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Repository: wasiahmad/paraphrase_identification
Branch: master
Commit: 88b208d0d094
Files: 45
Total size: 156.6 MB
Directory structure:
gitextract_ia7mi6tx/
├── LICENSE
├── README.md
├── dataset/
│ ├── msr-paraphrase-corpus/
│ │ ├── MSR Paraphrase Corpus.lnk
│ │ ├── Microsoft Shared Source License.htm
│ │ ├── Microsoft Shared Source License.rtf
│ │ ├── msr_paraphrase_README.htm
│ │ ├── msr_paraphrase_README.rtf
│ │ ├── msr_paraphrase_data.txt
│ │ ├── msr_paraphrase_test.txt
│ │ └── msr_paraphrase_train.txt
│ ├── msr-video-paraphrase-corpus/
│ │ ├── test-gold.tgz
│ │ ├── train-readme.txt
│ │ ├── train.tgz
│ │ └── trial.tgz
│ ├── mt-metrics-paraphrase-corpus/
│ │ ├── README
│ │ ├── msrp-annotations.csv
│ │ ├── pan-annotations.csv
│ │ ├── pan-test.labels
│ │ ├── pan-test_s1.txt
│ │ ├── pan-test_s2.txt
│ │ ├── pan-train.labels
│ │ ├── pan-train_s1.txt
│ │ └── pan-train_s2.txt
│ └── readme.md
├── source_code_in_theano/
│ ├── data/
│ │ ├── 20_news_group_sentences.txt
│ │ ├── msr_paraphrase_test.txt
│ │ └── msr_paraphrase_train.txt
│ ├── data.py
│ ├── deep_lstm.py
│ ├── input.py
│ ├── lstm.py
│ ├── models/
│ │ ├── backward_double_layer_lstm-2016-12-09-19-49-14000-48-64.dat.npz
│ │ ├── backward_single_layer_lstm-2016-11-30-21-07-14000-48-64.dat.npz
│ │ ├── forward_double_layer_lstm-2016-12-09-19-34-14000-48-64.dat.npz
│ │ ├── forward_single_layer_lstm-2016-12-05-13-04-14000-48-64.dat.npz
│ │ └── model_trained_on_20_news_group_dataset/
│ │ ├── backward_double_layer_lstm-2017-01-07-19-12-20000-64-128.dat.npz
│ │ ├── backward_single_layer_lstm-2017-01-07-19-00-20000-64-128.dat.npz
│ │ ├── forward_double_layer_lstm-2017-01-07-19-06-20000-64-128.dat.npz
│ │ └── forward_single_layer_lstm-2017-01-06-00-44-20000-64-128.dat.npz
│ ├── news_group_data.py
│ ├── readme.md
│ ├── test_lstm.py
│ ├── train_lstm.py
│ └── utils.py
└── state-of-art-details.md
================================================
FILE CONTENTS
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================================================
FILE: LICENSE
================================================
MIT License
Copyright (c) 2016 Wasi Ahmad
Permission 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
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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.
================================================
FILE: README.md
================================================
# Paraphrase-Identification-Task
Paraphrase detection is the task of examining two text entities (ex. sentence) and determining whether they have the same meaning. In order to obtain high accuracy on this task, thorough syntactic and semantic analysis of the two text entities is required.
## What is Paraphrase?
In simple words, paraphrase is just an alternative representation of the same meaning.
## Classification of Paraphrases
According to granularity, paraphrases are of two types.
* Surface Paraphrases
- Lexical level
* Example - ***solve*** and ***resolve***
- Phrase level
* Example - ***look after*** and ***take care of***
- Sentence level
* Example - ***The table was set up in the carriage shed*** and ***The table was laid under the cart-shed***
- Discourse level
* Structural paraphrases
- Pattern level
* Example - ***[X] considers [Y]*** and ***[X] takes [Y] into consideration***
- Collocation level
* Example - ***(turn on, OBJ ligth)*** and ***(switch on, OBJ light)***
According to paraphrase style, they can be classified into five types.
