opt.state_dict:\n            Download.download(own_model_class)\n            logger.info(\"loading weights from %s...\", self.opt.state_dict)\n            state_dict = torch.load(self.opt.state_dict, map_location=self.opt.device)\n            own_model_object.load_state_dict(state_dict)\n            logger.info(\"done\")\n        self.own_model = own_model_object\n        logger.info(\"initialized own model\")\n\n        if self.opt.export_finetuned_model:\n            self.save_pretrained_model(\n                own_model_object, transformer_tokenizer, self.opt.export_finetuned_model\n            )\n\n        self.evaluator = Evaluator(\n            SentimentClasses.get_sorted_expected_label_values(),\n            SentimentClasses.get_polarity_associations(),\n            self.opt.snem,\n            self.opt.is_return_confidence,\n        )\n\n        self._print_args()\n\n    def _load_dataset(self, path, coref_mode):\n        return FXDataset(\n            path,\n            self.opt.data_format,\n            self.own_tokenizer,\n            SentimentClasses.get_polarity_associations(),\n            SentimentClasses.get_polarity_associations_inverse(),\n            SentimentClasses.get_sorted_expected_label_names(),\n            self.opt.single_targets,\n            coref_mode,\n            self.opt.devmode,\n            self.opt.ignore_parsing_errors,\n        )\n\n    def load_datasets(self):\n        logger.info(\n            \"loading datasets {} from {}\".format(\n                self.opt.dataset_name, self.opt.dataset_path\n            )\n        )\n        self.trainset = self._load_dataset(\n            self.opt.dataset_path + \"train.jsonl\",\n            coref_mode=self.opt.coref_mode_in_training,\n        )\n        self.devset = self._load_dataset(\n            self.opt.dataset_path + \"dev.jsonl\", coref_mode=\"ignore\"\n        )\n        self.testset = self._load_dataset(\n            self.opt.dataset_path + \"test.jsonl\", coref_mode=\"ignore\"\n        )\n        self.all_datasets = [self.trainset, self.devset, self.testset]\n        logger.info(\"loaded datasets from {}\".format(self.opt.dataset_path))\n\n        all_datasets_overflow_counter = Counter()\n        for dataset in self.all_datasets:\n            all_datasets_overflow_counter += dataset.count_sequence_overflow\n        logger.info(\n            f\"count truncated sequences in total: {all_datasets_overflow_counter}\"\n        )\n\n    def _print_args(self):\n        n_trainable_params, n_nontrainable_params = 0, 0\n        for p in self.own_model.parameters():\n            n_params = torch.prod(torch.tensor(p.shape))\n            if p.requires_grad:\n                n_trainable_params += n_params\n            else:\n                n_nontrainable_params += n_params\n        logger.info(\n            \"n_trainable_params: {0}, n_nontrainable_params: {1}\".format(\n                n_trainable_params, n_nontrainable_params\n            )\n        )\n        logger.info(\"> training arguments:\")\n        for arg in vars(self.opt):\n            logger.info(\">>> {0}: {1}\".format(arg, getattr(self.opt, arg)))\n\n    def create_transformer_model(\n        self, pretrained_weights_name: str, only_model: bool = False\n    ):\n        logger.info(\n            \"creating model for weights name: {}\".format(pretrained_weights_name)\n        )\n\n        if not only_model:\n            model_info = TRANSFORMER_MODELS_INFO[pretrained_weights_name]\n            tokenizer_class = model_info[\"tokenizer_class\"]\n            model_class = model_info[\"model_class\"]\n\n            if (\n                self.opt.pretrained_model_name\n                and self.opt.pretrained_model_name is not None\n                and self.opt.pretrained_model_name != \"default\"\n            ):\n                model_path = self.opt.pretrained_model_name\n            else:\n                model_path = pretrained_weights_name\n            logger.info(\"using model_path: %s\", model_path)\n\n            self.transformer_tokenizers[\n                pretrained_weights_name\n            ] = tokenizer_class.from_pretrained(model_path)\n            \n            # supress the transformers warning\n            # \"Some weights of the model checkpoint..were not used..\"\n            transformers_logger = logging.getLogger('transformers.modeling_utils')\n            transformers_logger_level = transformers_logger.getEffectiveLevel()\n            transformers_logger.setLevel(logging.ERROR)\n\n            self.transformer_models[\n                pretrained_weights_name\n            ] = model_class.from_pretrained(model_path, output_hidden_states=True)\n            \n            # reset transformers logging level\n            transformers_logger.setLevel(transformers_logger_level)\n\n    def _reset_params_of_own_model(self):\n        for child in self.own_model.children():\n            if not issubclass(\n                child.__class__, PreTrainedModel\n            ):  # if type(child) != BertModel:  # skip bert params\n                for p in child.parameters():\n                    if p.requires_grad:\n                        if len(p.shape) > 1:\n                            self.opt.initializer(p)\n                        else:\n                            stdv = 1.0 / math.sqrt(p.shape[0])\n                            torch.nn.init.uniform_(p, a=-stdv, b=stdv)\n\n    def _create_prepare_model_path_to_store_state_dict(self, snem, epoch):\n        selected_model_filename = \"{0}_{1}_val_{2}_{3}_epoch{4}\".format(\n            self.opt.own_model_name,\n            self.opt.dataset_name,\n            self.opt.snem,\n            round(snem, 4),\n            epoch,\n        )\n\n        pathdir = os.path.join(self.opt.experiment_path, \"state_dict\")\n\n        os.makedirs(pathdir, exist_ok=True)\n        selected_model_path = os.path.join(pathdir, selected_model_filename)\n\n        return selected_model_filename, selected_model_path\n\n    def select_inputs(self, sample_batched, is_single_item=False):\n        \"\"\"\n        The input to this function is a batch of the dataset, aggregated by pytorch's\n        DataLoader. The DataLoader performs complex aggregation of multiple items of the\n        batch into one vector, e.g.:\n        - a field containing a single number or boolean in each item will become a tensor of size\n          k, where k is the number of items in the batch. Examples: polarity\n        - a field containing a vector (list of) numbers of some size up to m, will\n          become a tensor of size (k, m). Examples: target_mask, text_ids_with_special_tokens\n        - a field containing a str, will become a list of str of size k. Examples: label\n\n        The function at hand then selects only those fields that are one of\n         [FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS, FIELD_TARGET_MASK], for each LM tokenizer\n         defined in the FXEasyTokenizer (this information is setup during initializing\n          the instructor), specifically in self.own_tokenizer.tokenizers_name_and_obj.