* Trivial Change
* Example - ***all the members of*** and ***all members of***
* Phrase replacement
* Example - ***There will be major cuts in the salaries of high-level civil servants*** and ***There will be major cuts in the salaries of senior officials***
* Phrase reordering
* Example - ***Last night, I saw TOM in the shopping mall*** and ***I saw Tom in the shopping mall last night***
* Sentence split & merge
* Example - ***He baught a computer which is very expensive*** and ***(1) He bought a computer. (2) The computer is very expensive.***
* Complex paraphrase
* Example - ***He said there will be major cuts in the salaries of high-level civil servants*** and ***He claimed to implement huge salary cut to senior civil servants***
## Applications of Paraphrase Identification
* Machine Translation
- Simplify input sentences
- Alleviate data sparseness
* Question Answering
- Question reformulation
* Information Extraction
- IE pattern expansion
* Information Retrieval
- Query reformulation
* Summarization
- Sentence clustering
- Automatic evaluation
* Natural Language Generation
- Sentence rewriting
* Others
- Changing writing style
- Text simplification
- Identifying plagiarism
## Relevant Research Topic
* Textual Entailment
* Semantic Textual Similarity
## Research on Paraphrasing
* Paraphrase identification
* Paraphrase extraction
* Paraphrase generation
* Paraphrase applications
## Paraphrase Identification
* Specially refers to sentential paraphrase identification
- Given any pair of sentences, automatically identifies whether these two sentences are paraphrases
## Overview of Paraphrase Identification Methods
* Classification based methods
* Reviewed as a binary classification problem
* Compute the similarities between two sentences at different levels which are then used as classification features
* Previous works: [Brockett and Dolan, 2005](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/I05-50015B15D.pdf), [Finch et al., 2005](http://www.aclweb.org/anthology/I05-5003), [Malakasiotis, 2009](http://www.aclweb.org/anthology/P09-3004)
* Alignment based methods
* Align the two sentences and score the pair based on the alignment results
* Previous works: [Wu, 2005](http://dl.acm.org/citation.cfm?id=1631867), [Das and Smith, 2009](https://www.aclweb.org/anthology/P/P09/P09-1053.pdf)
More discussion on the previous works are documented [here](https://github.com/wasiahmad/Paraphrase-Identification-Task/blob/master/state-of-art-details.md).
## Reference
* [Paraphrases and Application - Association for Computational Linguistics](http://www.aclweb.org/anthology/C10-4001)
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FILE: dataset/msr-paraphrase-corpus/Microsoft Shared Source License.htm
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\s15\qj \li0\ri0\nowidctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid12744622 \fs21\lang1033\langfe1041\kerning2\loch\af11\hich\af2\dbch\af11\cgrid\langnp1033\langfenp1041 {\loch\af2\insrsid16326027 \hich\af2\dbch\af11\loch\f2 Microsoft
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<div class=Section1>
<p class=MsoNormal align=center style='text-align:center'><b><span lang=EN-US
style='font-size:14.0pt;font-family:Arial'>Microsoft Research Paraphrase Corpus</span></b></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN-US> </span></p>
<p class=MsoNormal align=center style='text-align:center'><b><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Bill Dolan</span></b><b><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>, Chris Brockett, and
Chris Quirk</span></b></p>
<p class=MsoNormal align=center style='text-align:center'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>Microsoft Research</span></b></p>
<p class=MsoNormal align=center style='text-align:center'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>March 2, 2005</span></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>This document provides
some information about the creation of the corpus, along with results of the
annotation effort. If you use the corpus in your research, we would appreciate
your citing one or both of the following papers, which give some details of our
work on paraphrase and our data annotation efforts. (A paper describing in
detail how this corpus was created is currently in progress.) We are continuing
to tag data, and hope to release a larger version of this corpus to the
research community in the future.</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><b><span lang=EN-US
style='font-size:8.5pt;font-family:Verdana'>Quirk, C., C. Brockett, and W. B.
Dolan. 2004. <a
href="http://research.microsoft.com/copyright/accept.asp?path=http://www.research.microsoft.com/nlp/publications/Paraphrase_EMNLP2004.pdf&pub=ACL"><span
style='color:#003399'>Monolingual Machine Translation for Paraphrase Generation</span></a></span></b><span
lang=EN-US style='font-size:8.5pt;font-family:Verdana'>, In <i>Proceedings of
the 2004 Conference on Empirical Methods in Natural Language Processing</i>, Barcelona Spain. </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><b><span lang=EN-US
style='font-size:8.5pt;font-family:Verdana'>Dolan W. B., C. Quirk, and C.