\n        \"\"\"\n        inputs = []\n        params2index = {}\n        index = 0\n        for weights_name, field_name in self.own_model.get_input_field_ids():\n            seq = sample_batched[weights_name][field_name]\n            if is_single_item:\n                # if we only have a single item, we need to add a virtual, singleton\n                # batch dimension\n                seq = seq.unsqueeze(0)\n            # move to device and append to list\n            inputs.append(seq.to(self.opt.device))\n            # store in param dict for easy access later\n            param_id = (weights_name, field_name)\n            params2index[param_id] = index\n            index += 1\n\n        FXDataset.set_params2index(params2index)\n\n        return inputs\n\n    def _train(self, criterion, optimizer, train_data_loader, dev_data_loader):\n        global_step = 0\n        selected_model_path = None\n        selected_model_filename = None\n        selected_model_dev_stats = None\n\n        # initialize the early_stopping object\n        early_stopping = EarlyStopping()\n\n        # skip training\n        if self._is_random_model():\n            logger.info(\n                \"skipping training because random model: %s\", self.opt.own_model_name\n            )\n            # perform one fake intraining evaluation so that we can save the model and\n            # use that for testset evaluation\n            # set epoch to a bit higher than max number of epochs to ensure that the\n            # model is being saved\n            fake_epoch = self.opt.num_epoch + 2\n            (\n                selected_model_path,\n                selected_model_filename,\n                selected_model_dev_stats,\n            ) = self._intraining_evaluation_and_model_save(\n                dev_data_loader,\n                early_stopping,\n                fake_epoch,\n                selected_model_path,\n                selected_model_filename,\n                selected_model_dev_stats,\n            )\n        else:\n            for epoch in range(self.opt.num_epoch):\n                logger.info(\">\" * 100)\n                logger.info(\n                    \"epoch: {} (num_epoch: {})\".format(epoch, self.opt.num_epoch)\n                )\n                num_correct_predictions_total = 0\n                num_predictions_total = 0\n                num_examples_total = 0\n                loss_total = 0\n\n                # switch model to training mode\n                self.own_model.train()\n\n                # train on batches\n                for i_batch, sample_batched in enumerate(train_data_loader):\n                    global_step += 1\n                    # clear gradient accumulators\n                    optimizer.zero_grad(set_to_none = False)\n                    # select only relevant fields\n                    inputs = self.select_inputs(sample_batched)\n                    targets = sample_batched[\"polarity\"].to(self.opt.device)\n\n                    # invoke the model\n                    outputs = self.own_model(inputs)\n\n                    # some models return multiple objects\n                    if self.opt.own_model_name in [\"contrasting\"]:\n                        outputs, cross_weight = outputs\n\n                    # since the following logic is based on multi targets, but in case of\n                    # single_targets=True this dimension is removed (since the state of the\n                    # art models for single target per item, such as LCF, were not adapted\n                    # to multiple targets, and thus output only a two dimensional tensor\n                    # (batch, polarity)), we need to add a singleton dimension representing\n                    # the target dimension\n                    if self.opt.single_targets:\n                        outputs = outputs.unsqueeze(1)\n\n                    # permute to match k-dimensional crossentropyloss,\n                    # see https://pytorch.org/docs/stable/nn.html#crossentropyloss\n                    outputs = outputs.permute(0, 2, 1)\n\n                    # apply loss\n                    if self.opt.loss == \"sequence\":\n                        # sequence loss requires targets mask (indev: currently, this will\n                        # work only for the \"seq2seq\" model)\n                        text_bert_indices_targets_mask = FXDataset.get_input_by_params(\n                            inputs,\n                            get_default_lm(),\n                            FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK,\n                        )\n                        loss = criterion(\n                            outputs, targets, text_bert_indices_targets_mask\n                        )\n                    elif self.opt.loss == \"crossentropy_crossweight\":\n                        text_bert_indices_targets_mask = FXDataset.get_input_by_params(\n                            inputs,\n                            get_default_lm(),\n                            FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK,\n                        )\n                        loss = criterion(\n                            outputs,\n                            targets,\n                            cross_weight,\n                            text_bert_indices_targets_mask,\n                        )\n                    elif self.opt.is_return_confidence:\n                        loss = criterion(outputs, targets)\n                    else:\n                        loss = criterion(outputs, targets)\n\n                    loss.backward()\n                    optimizer.step()\n\n                    # calculate training stats\n                    # get predicted classes\n                    if self.opt.loss == \"sequence\":\n                        predicted_classes = self._get_classes_from_sequence_output(\n                            outputs, text_bert_indices_targets_mask\n                        )\n                    else:\n                        predicted_classes = torch.argmax(outputs, dim=1)\n\n                    # calculate number of correctly predicted classes and sum it. here, we\n                    # can ignore SentimentClasses.FILLUP_POLARITY_VALUE because when in\n                    # a cell in \"targets\" the value is\n                    # SentimentClasses.FILLUP_POLARITY_VALUE, the corresponding value in\n                    # predicted_classes will never be the same (so this will never attribute\n                    # to a correct prediction)\n                    num_correct_predictions = (\n                        (predicted_classes == targets).sum().item()\n                    )\n                    # to count number of all predictions, we need to ignore those that have\n                    # SentimentClasses.FILLUP_POLARITY_VALUE in a cell of \"targets\"\n                    # note, that we do not use the number of examples but the number of\n                    # predictions, since one training example can contain one or more\n                    # targets\n                    num_predictions = targets != SentimentClasses.FILLUP_POLARITY_VALUE\n                    num_predictions = num_predictions.sum().item()\n                    # ensure the number of predictions in this batch is equal to the number\n                    # of targets defined by the dataset.py\n                    assert num_predictions == sample_batched[\"num_targets\"].sum().item()\n                    # get number of examples (we can use more or less any field in\n                    # sample_batched to get the number of examples)\n                    num_examples = len(sample_batched[\"num_targets\"])\n\n                    # update stats\n                    num_correct_predictions_total += num_correct_predictions\n                    num_predictions_total += num_predictions\n                    loss_total += loss.item() * num_predictions\n                    num_examples_total += num_examples\n                    if global_step % self.opt.log_step == 0:\n                        # update accuracy\n                        train_acc = (\n                            num_correct_predictions_total / num_predictions_total\n                        )\n                        train_loss = loss_total / num_predictions_total\n                        logger.info(\n                            \"loss: {:.4f}, acc: {:.4f}, ex.: {}, pred.: {}/{}\".format(\n                                train_loss,\n                                train_acc,\n                                num_examples_total,\n                                num_correct_predictions_total,\n                                num_predictions_total,\n                            )\n                        )\n\n                # completed all batches of current epoch. now, perform a devset\n                # evaluation and if best model so far, save it\n                (\n                    selected_model_path,\n                    