Brockett. 2004. <a
href="http://research.microsoft.com/copyright/accept.asp?path=http://www.research.microsoft.com/nlp/publications/Paraphrase_Coling.pdf&pub=COLING"><span
style='color:#003399'>Unsupervised Construction of Large Paraphrase Corpora:
Exploiting Massively Parallel News Sources</span></a></span></b><span
lang=EN-US style='font-size:8.5pt;font-family:Verdana'>. <i>COLING 2004</i>, Geneva, Switzerland. </span></p>
<p class=MsoNormal><span lang=EN-US> </span></p>
<p class=MsoNormal style='margin-left:21.25pt;text-indent:-21.25pt'><b><i><span
lang=EN-US style='font-size:14.0pt;font-family:Arial'>1.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-size:14.0pt;
font-family:Arial'>Introduction to the paraphrase tagging task</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>This dataset consists of
5801 pairs of sentences gleaned over a period of 18 months from thousands of
news sources on the web. Accompanying each pair is judgment reflecting whether multiple
human annotators considered the two sentences to be close enough in meaning to
be considered close paraphrases.</span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Each pair of sentences
has been examined by 2 human judges who were asked to give a binary judgment as
to whether the two sentences could be considered semantically equivalent.
Disagreements were resolved by a 3rd judge. This annotation task was carried
out by an independent company, the Butler Hill Group, LLC. Mo Corston-Oliver
directed the effort, with Jeff Stevenson, Amy Muia, and David Rojas acting as
raters. Mo Corston-Oliver and Jeff Stevenson also helped with the preparation
of this document.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>After resolving
differences between raters, </span><span lang=EN-US>3900 </span><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>(67%) of the original </span><span
lang=EN-US>5801 </span><span lang=EN-US style='font-size:10.0pt;font-family:
Arial'>pairs were judged semantically equivalent.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>In many instances, the
pair of sentences rated by 2 judges as semantically equivalent will in fact
diverge semantically to at least some degree. If a full paraphrase relationship
can be described as bidirectional entailment, then the majority of the
equivalent pairs in this dataset exhibit mostly bidirectional entailments,
with one sentence containing information that differs from or is not contained
in the other. Some specific rating criteria are included in a tagging
specification (Section 3), but by and large the degree of mismatch allowed
before the pair was judged non-equivalent was left to the discretion of the
individual rater: did a particular set of asymmetries alter the meanings of the
sentences enough that they couldnt be considered the same in meaning? This
task was ill-defined enough that we were surprised at how high interrater
agreement was (averaging 83%). </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>A series of experiments
aimed at making the judging task more concrete resulted in uniformly degraded interrater
agreement. Providing a checkbox to allow judges to specify that one sentence
entailed another, for instance, left the raters frustrated and had a negative
impact on agreement. Similarly, efforts to identify classes of syntactic
alternations that would not count against an equivalent judgment resulted, in
most cases, in a collapse in interrater agreement. The relatively few situations
where we found firm guidelines of this type to be helpful (e.g. in dealing with
anaphora) are included in Section 3.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>The decision to tag
sentences as being more or less semantically equivalent, rather than
semantically equivalent was ultimately a practical one: insisting on complete
sets of bidirectional entailments would have ruled out all but the most trivial
sorts of paraphrase relationships, such as sentence pairs differing only a
single word or in the presence of titles like Mr. and Ms.. Our interest was
in identifying more complex paraphrase relationships, which required a somewhat
looser definition of what semantic equivalence means. In an effort to focus
on these more interesting pairs, the dataset was restricted to pairs with a
minimum word-based Levenshtein distance of </span><span lang=EN-US
style='font-size:10.0pt;font-family:"Franklin Gothic Medium"'>≥</span><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'> 8.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Given our relatively
loose definition of equivalence, any 2 of the following sentences would probably
have been considered paraphrases, despite obvious differences in information
content:</span></p>
<p class=MsoNormal><span lang=EN-US> </span></p>
<p class=MsoNormal style='margin-left:36.0pt;text-align:justify;text-justify:
inter-ideograph;text-indent:-36.0pt;page-break-after:avoid;layout-grid-mode:
char'><span lang=EN-US style='font-size:10.0pt;font-family:Symbol;color:black'><span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:black'>The genome of the fungal pathogen that causes Sudden Oak Death has
been sequenced by US scientists</span></p>
<p class=MsoNormal style='margin-left:36.0pt;text-align:justify;text-justify:
inter-ideograph;text-indent:-36.0pt;page-break-after:avoid;layout-grid-mode:
char'><span lang=EN-US style='font-size:10.0pt;font-family:Symbol;color:black'><span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:black'>Researchers announced Thursday they've completed the genetic
blueprint of the blight-causing culprit responsible for sudden oak death</span></p>
<p class=MsoNormal style='margin-left:36.0pt;text-align:justify;text-justify:
inter-ideograph;text-indent:-36.0pt;page-break-after:avoid;layout-grid-mode:
char'><span lang=EN-US style='font-size:10.0pt;font-family:Symbol;color:black'><span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:black'>Scientists have figured out the complete genetic code of a
virulent pathogen that has killed tens of thousands of California native oaks</span></p>
<p class=MsoNormal style='margin-left:36.0pt;text-align:justify;text-justify:
inter-ideograph;text-indent:-36.0pt;layout-grid-mode:char'><span lang=EN-US
style='font-size:10.0pt;font-family:Symbol;color:black'><span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:black'>The East Bay-based Joint Genome Institute said Thursday it has
unraveled the genetic blueprint for the diseases that cause the sudden death of
oak trees</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Raters were presented
with sentences in which several classes of named entities were replaced by
generic tags, so that Tuesday became %%DAY%%, $10,000 became %%MONEY%%,
and so on. The release versions, however, preserve the original strings.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Note that many of the
sentence pairs judged to be <b>not equivalent</b> will still overlap
significantly in information content and even wording. A variety of automatic
filtering techniques were used to create an initial dataset that was rich in
paraphrase relationships, and the success of these techniques meant that
approximately 70% of the pairs examined by raters were, by our criteria,
semantically equivalent. The remaining 30% represent a range of relationships,
from pairs that are completely unrelated semantically, to those that are
partially overlapping, to those that are almost-but-not-quite semantically
equivalent. For this reason, this <b>not equivalent</b> set should not be
used as negative training data.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>We have made every effort
to ensure that each sentence in this dataset has been given proper attribution.
If you encounter any errors/omissions, please contact Bill Dolan (<a
href="mailto:billdol@microsoft.com">billdol@microsoft.com</a>), and we will
promptly modify the data to reflect the correct information.</span></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-size:14.0pt;
font-family:Arial'><span style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-size:14.0pt;
font-family:Arial'><span style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-size:14.0pt;
font-family:Arial'><span style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-size:14.0pt;
font-family:Arial'><span style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal style='margin-left:21.25pt;text-indent:-21.25pt'><b><i><span
lang=EN-US style='font-size:14.0pt;font-family:Arial'>2.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-size:14.0pt;
font-family:Arial'>Methodology and Results</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>This
data set consists of 5801 sentence pairs, with a binary human judgment of
whether or not the pairing constitutes a paraphrase.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>2.1.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Methodology</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>To generate the
judgments, we used 3 raters to score the sentence pairs according to a given
specification. Rater 1 scored all 5801 sentences. Rater 2 scored 3533
sentences, and Rater 3 scored 2268 sentences. For the sentences where Rater 1
and 2 did not agree on the judgment, Rater 3 gave a final judgment, while Rater
2 gave the final judgment on sentences where Rater 1 and Rater 3 did not agree.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>2.2.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Interrater
Agreement</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>To
test interrater agreement, we took a simple percentage:</span></p>
<p class=MsoNormal style='page-break-after:avoid'><span lang=EN-US> </span></p>
<div align=center>
<table class=MsoTableGrid border=1 cellspacing=0 cellpadding=0
style='border-collapse:collapse;border:none'>
<tr>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-left:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Total
scored</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-left:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Total
agreements</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-left:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Percentage
agreement</span></p>
</td>
</tr>
<tr>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-top:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Raters
1 & 2</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>3533</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>2904</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>82.20</span></p>
</td>
</tr>
<tr>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-top:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Raters
1 & 3</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>2268</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>1921</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>84.70</span></p>
</td>
</tr>
</table>
</div>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>2.3.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Overall
scoring results</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>We
computed scoring results for each individual (raw scores, before resolving</span><span
lang=EN-US> differences):</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<div align=center>
<table class=MsoTableGrid border=1 cellspacing=0 cellpadding=0
style='border-collapse:collapse;border:none'>
<tr>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-left:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Total
scored</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-left:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Number
yes</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-left:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Percentage
yes</span></p>
</td>
</tr>
<tr>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-top:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Rater
1</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>5801</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>3601</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>62.08</span></p>
</td>
</tr>
<tr>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-top:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Rater
2</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>3533</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>2589</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>73.28</span></p>
</td>
</tr>
<tr>
<td width=148 valign=top style='width:88.55pt;border:solid windowtext 1.0pt;
border-top:none;padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Rater