selected_model_filename,\n                    selected_model_dev_stats,\n                ) = self._intraining_evaluation_and_model_save(\n                    dev_data_loader,\n                    early_stopping,\n                    epoch,\n                    selected_model_path,\n                    selected_model_filename,\n                    selected_model_dev_stats,\n                )\n\n                if early_stopping.early_stop and self.opt.use_early_stopping:\n                    logger.info(\n                        \"early stopping after {} epochs without improvement, total epochs: {} of {}\".format(\n                            early_stopping.patience, epoch, self.opt.num_epoch\n                        )\n                    )\n                    break\n\n        return selected_model_path, selected_model_filename, selected_model_dev_stats\n\n    def _intraining_evaluation_and_model_save(\n        self,\n        dev_data_loader,\n        early_stopping,\n        epoch,\n        selected_model_path,\n        selected_model_filename,\n        selected_model_dev_stats,\n    ):\n        dev_stats = self._evaluate(dev_data_loader)\n        dev_snem = dev_stats[self.opt.snem]\n        self.evaluator.print_stats(dev_stats, \"dev during training\")\n        early_stopping(dev_snem)\n\n        (\n            has_stored,\n            _selected_model_filename,\n            _selected_model_path,\n            _selected_model_dev_stats,\n        ) = self._save_model_state_dict(early_stopping, epoch, dev_stats)\n        if has_stored:\n            selected_model_dev_stats = _selected_model_dev_stats\n            selected_model_path = _selected_model_path\n            selected_model_filename = _selected_model_filename\n\n        return selected_model_path, selected_model_filename, selected_model_dev_stats\n\n    def save_pretrained_model(\n        self,\n        pretrained_model: PreTrainedModel,\n        tokenizer: PreTrainedTokenizer,\n        save_directory: str,\n    ):\n        \"\"\"\n        Used to create a model that can be uploaded to huggingface hub\n        :param finetuned_pretrained_model: Should typically be finetuned already\n        :param save_directory:\n        :return:\n        \"\"\"\n        pretrained_model.save_pretrained(save_directory)\n        tokenizer.save_pretrained(save_directory)\n        tokenizer.save_vocabulary(save_directory)\n\n        logger.info(\"model exported to: %s\", save_directory)\n\n    def _save_model_state_dict(self, early_stopping, epoch: int, dev_stats):\n        \"\"\"\n        Used during evaluation to store the best performing model in pytorch format\n        :param early_stopping:\n        :param epoch:\n        :param dev_stats:\n        :return:\n        \"\"\"\n        dev_snem = dev_stats[self.opt.snem]\n\n        has_stored = False\n        selected_model_filename = None\n        selected_model_path = None\n        selected_model_dev_stats = None\n\n        if self.opt.eval_only_after_last_epoch:\n            if epoch >= self.opt.num_epoch - 1:\n                # return the model that was trained through all epochs as the selected model\n                logger.info(\"all epochs finished, saving model to disk...\")\n\n                has_stored = True\n                selected_model_dev_stats = dev_stats\n\n                (\n                    selected_model_filename,\n                    selected_model_path,\n                ) = self._create_prepare_model_path_to_store_state_dict(dev_snem, epoch)\n                torch.save(self.own_model.state_dict(), selected_model_path)\n                logger.info(\">> saved: {}\".format(selected_model_path))\n\n                # save confusion matrices\n                filepath_stats_base = os.path.join(\n                    self.opt.experiment_path, \"statistics\", selected_model_filename\n                )\n                if not filepath_stats_base.endswith(\"/\"):\n                    filepath_stats_base += \"/\"\n                os.makedirs(filepath_stats_base, exist_ok=True)\n                create_save_plotted_confusion_matrix(\n                    dev_stats[\"confusion_matrix\"],\n                    expected_labels=SentimentClasses.get_sorted_expected_label_values(),\n                    basepath=filepath_stats_base,\n                )\n                logger.debug(\n                    \"created confusion matrices in path: {}\".format(filepath_stats_base)\n                )\n        else:\n            # return the best model during any epoch\n            if early_stopping.flag_has_score_increased_since_last_check:\n                logger.info(\"model yields best performance so far, saving to disk...\")\n                has_stored = True\n                selected_model_dev_stats = dev_stats\n                (\n                    selected_model_filename,\n                    selected_model_path,\n                ) = self._create_prepare_model_path_to_store_state_dict(dev_snem, epoch)\n\n                torch.save(self.own_model.state_dict(), selected_model_path)\n                logger.info(\">> saved: {}\".format(selected_model_path))\n\n                # save confusion matrices\n                filepath_stats_base = os.path.join(\n                    self.opt.experiment_path, \"statistics\", selected_model_filename\n                )\n                if not filepath_stats_base.endswith(\"/\"):\n                    filepath_stats_base += \"/\"\n                os.makedirs(filepath_stats_base, exist_ok=True)\n                create_save_plotted_confusion_matrix(\n                    dev_stats[\"confusion_matrix\"],\n                    expected_labels=SentimentClasses.get_sorted_expected_label_values(),\n                    basepath=filepath_stats_base,\n                )\n                logger.debug(\n                    \"created confusion matrices in path: {}\".format(filepath_stats_base)\n                )\n        return (\n            has_stored,\n            selected_model_filename,\n            selected_model_path,\n            selected_model_dev_stats,\n        )\n\n    def _get_classes_from_sequence_output(\n        self, model_outputs, text_bert_indices_targets_mask\n    ):\n        \"\"\"\n\n        :param model_outputs: Tensor of shape:\n            batch, numclasses, seqlen\n        :param text_bert_indices_targets_mask: Tensor of shape:\n            batch, targets, seqlen\n        :return: Tensor of shape:\n            batch, targets\n        \"\"\"\n        num_targets = text_bert_indices_targets_mask.shape[1]\n        num_classes = model_outputs.shape[1]\n\n        # prepare model output\n        model_outputs = model_outputs.unsqueeze(1)\n        model_outputs = model_outputs.repeat(1, num_targets, 1, 1)\n        # new shape: batch, targets, numclasses, seqlen\n\n        # prepare text_bert_indices_targets_mask\n        text_bert_indices_targets_mask = text_bert_indices_targets_mask.unsqueeze(2)\n        text_bert_indices_targets_mask = text_bert_indices_targets_mask.repeat(\n            1, 1, num_classes, 1\n        )\n        # new shape: batch, targets, numclasses, seqlen\n\n        # multiply so that we will only have the values model output values that belong\n        # to a target node (1's for output nodes with a target in text_bert_indices...