3</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>2268</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>1612</span></p>
</td>
<td width=148 valign=top style='width:88.55pt;border-top:none;border-left:
none;border-bottom:solid windowtext 1.0pt;border-right:solid windowtext 1.0pt;
padding:0cm 5.4pt 0cm 5.4pt'>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>71.08</span></p>
</td>
</tr>
</table>
</div>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>After resolving
differences, we judged 3900 out of 5801 sentence pairs to be valid paraphrases,
for a final percentage of 67.23%</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:28.1pt;text-indent:-28.1pt;page-break-after:
avoid'><b><i><span lang=EN-US style='font-family:Arial'>2.4.<span
style='font:7.0pt "Times New Roman"'> </span></span></i></b><b><i><u><span
lang=EN-US style='font-family:Arial'>Test/training</span></u></i></b></p>
<p class=MsoNormal style='page-break-after:avoid'><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>We assigned a random
sequence ID to each sentence pair, sorted them, and assigned the first 30% of
the data to be training and the last 70% to be test data. For obscure technical
reasons, the final test/train percentage is inexact (29.7% (1725 sentence
pairs) vs. 70.3% (4076 sentence pairs))</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><b><span lang=EN-US style='font-size:14.0pt'> </span></b></p>
<p class=MsoNormal style='margin-left:21.25pt;text-indent:-21.25pt'><b><i><span
lang=EN-US style='font-family:Arial'>3.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-size:14.0pt;
font-family:Arial'>Detailed Tagging Guidelines</span></u></i></b><b><i><u><span
lang=EN-US style='font-family:Arial'> </span></u></i></b></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-family:Arial'><span
style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-family:Arial'><span
style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>3.1.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Equivalent
vs. not equivalent content</span></u></i></b></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-family:Arial'><span
style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal style='margin-left:36.0pt;text-indent:-36.0pt'><span
lang=EN-US style='font-size:10.0pt;font-family:Symbol'><span style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>In
this task, we are trying to determine if two sentences express the same
content.</span></p>
<p class=MsoNormal style='margin-left:36.0pt;text-indent:-36.0pt'><span
lang=EN-US style='font-size:10.0pt;font-family:Symbol'><span style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>As is
true for paraphrase in general, this may be realized by means of alternative
but similar syntactic constructions and lexical items, etc.</span></p>
<p class=MsoNormal style='margin-left:36.0pt;text-indent:-36.0pt'><span
lang=EN-US style='font-size:10.0pt;font-family:Symbol'><span style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>In
general, the standard as to whether two sentences express the same content should
be relatively high, meaning that many of ambiguous cases should be marked
"<b>not equivalent</b>" rather than "<b>equivalent</b>".</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Examples
of sentences with <b>equivalent</b> content expressed via alternative lexical
items:</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>The Senate Select
Committee on Intelligence is preparing a blistering report on <b>prewar
intelligence </b>on Iraq.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>American <b>intelligence
leading up to the war</b> on Iraq will be criticised by a powerful US Congressional committee due to report soon, officials said today.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:black'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:black'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>A strong geomagnetic
storm was expected to hit Earth today <b>with the potential to affect</b>
electrical grids and satellite communications.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>A strong geomagnetic
storm is expected to hit Earth sometime %%DAY%% and <b>could knock out</b>
electrical grids and satellite communications.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'>These sentences are clearly paraphrases. The different lexical
items are still expressing the same content. </span><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>This type of sentence pair should be
tagged as <b>equivalent</b>.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>3.2.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Equivalent
sentence pairs with minor differences in content</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Minor differences between
sentences can be overlooked when determining if two sentences are paraphrases.
For example:</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>An autopsy found
Hatab's death was caused by "strangulation/asphyxiation," Rawson said
%%DAY%%.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>An autopsy found that
Nagem Sadoon Hatab's death on %%DATE%% was caused by "strangulation/asphyxiation,
Marine spokesman %%NUMBER%% st Lt. Dan Rawson said %%DAY%%.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>The
following sentences also express <b>equivalent</b> content:</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:blue'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>Mr. Concannon</span></b><span
lang=EN-US style='font-size:10.0pt;font-family:Courier;color:black'> <u>had
been doused in petrol</u>, <b>set himself alight</b> and <b>jumped onto a bike
to leap</b> <u>eight metres</u> <b>onto a mattress</b> below.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:blue'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>A SYDNEY man</span></b><span
lang=EN-US style='font-size:10.0pt;font-family:Courier;color:black'> <u>suffered
serious burns</u> <b>after setting himself alight</b> before <b>attempting to
jump a BMX bike</b> <u>off a toilet block</u> <b>into a pile of mattresses</b>
, </span><b><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:red'>police said</span></b><span lang=EN-US style='font-size:10.0pt;
font-family:Courier;color:black'>.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial;color:black'>The agent (<i>Mr.