\n        # 0's for non-targets)\n        only_target_outputs = model_outputs * text_bert_indices_targets_mask\n        # shape: batch, targets, numclasses, seqlen\n\n        # aggregate, e.g., mean\n        # note that in principle any way of reducing (or aggregating) could be used here\n        # e.g., also sum or max. however, the reducing method should as good as possible\n        # match the way of calculating the sequence based loss (seq2seqloss.py). our\n        # seq-based loss currently equally assigns the loss to each target output node\n        # so that in my opinion the unweighted mean is most appropriate here for\n        # reduction, since it also equally uses the output of each target node\n        only_target_outputs_aggregated = only_target_outputs.mean(3)\n        # shape: batch, targets, classes\n\n        predicted_classes = torch.argmax(only_target_outputs_aggregated, dim=2)\n        # predicted_classes shape: batch, targets\n        return predicted_classes\n\n    def _evaluate(self, data_loader, get_examples=False, basepath=None):\n        t_labels_all = None\n        t_outputs_all = None\n        t_text_bert_indices_targets_mask_all = None\n        t_texts_all = []\n        t_outputs_confidence = None\n\n        # switch model to evaluation mode\n        self.own_model.eval()\n\n        with torch.no_grad():\n            for t_batch, t_sample_batched in enumerate(data_loader):\n                t_inputs = self.select_inputs(t_sample_batched)\n                t_labels = t_sample_batched[\"polarity\"].to(self.opt.device)\n                t_text_bert_indices_targets_mask = FXDataset.get_input_by_params(\n                    t_inputs,\n                    self.own_model.get_language_models()[0],\n                    FIELD_TEXT_IDS_WITH_SPECIAL_TOKENS_TARGET_MASK,\n                )\n                assert len(self.own_model.get_language_models()) == 1, (\n                    f\"multiple language models per own model are currently not supported: \"\n                    f\"{self.own_model.get_language_models()}, \"\n                    f\"{len(self.own_model.get_language_models())}\"\n                )\n\n                t_texts = t_sample_batched[\"text\"]\n                # t_targets = t_sample_batched[\"orig_targets\"]\n\n                # invoke the model\n                t_outputs = self.own_model(t_inputs)\n                # some models return multiple objects\n                if self.opt.own_model_name in [\"contrasting\"]:\n                    t_outputs, t_cross_weight = t_outputs\n\n                if self.opt.single_targets:\n                    t_outputs = t_outputs.unsqueeze(1)\n\n                if t_labels_all is None:\n                    t_labels_all = t_labels\n                    t_outputs_all = t_outputs\n                    t_text_bert_indices_targets_mask_all = (\n                        t_text_bert_indices_targets_mask\n                    )\n                else:\n                    t_labels_all = torch.cat((t_labels_all, t_labels), dim=0)\n                    t_outputs_all = torch.cat((t_outputs_all, t_outputs), dim=0)\n                    t_text_bert_indices_targets_mask_all = torch.cat(\n                        (\n                            t_text_bert_indices_targets_mask_all,\n                            t_text_bert_indices_targets_mask,\n                        ),\n                        dim=0,\n                    )\n\n                t_texts_all.extend(t_texts)\n                # t_targets_all.extend(t_targets)\n\n        y_true = t_labels_all.cpu()\n\n        if self.opt.loss == \"sequence\":\n            # we first need to convert sequence-based predictions to target-based\n            # predictions\n            # permute to match requirement of _get_classes_from_sequence_output\n            t_outputs_all = t_outputs_all.permute(0, 2, 1)\n            y_pred = self._get_classes_from_sequence_output(\n                t_outputs_all, t_text_bert_indices_targets_mask_all\n            ).cpu()\n        else:\n            # softmax: get predictions from outputs\n            # have to take the 3rd (dim=2) dimension\n            if self.opt.is_return_confidence:\n                # we have to remove the last class because this is the confidence and\n                # we do not want to evaluate on the confidence (at least not now)\n                t_outputs_confidence = t_outputs_all.clone().cpu()[:, :, -1]\n                t_outputs_all = t_outputs_all[:, :, :-1]\n            y_pred = torch.argmax(t_outputs_all, dim=2).cpu()\n\n        stats = self.evaluator.calc_statistics(y_true, y_pred, t_outputs_confidence)\n\n        if get_examples:\n            self.evaluator.write_error_table(\n                y_true, y_pred, t_texts_all, basepath + \"errortable.jsonl\",\n            )\n\n        return stats\n\n    def get_normalized_inv_class_frequencies(self):\n        inv_freqs = []\n        for label_name in self.sorted_expected_label_names:\n            inv_freq_of_class = 1.0 / self.testset.label_counter[label_name]\n            inv_freqs.append(inv_freq_of_class)\n\n        sum_of_inv_freqs = sum(inv_freqs)\n        for i in range(len(inv_freqs)):\n            inv_freqs[i] = inv_freqs[i] / sum_of_inv_freqs\n\n        return inv_freqs\n\n    def _is_random_model(self):\n        return self.opt.own_model_name in [\"random_multi\", \"random_single\"]\n\n    def run(self):\n        # balancing modes\n        class_weights = None\n        sampler_train = None\n        assert self.opt.balancing is None, (\n            \"balancing is currently only implemented for None. if we want to have it, \"\n            \"we need to come up with a logic that considers that an item can have \"\n            \"multiple polarities in mtsc-mode\"\n        )\n        if self.opt.balancing == \"lossweighting\":\n            inv_class_freqs = self.get_normalized_inv_class_frequencies()\n            logger.info(\"weighting losses of classes: {}\".format(inv_class_freqs))\n            class_weights = torch.tensor(inv_class_freqs).to(self.opt.device)\n        elif self.opt.balancing == \"oversampling\":\n            sampler_train = RandomOversampler(self.trainset, self.opt.seed)\n\n        if self.opt.loss == \"crossentropy\":\n            if self.opt.is_return_confidence:\n                criterion = CrossEntropyLossWithConfidence(\n                    weight=class_weights,\n                    ignore_index=SentimentClasses.FILLUP_POLARITY_VALUE,\n                )\n            else:\n                criterion = nn.CrossEntropyLoss(\n                    weight=class_weights,\n                    ignore_index=SentimentClasses.FILLUP_POLARITY_VALUE,\n                )\n        elif self.opt.loss == \"crossentropy_lsr\":\n            criterion = CrossEntropyLoss_LSR(\n                self.opt.device, smoothing_value=0.2, weight=class_weights\n            )\n        elif self.opt.loss == \"crossentropy_crossweight\":\n            criterion = CrossEntropyLoss_CrossWeight(\n                device=self.opt.device,\n                weight=class_weights,\n                ignore_index=SentimentClasses.FILLUP_POLARITY_VALUE,\n            )\n        elif self.opt.loss == \"sequence\":\n            criterion = SequenceLoss(device=self.opt.device, weight=class_weights)\n        else:\n            raise ValueError(\"loss unknown: {}\".format(self.opt.loss))\n\n        # optimizer\n        if self._is_random_model():\n            logger.info(\"initialize optimizer\")\n            optimizer = None\n        else:\n            _params = filter(lambda p: p.requires_grad, self.own_model.parameters())\n            optimizer = self.opt.optimizer(\n                _params, lr=self.opt.learning_rate, weight_decay=self.opt.l2reg\n            )\n\n        # data loaders\n        if sampler_train:\n            train_data_loader = DataLoader(\n                dataset=self.trainset,\n                batch_size=self.opt.batch_size,\n                sampler=sampler_train,\n            )\n        else:\n            train_data_loader = DataLoader(\n                dataset=self.trainset, batch_size=self.opt.batch_size, shuffle=True\n            )\n        dev_data_loader = DataLoader(\n            dataset=self.devset, batch_size=self.opt.batch_size, shuffle=False\n        )\n        test_data_loader = DataLoader(\n            dataset=self.testset, batch_size=self.opt.batch_size, shuffle=False\n        )\n\n        # start training\n        self._reset_params_of_own_model()\n        logger.info(\"starting training...\")\n        time_training_start = time.time()\n        best_model_path, best_model_filename, selected_model_dev_stats = self._train(\n            criterion, optimizer, train_data_loader, dev_data_loader\n        )\n        time_training_elapsed_mins = (time.time() - time_training_start) // 60\n        logger.info(\n            \"training finished. duration [mins]: {}\".format(time_training_elapsed_mins)\n        )\n\n        self.perform_post_training_actions(\n            best_model_path,\n            best_model_filename,\n            test_data_loader,\n            selected_model_dev_stats,\n            time_training_elapsed_mins,\n        )\n\n    def get_serializable_stats(self, stats):\n        sstats = stats.copy()\n        sstats[\"recalls_of_classes\"] = stats[\"recalls_of_classes\"].tolist()\n        sstats[\"confusion_matrix\"] = stats[\"confusion_matrix\"].tolist()\n        return sstats\n\n    def get_serializable_opts(self):\n        opts = vars(self.opt)\n        sopts = opts.copy()\n        del sopts[\"optimizer\"]\n        del sopts[\"initializer\"]\n        del sopts[\"device\"]\n        return sopts\n\n    def perform_post_training_actions(\n        self,\n        selected_model_path,\n        selected_model_filename,\n        test_data_loader,\n        selected_model_dev_stats,\n        time_training_elapsed_mins,\n    ):\n        logger.info(\n            \"loading selected model from training: {}\".format(selected_model_path)\n        )\n        self.own_model.load_state_dict(torch.load(selected_model_path))\n\n        logger.info(\"evaluating selected model on test-set\")\n        # set model into evaluation mode (cf. https://pytorch.org/docs/stable/nn.html#torch.nn.Module.train)\n        self.own_model.eval()\n\n        # do the actual evaluation\n        filepath_stats_prefix = os.path.join(\n            self.opt.experiment_path, \"statistics\", selected_model_filename\n        )\n        os.makedirs(filepath_stats_prefix, exist_ok=True)\n        if not filepath_stats_prefix.endswith(\"/\"):\n            filepath_stats_prefix += \"/\"\n\n        test_stats = self._evaluate(\n            test_data_loader, get_examples=True, basepath=filepath_stats_prefix\n        )\n        test_snem = test_stats[self.opt.snem]\n\n        self.evaluator.print_stats(test_stats, \"evaluation on test-set\")\n\n        # save dev and test results\n        experiment_results = {}\n        experiment_results[\"test_stats\"] = self.get_serializable_stats(test_stats)\n        experiment_results[\"dev_stats\"] = self.get_serializable_stats(\n            selected_model_dev_stats\n        )\n        experiment_results[\"options\"] = self.get_serializable_opts()\n        experiment_results[\"time_training_elapsed_mins\"] = time_training_elapsed_mins\n\n        experiment_results_path = os.path.join(\n            self.opt.experiment_path, \"experiment_results.jsonl\"\n        )\n        with jsonlines.open(experiment_results_path, \"w\") as writer:\n            writer.write(experiment_results)\n\n        # save confusion matrices\n        test_confusion_matrix = test_stats[\"confusion_matrix\"]\n\n        create_save_plotted_confusion_matrix(\n            test_confusion_matrix,\n            expected_labels=SentimentClasses.get_sorted_expected_label_values(),\n            basepath=filepath_stats_prefix,\n        )\n\n        logger.info(\"finished execution of this run. exiting.\")\n\n        # print snem pad_value to stdout, for the controller to parse it\n        print(test_snem)\n\n\ndef str2bool(v):\n    if isinstance(v, bool):\n        return v\n    if v.lower() in (\"yes\", \"true\", \"t\", \"y\", \"1\"):\n        return True\n    elif v.lower() in (\"no\", \"false\", \"f\", \"n\", \"0\"):\n        return False\n    else:\n        raise argparse.ArgumentTypeError(\"Boolean pad_value expected.\")\n\n\ndef _setup_cuda(opt):\n    logger.info(\"cuda information\")\n    logger.info(\"scc SGE_GPU: %s\", os.environ.get(\"SGE_GPU\"))\n    logger.info(\"arg: cuda device: %s\", opt.device)\n\n    if torch.cuda.is_available():\n        logger.info(\"cuda is available on this machine\")\n        if opt.device == \"cpu\":\n            logger.info(\"forced use of cpu\")\n            opt.device = torch.device(\"cpu\")\n        elif opt.device is None:\n            logger.info(\"no cuda device defined by argument, using default cuda:0\")\n            opt.device = torch.device(\"cuda:0\")\n        else:\n            assert opt.device and opt.device != \"cpu\"\n            logger.info(\"using cuda device defined by argument\")\n            opt.device = torch.device(opt.device)\n    else:\n        opt.device = torch.device(\"cpu\")\n\n    if opt.device.type == \"cuda\":\n        logger.info(\"GPGPU enabled. CUDA dev index: %s\", opt.device.index)\n        logger.info(\n            \"using GPU (cuda memory allocated: %s)\", torch.cuda.memory_allocated()\n        )\n    else:\n        logger.info(\"using CPU\")\n\n\ndef _die_gracefully(reason: str):\n    logger.info(\"grateful exit:\")\n    logger.info(reason)\n    # traceback.print_stack()\n    sys.exit(99)\n\n\ndef check_arguments(opt):\n    \"\"\"\n    Perform simple check of arguments passed to the tool. Idea is to die gratefully as\n    early as possible with a special RC = -99 if conditions are not met, e.g., neither\n    single_targets nor multi_targets mode is enabled, or if single_targets mode is used\n    with a loss function for multi targets, etc.\n\n    :param opt:\n    :return:\n    \"\"\"\n\n    if not (opt.single_targets != opt.multi_targets):\n        _die_gracefully(\"you must use either \" \"single_targets or multi_targets\")\n\n    if opt.eval_only_after_last_epoch:\n        if opt.use_early_stopping:\n            _die_gracefully(\n                \"early stopping and eval only after last epoch both enabled\"\n            )\n\n    # loss\n    # some easy validation\n    if opt.own_model_name in [\"seq2seq\", \"seq2seq_withouttargetmask\"]:\n        if opt.loss != \"sequence\":\n            _die_gracefully(f\"model_name: {opt.own_model_name}, loss: {opt.loss}\")\n    else:\n        if opt.loss == \"sequence\":\n            _die_gracefully(f\"model_name: {opt.own_model_name}, loss: {opt.loss}\")\n\n    if opt.own_model_name in [\"contrasting\"]:\n        if opt.loss != \"crossentropy_crossweight\":\n            _die_gracefully(f\"model_name: {opt.own_model_name}, loss: {opt.loss}\")\n    else:\n        if opt.loss == \"crossentropy_crossweight\":\n            _die_gracefully(f\"model_name: {opt.own_model_name}, loss: {opt.loss}\")\n\n    # check knowledge source\n    assert type(opt.knowledgesources) == tuple, \"opt.knowledgesources is not tuple\"\n    for source in opt.knowledgesources:\n        if source not in [\n            \"bingliu_opinion\",\n            \"mpqa_subjectivity\",\n            \"nrc_emotions\",\n            \"liwc\",\n            \"zeros\",\n        ]:\n            _die_gracefully(f\"incorrect source: {source} (of '{opt.knowledgesources}')\")\n\n    # coref mode\n    # single-target mode: one target per example\n    # coref ignore: as before\n    #       in_targetmask: just add to each target's targetmask (more 1's in there)\n    #       additional_ex: create additional examples\n    # multi-target mode: k targets per example\n    # coref ignore: as before\n    #       in_targetmask: see above\n    #       additional_ex: create additional examples\n    # but all of this ONLY for train set!\n    assert opt.coref_mode_in_training in [\n        \"ignore\",\n        \"in_targetmask\",\n        \"additional_examples\",\n    ]\n\n\ndef post_process_arguments(opt):\n    # if neither single nor multi targets is enabled, assume default, i.e., single\n    if not opt.single_targets and not opt.multi_targets:\n        opt.single_targets = True\n\n    # post process\n    if type(opt.knowledgesources) == str:\n        # should be a list but sometimes this does not work...\n        opt.knowledgesources = opt.knowledgesources.split(\" \")\n    elif isinstance(opt.knowledgesources, Iterable) and len(opt.knowledgesources) == 1:\n        # actually, if multiple knowledge sources are passed by controller, they will be\n        # treated as a quoted str so that a list of 1 item is created\n        opt.knowledgesources = opt.knowledgesources[0].split(\" \")\n    opt.knowledgesources = tuple(opt.knowledgesources)\n\n    for eks in opt.knowledgesources:\n        if eks == \"nrc_emotions\":\n            num_categories = get_num_nrc_emotions()\n        elif eks == \"mpqa_subjectivity\":\n            num_categories = get_num_mpqa_subjectivity_polarities()\n        elif eks == \"bingliu_opinion\":\n            num_categories = get_num_bingliu_polarities()\n        elif eks == \"liwc\":\n            from knowledge.liwc.liwc import get_num_liwc_categories\n\n            num_categories = get_num_liwc_categories()\n        elif eks == \"zeros\":\n            num_categories = get_num_zero_dimensions()\n        else:\n            raise NotImplementedError(f\"unknown knowledgesource: {eks}\")\n        FXEasyTokenizer.NUM_CATEGORIES_OF_SELECTED_KNOWLEDGE_SOURCES += num_categories\n        logger.info(\n            \"updated total number of categories to %s with EKS %s\",\n            FXEasyTokenizer.NUM_CATEGORIES_OF_SELECTED_KNOWLEDGE_SOURCES,\n            eks,\n        )\n\n\ndef prepare_and_start_instructor(opt):\n    # overwrite default lm\n    set_default_lm(opt.default_lm)\n    logger.info(\"set default language model to %s\", get_default_lm())\n\n    post_process_arguments(opt)\n\n    # check arguments\n    check_arguments(opt)\n\n    if opt.targetclasses == \"newsmtsc3\":\n        SentimentClasses.Sentiment3ForNewsMtsc()\n    elif opt.targetclasses == \"newsmtsc3strong\":\n        SentimentClasses.SentimentStrong3ForNewsMtsc()\n    elif opt.targetclasses == \"newsmtsc3weak\":\n        SentimentClasses.SentimentWeak3ForNewsMtsc()\n    else:\n        raise ValueError(\"\")\n    assert (\n        opt.polarities_dim == -1\n    ), \"polarities_dim needs to be -1 for automatic detection\"\n    opt.polarities_dim = len(SentimentClasses.SENTIMENT_CLASSES)\n    logger.info(\"set number of polarity classes to %s\", opt.polarities_dim)\n\n    if not opt.balancing or opt.balancing == \"None\":\n        opt.balancing = None\n\n    if opt.seed is None:\n        opt.seed = int(time.time())\n        logger.info(\"no random seed was given, using system time\")\n    logger.info(\"setting random seed: {}\".format(opt.seed))\n    random.seed(opt.seed)\n    numpy.random.seed(opt.seed)\n    torch.manual_seed(opt.seed)\n    torch.cuda.manual_seed(opt.seed)\n    torch.backends.cudnn.deterministic = True\n    torch.backends.cudnn.benchmark = False\n\n    initializers = {\n        \"xavier_uniform_\": torch.nn.init.xavier_uniform_,\n        \"xavier_normal_\": torch.nn.init.xavier_normal,\n        \"orthogonal_\": torch.nn.init.orthogonal_,\n    }\n    optimizers = {\n        \"adadelta\": torch.optim.Adadelta,  # default lr=1.0\n        \"adagrad\": torch.optim.Adagrad,  # default lr=0.01\n        \"adam\": torch.optim.Adam,  # default lr=0.001\n        \"adamax\": torch.optim.Adamax,  # default lr=0.002\n        \"asgd\": torch.optim.ASGD,  # default lr=0.01\n        \"rmsprop\": torch.optim.RMSprop,  # default lr=0.01\n        \"sgd\": torch.optim.SGD,\n    }\n\n    # support for custom pretrained language models, e.g., domain adapted models\n    if not opt.pretrained_model_name or opt.pretrained_model_name == \"default\":\n        opt.pretrained_model_name = None\n    else:\n        opt.pretrained_model_name = os.path.join(\n            opt.base_path, \"pretrained_models\", opt.pretrained_model_name\n        )\n\n    # statedicts\n    if opt.state_dict is not None:\n        if os.path.isfile(opt.state_dict) or opt.state_dict == \"pretrained\":\n            # if exists or using pretrained, nothing to do\n            pass\n        else:\n            # if not exists, prefix default path\n            new_path = os.path.join(\"pretrained_models\", \"state_dicts\", opt.state_dict)\n            opt.state_dict = new_path\n    else:\n        # if not defined, nothing to do\n        pass\n\n    if not opt.experiment_path:\n        opt.experiment_path = \".\"\n    if not opt.experiment_path.endswith(\"/\"):\n        opt.experiment_path = opt.experiment_path + \"/\"\n\n    _setup_cuda(opt)\n\n    if opt.training_mode:\n        logger.debug(\"dataset_path not defined, creating from dataset_name...\")\n        opt.dataset_path = os.path.join(\"datasets\", opt.dataset_name)\n        if not opt.dataset_path.endswith(\"/\"):\n            opt.dataset_path = opt.dataset_path + \"/\"\n        logger.debug(\n            \"dataset_path created from dataset_name: {}\".format(opt.dataset_path)\n        )\n\n        # set dataset_path to include experiment_path\n        opt.dataset_path = os.path.join(opt.experiment_path, opt.dataset_path)\n\n    ins = Instructor(opt)\n\n    if opt.training_mode:\n        opt.initializer = initializers[opt.initializer]\n        opt.optimizer = optimizers[opt.optimizer]\n\n        ins.run()\n    else:\n        return ins\n\n\ndef parse_arguments(override_args=False, overwrite_logging_level=None):\n    \"\"\"\n    Where applicable, for each argument a default is defined that led to the best\n    results in our experiments for grutsc (which itself is set as a default for the\n    corresponding argument).\n    :param override_args:\n    :param overwrite_logging_level:\n    :return:\n    \"\"\"\n\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\n        \"--training_mode\", type=str2bool, nargs=\"?\", const=True, default=True\n    )\n    parser.add_argument(\"--own_model_name\", type=str)\n    parser.add_argument(\n        \"--dataset_name\",\n        default=None,\n        type=str,\n        help=\"name of the sub-folder in 'datasets' containing files named [train,dev,test].jsonl\",\n    )\n    parser.add_argument(\"--data_format\", default=\"newsmtsc\", type=str)\n    parser.add_argument(\"--optimizer\", default=\"adam\", type=str)\n    parser.add_argument(\"--initializer\", default=\"xavier_uniform_\", type=str)\n    parser.add_argument(\n        \"--learning_rate\",\n        default=2e-5,\n        type=float,\n        help=\"try 5e-5, 2e-5 for BERT, 1e-3 for others\",\n    )\n    parser.add_argument(\"--dropout\", default=0.1, type=float)\n    parser.add_argument(\"--l2reg\", default=0.01, type=float)\n    parser.add_argument(\n        \"--num_epoch\",\n        default=3,\n        type=int,\n        help=\"try larger number for non-BERT models\",\n    )\n    parser.add_argument(\n        \"--batch_size\", default=16, type=int, help=\"try 16, 32, 64 for BERT models\"\n    )\n    parser.add_argument(\"--log_step\", default=5, type=int)\n    parser.add_argument(\"--max_seq_len\", default=150, type=int)\n    parser.add_argument(\"--polarities_dim\", default=-1, type=int)\n    parser.add_argument(\n        \"--device\",\n        default=None,\n        type=str,\n        help=\"e.g., cuda:0; if None, CPU will be used\",\n    )\n    parser.add_argument(\n        \"--seed\", default=None, type=int, help=\"set seed for reproducibility\"\n    )\n    parser.add_argument(\n        \"--local_context_focus\",\n        default=\"cdm\",\n        type=str,\n        help=\"local context focus mode, cdw or cdm\",\n    )\n    parser.add_argument(\n        \"--SRD\",\n        default=3,\n        type=int,\n        help=\"semantic-relative-distance, see the paper of LCF-BERT \" \"model\",\n    )\n    parser.add_argument(\n        \"--snem\", default=\"f1_macro\", help=\"see evaluator.py for valid options\"\n    )\n    parser.add_argument(\n        \"--devmode\",\n        type=str2bool,\n        nargs=\"?\",\n        const=True,\n        default=False,\n        help=\"devmode, default off, enable by using True\",\n    )\n    parser.add_argument(\n        \"--experiment_path\",\n        default=\"./NewsSentiment/experiments/default\",\n        type=str,\n        help=\"if defined, all data will be read from / saved to a folder in the experiments folder\",\n    )\n    parser.add_argument(\"--balancing\", type=str, default=None)\n    parser.add_argument(\"--spc_lm_representation\", type=str, default=\"mean_last\")\n    parser.add_argument(\n        \"--spc_input_order\",\n        type=str,\n        default=\"text_target\",\n        help=\"SPC: order of input; target_text \" \"or text_target\",\n    )\n    parser.add_argument(\n        \"--use_early_stopping\", type=str2bool, nargs=\"?\", const=True, default=False\n    )\n    parser.add_argument(\n        \"--eval_only_after_last_epoch\",\n        type=str2bool,\n        nargs=\"?\",\n        const=True,\n        default=False,\n        help=\"if False, evaluate the best model that was seen during any training epoch. if True, \"\n        \"evaluate only the model that was trained through all num_epoch epochs.\",\n    )\n    parser.add_argument(\n        \"--pretrained_model_name\",\n        type=str,\n        default=\"default\",\n        help=\"has to be placed in folder pretrained_models\",\n    )\n    parser.add_argument(\"--state_dict\", type=str, default=None)\n    parser.add_argument(\n        \"--single_targets\", type=str2bool, nargs=\"?\", const=True, default=False\n    )\n    parser.add_argument(\n        \"--multi_targets\", type=str2bool, nargs=\"?\", const=True, default=False\n    )\n    parser.add_argument(\"--loss\", type=str, default=\"crossentropy\")\n    parser.add_argument(\"--targetclasses\", type=str, default=\"newsmtsc3\")\n    parser.add_argument(\n        \"--knowledgesources\",\n        nargs=\"+\",\n        default=[\"nrc_emotions\", \"mpqa_subjectivity\", \"bingliu_opinion\"],\n    )\n    parser.add_argument(\n        \"--is_use_natural_target_phrase_for_spc\",\n        type=str2bool,\n        nargs=\"?\",\n        const=True,\n        default=False,\n    )\n    parser.add_argument(\"--default_lm\", type=str, default=ROBERTA_BASE)\n    parser.add_argument(\"--run_id\", type=int, default=0)\n    parser.add_argument(\"--coref_mode_in_training\", type=str, default=\"ignore\")\n    parser.add_argument(\n        \"--logging\", type=str, default=\"INFO\",\n    )\n    parser.add_argument(\n        \"--ignore_parsing_errors\", type=str2bool, nargs=\"?\", const=True, default=False\n    )\n    parser.add_argument(\"--export_finetuned_model\", type=str, default=None)\n    parser.add_argument(\n        \"--is_return_confidence\", type=str2bool, nargs=\"?\", const=True, default=False\n    )\n\n    # if own_args == None -> parse_args will use sys.argv\n    # if own_args == [] -> parse_args will use this empty list instead\n    own_args = None\n    if override_args:\n        own_args = []\n\n    # create arguments\n    opt = parser.parse_args(args=own_args)\n\n    # add basepath\n    dir_path = os.path.dirname(os.path.realpath(__file__))\n    opt.base_path = dir_path\n\n    # set logging\n    if overwrite_logging_level:\n        logger.setLevel(overwrite_logging_level)\n    else:\n        logger.setLevel(opt.logging)\n\n    return opt\n\n\nif __name__ == \"__main__\":\n    logger.info(\"python bin: %s\", sys.executable)\n    opt = parse_arguments()\n    prepare_and_start_instructor(opt)\n"
  },
  {
    "path": "README.md",
    "content": "# NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles\nNewsMTSC is a dataset for target-dependent sentiment classification (TSC) on\nnews articles reporting on policy issues. The dataset consists of more than 11k labeled\nsentences, which we sampled from news articles from online US news outlets. More\ninformation can be found in our paper published at the EACL 2021.\n\nThis repository contains the **dataset** for target-dependent\nsentiment classification in news articles reporting on policy issues. Additionally,\nthe repository contains our **model** named GRU-TSC, which achieves state-of-the-art\nTSC classification performance on NewsMTSC. Check it out - it **works out of the box** :-)\n\n# Quick start\n\n* **I want to classify sentiment**: check out our easy-to-use, high-quality sentiment classifier on [PyPI](https://pypi.org/project/NewsSentiment/)\n* **I need the dataset**: you can [download it here](https://github.com/fhamborg/NewsMTSC/raw/main/NewsSentiment/controller_data/datasets/NewsMTSC-dataset/NewsMTSC-dataset.zip) or [view it here](https://github.com/fhamborg/NewsMTSC/tree/main/NewsSentiment/controller_data/datasets/NewsMTSC-dataset). We also offer NewsMTSC as a dataset on [Huggingface Hub](https://huggingface.co/datasets/fhamborg/news_sentiment_newsmtsc) and on [Kaggle](https://www.kaggle.com/fhamborg/news-articles-sentiment).\n* **I want to train my own models**: read the remainder of this file.\n\nReminder: the following description is only relevant if you in fact want to train your own models. If that's not the case, please check above for links to the dataset and our easy-to-use python package.\n\n\n# Installation\nIt's super easy, we promise! Note that following these instructions is only necessary if you're planning to train a model using our tool. If you only want to predict the sentiment of sentences, please use our [Python package](https://pypi.org/project/NewsSentiment/), which is even easier to install and use :-)\n\nNewsMTSC was tested on MacOS and Ubuntu; other OS may work, too. Let us know :-)\n\n**1. Setup the environment:**\n\nThis step is optional if you have Python 3.8 installed already (`python --version`). If you don't have Python 3.8, we recommend using Anaconda for setting up requirements. If you do not have it yet, follow Anaconda's\n[installation instructions](https://docs.anaconda.com/anaconda/install/). \n\nTo setup a Python 3.8 environment (in case you don't have one yet) you may use, for example:\n```bash\nconda create --yes -n newsmtsc python=3.8\nconda activate newsmtsc\n```\n\nFYI, for users of virtualenv, the equivalent command would be:\n```bash\nvirtualenv -ppython3.8 --setuptools 45 venv\nsource venv/bin/activate\n```\n\nNote: We recommend Python 3.8, however we have successfully tested NewsMTSC with Python version >=3.8, <3.12.\n\n**2. Setup NewsMTSC:**\n```bash\ngit clone git@github.com:fhamborg/NewsMTSC.git\n```\n\nAfterward, for example, open the project in your IDE and follow the instruction described in the section \"Training\".\n\nNote that if you only want to classify sentiment using our model, we recommend that you use our PyPI package [NewsSentiment](https://pypi.org/project/NewsSentiment/). Getting it is as simple as `pip install NewsSentiment` and using it is four lines of code :-)\n\n\n# Training\nIf you want to train one of our models or your own model, please clone the repository first.\n\n\nThere are two entry points to the system. `train.py` is used to train and evaluate a specific model on a specific dataset using\nspecific hyperparameters. We call a single run an _experiment_. `controller.py` is used to run multiple experiments\nautomatically. This is for example useful for model selection and evaluating hundreds or thousands of combinations of\nmodels, hyperparameters, and datasets.\n\n## Running a single experiment\nGoal: training a model with a user-defined (hyper)parameter combination.\n\n`train.py` allows fine-grained control over the training and evaluation process, yet for most command line arguments\nwe provide useful defaults. Two arguments are required:\n\n* `--own_model_name` (which model is used, e.g., `grutsc`),\n* `--dataset_name` (which dataset is used, e.g., `newsmtsc-rw`).\n\nFor more information refer to `train.py` and\n`combinations_absadata_0.py`. If you just want to get started quickly, the command below should work out of the box. \n\n```\npython train.py --own_model_name grutsc --dataset_name newsmtsc-rw\n```\n\n## Running multiple experiments \nGoal: finding the (hyper)parameter combination to train a model that achieves the best performance.\n\n`controller.py` takes a set of values for each argument, creates combinations of arguments, applies conditions to remove\nunnecessary combinations (e.g., some arguments may only be used for a specific model), and creates a multiprocessing\npool to run experiments of these argument combinations in parallel. After completion, `controller.py` creates a summary,\nwhich contains detailed results, including evaluation performance, of all experiments. By using `createoverview.py`, you\ncan export this summary into an Excel spreadsheet.   \n\n# Support\nIf you have questions on how to use NewsMTSC or its library, please create a new [issue](https://github.com/fhamborg/NewsMTSC/issues) on GitHub. Please understand that we are not able to provide individual support via email. We think that help is more valuable if it is shared publicly so that more people can benefit from it.\n\n# Acknowledgements\nThis repository is in part based on [ABSA-PyTorch](https://github.com/songyouwei/ABSA-PyTorch).\nWe thank Song et al. for making their excellent repository open source.\n\n# How to cite\nIf you use the dataset or model, please cite our [paper](https://www.aclweb.org/anthology/2021.eacl-main.142/) ([PDF](https://www.aclweb.org/anthology/2021.eacl-main.142.pdf)):\n\n```\n@InProceedings{Hamborg2021b,\n  author    = {Hamborg, Felix and Donnay, Karsten},\n  title     = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles},\n  booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},\n  year      = {2021},\n  month     = {Apr.},\n  location  = {Virtual Event},\n}\n```\n"
  },
  {
    "path": "READMEpypi.md",
    "content": "# NewsSentiment: easy-to-use, high-quality target-dependent sentiment classification for news articles\nNewsSentiment is an easy-to-use Python library that achieves state-of-the-art performance\nfor target-dependent sentiment classification on news articles.\nNewsSentiment uses the currently [best performing](https://aclanthology.org/2021.eacl-main.142.pdf) \ntargeted sentiment classifier for news articles. In contrast to regular sentiment\nclassification, targeted sentiment classification allows you to provide a target in a sentence. \nOnly for this target, the sentiment is then predicted. This is more reliable in many\ncases, as demonstrated by the following simplistic example: \"I like Bert, but I hate Robert.\"\n\nWe designed NewsSentiment to serve as an easy-to-use wrapper around the sophisticated\nGRU-TSC model, which was trained on the NewsMTSC dataset consisting of more than 10k \nlabeled sentences sampled from political news articles. More information on the dataset \nand the model can be found [here](https://aclanthology.org/2021.eacl-main.142.pdf). The\ndataset, the model, and its source code can be viewed in our [GitHub repository](https://github.com/fhamborg/NewsMTSC).\n\n# Installation\nIt's super easy, we promise! \n\nYou just need a Python 3.8 environment. See [here](https://raw.githubusercontent.com/fhamborg/NewsMTSC/main/pythoninfo.md) if you \ndon't have Python or a different version (run `python --version` in a terminal to see \nyour version). Then run:\n\n```bash\npip3 install NewsSentiment        # without cuda support (choose this if you don't know what cuda is)\npip3 install NewsSentiment[cuda]  # with cuda support\n```\n\nYou're all set now :-)\n\n# Target-dependent Sentiment Classification\n\nNote that using NewsSentiment the first time will take *a few minutes* because it needs\nto download the fine-tuned language model. Please do not abort this initial download. \nSince this is a one-time process, future use of NewsSentiment will be much faster.\n\n```python\nfrom NewsSentiment import TargetSentimentClassifier\ntsc = TargetSentimentClassifier()\n\ndata = [\n    (\"I like \", \"Peter\", \" but I don't like Robert.\"),\n    (\"\", \"Mark Meadows\", \"'s coverup of Trump’s coup attempt is falling apart.\"),\n]\n\nsentiments = tsc.infer(targets=data)\n\nfor i, result in enumerate(sentiments):\n    print(\"Sentiment: \", i, result[0])\n```\n\nThis method will internally split the data into batches of size 16 for increased speed. You can adjust the\nbatch size using the `batch_size` parameter, e.g., `batch_size=32`.\n\nAlternatively, you can also use the `infer_from_text` method to infer sentiment for a single target:\n\n```python\nsentiment = tsc.infer_from_text(\"I like \" ,\"Peter\", \" but I don't like Robert.\")\nprint(sentiment[0])\n```\n\n# How to identify a person in a sentence?\n\nIn case your data is not separated as shown in the examples above, i.e., in three segments, you will need to identify one (or more) targets first.\nHow this is done best depends on your project and analysis task but you may, for example, use NER. This [example](https://github.com/fhamborg/NewsMTSC/issues/30#issuecomment-1700645679) shows a simple way of doing so.\n\n# Acknowledgements\n\nThanks to [Tilman Hornung](https://github.com/t1h0) for adding the batching functionality and various other improvements.\n\n# How to cite\nIf you use the dataset or model, please cite our [paper](https://www.aclweb.org/anthology/2021.eacl-main.142/) ([PDF](https://www.aclweb.org/anthology/2021.eacl-main.142.pdf)):\n\n```\n@InProceedings{Hamborg2021b,\n  author    = {Hamborg, Felix and Donnay, Karsten},\n  title     = {NewsMTSC: (Multi-)Target-dependent Sentiment Classification in News Articles},\n  booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},\n  year      = {2021},\n  month     = {Apr.},\n  location  = {Virtual Event},\n}\n```\n"
  },
  {
    "path": "hubconf.py",
    "content": "from NewsSentiment.models.singletarget.grutscsingle import GRUTSCSingle\n"
  },
  {
    "path": "pyproject.toml",
    "content": "[build-system]\nrequires = [\n  \"setuptools>=45\",\n  \"wheel\"\n]\nbuild-backend = \"setuptools.build_meta\"\n"
  },
  {
    "path": "pythoninfo.md",
    "content": "This step is optional if you have Python >=3.8, <3.12 installed (run `python --version`\nin a terminal and check the version that is printed; we recommend 3.8). If you don't\nhave Python (in the correct version), we recommend using Anaconda for setting up\nrequirements because it is very easy (but any way of installing is fine).\nIf you do not have Anaconda yet, follow their\n[installation instructions](https://docs.anaconda.com/anaconda/install/).\n\nAfter installing Anaconda, to set up a Python 3.8 environment (in case you don't have one\nyet) execute:\n\n```bash\nconda create --yes -n newsmtsc python=3.8\nconda activate newsmtsc\n```\n"
  },
  {
    "path": "setup.cfg",
    "content": "[metadata]\nname = NewsSentiment\nversion = 1.2.28\nauthor = Felix Hamborg\nauthor_email = felix.hamborg@uni-konstanz.de\ndescription = Easy-to-use, high-quality target-dependent sentiment classification for English news articles\nlong_description = file: READMEpypi.md\nlong_description_content_type = text/markdown\nurl = https://github.com/fhamborg/NewsMTSC\nproject_urls =\n    Bug Tracker = https://github.com/fhamborg/NewsMTSC/issues\nclassifiers =\n    Development Status :: 5 - Production/Stable\n    Environment :: Console\n    License :: OSI Approved :: MIT License\n    Operating System :: OS Independent\n    Programming Language :: Python :: 3\n    Programming Language :: Python :: 3.8\n    Programming Language :: Python :: 3.9\n    Programming Language :: Python :: 3.10\n    Programming Language :: Python :: 3.11\n    Intended Audience :: Developers\n    Intended Audience :: Science/Research\n    Topic :: Scientific/Engineering\n    Topic :: Scientific/Engineering :: Information Analysis\n    Topic :: Scientific/Engineering :: Artificial Intelligence\n    Topic :: Text Processing :: Linguistic\n\n[options]\npackage_dir =\n    = .\npackages = find_namespace:\npython_requires = >=3.8, <3.12\n# include_package_data = true\ninstall_requires =\n    boto3>=1.19.7\n    gensim>=4.0.1\n    imbalanced-learn>=0.8.1\n    jsonlines>=2.0.0\n    matplotlib>=3.4.3\n    networkx>=2.6.3\n    openpyxl>=3.0.5\n    pandas>=1.3.3\n    regex>=2021.10.23\n    requests>=2.26.0\n    sacremoses>=0.0.46\n    scikit-learn>=1.0.1\n    spacy>=3.2\n    tabulate>=0.8.9\n    tqdm>=4.62.3\n    transformers>=4.17,<=4.24\n    torch>=1.12,<2.1\n\n[options.packages.find]\nwhere = .\n\n[options.package_data]\n* = *.txt, *.ddict, *.tff, *.gitignore, *.gitkeep\n\n[options.data_files]\ngit =\n    *.gitignore\n\n[options.extras_require]\ncuda =\n    cudatoolkit==10.1\n"
  }
]