Concanon</i>), the predicated actions (<i>set himself alight, jumped a bike</i>),
and important details (<i>onto a pile of mattresses</i>) are present in both
sentences. Additional lexical material in either sentence mainly serves to
embellish the main propositions (for example, . . .<i>suffered serious burns</i>
which is logically entailed by <i>set himself alight</i>). Also notice that
the details of a given proposition need not be exact: <i>a mattress </i>(sing.)
vs. <i>a pile of mattresses</i> (plur.). </span><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>Finally, notice that the second of
the sentence pairs in the previous example is attributed to the police where
the first is not. This difference between sentences is also acceptable for
purposes of tagging them as paraphrases.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>For this type of sentence
pair, we want to mark them as equivalent (paraphrases). Notice that the
sentence pairs, while clearly similar overall in content, <i>both</i> differ in
additional, modifying content.. As the main content of the sentences similar in
meaning, we allow some minor content mismatch.</span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>3.3.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Anaphora</span></u></i></b></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US></span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Sometimes the difference between
two sentences involves anaphora (NPs and pronominal). These sentences can be
tagged as paraphrases despite the (sometimes) fairly large gap between them in
terms of their corresponding full-form NPs</span><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>. Examples follow.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.3.1.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><span lang=EN-US style='font-size:10.0pt'> Demonstratives</span></i></b></h3>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>But Secretary of State Colin
Powell brushed off <b>this possibility</b> %%day%%.</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>Secretary of State Colin Powell
last week ruled out <b>a non-aggression treaty</b>.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.3.2.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><span lang=EN-US style='font-size:10.0pt'>NP ->
pro</span></i></b></h3>
<p class=MsoNormal style='page-break-after:avoid'><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>Meteorologists predicted <b>the
storm</b> would become a category %%number%% hurricane before landfall.</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>It</span></b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> was predicted to become a
category 1 hurricane overnight.</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'> </span></i></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.3.3.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><span lang=EN-US style='font-size:10.0pt'> <b><i>Proper
NP (+animate) -> pro</i></b></span></h3>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>Earlier, <b>he </b>told France
Inter-Radio , ''I think we can now qualify what is happening as a genuine
epidemic.''</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>''I think we can now qualify what
is happening as a genuine epidemic,'' <b>he<i>alth minister Jean-Francois
Mattei </i></b><i>said on France Inter Radio.</i></span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.3.4.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><span lang=EN-US style='font-size:10.0pt'>Title +
proper NP (+animate) -> pro</span></i></b></h3>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-size:10.0pt;
font-family:Arial'><span style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>''United is continuing to deliver
major cost reductions and is now coupling that effort with significant unit
revenue improvement, '' <b>chief financial officer Jake Brace</b> said in a statement.</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>''United is continuing to deliver
major cost reductions and is now coupling that effort with significant unit
revenue improvement,'' <b>he</b> said.</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'> </span></i></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.3.5.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><span lang=EN-US style='font-size:10.0pt'> <b><i>NP
(-animate) -> pro</i></b></span></h3>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>''Spoofing</span></b><span
lang=EN-US style='font-size:10.0pt;font-family:Courier'> is a problem faced by
any company with a trusted domain name that uses e-mail to communicate with its
customers.</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:36.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>It</span></b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> is a problem for Amazon and
others that have a trusted domain name and use e-mail to communicate with
customers.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><b><i><u><span lang=EN-US style='font-family:Arial'><span
style='text-decoration:none'> </span></span></u></i></b></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>3.4.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Inherent
ambiguity of the task</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>The relatively
holistic/vague criteria established above should work well for most sentence
pairs. In the end, were tagging something thats not quite paraphrase, but
something like semantic near-equivalence sentences pairs that ideally
involve complete sets of bidirectional entailments, but which in fact often
have some entailment asymmetries or other mismatches. The issue here is when
those asymmetries/differences become significant enough to make the pair
different enough that you dont think they mean more or less the same thing
anymore, where more or less becomes a personal judgment call.</span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:1.0cm;text-indent:-1.0cm'><b><i><span
lang=EN-US style='font-family:Arial'>3.5.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-family:Arial'>Sentence
pairs with different content</span></u></i></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'> </span></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.5.1.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><u><span lang=EN-US style='font-size:10.0pt'></span></u></i></b><b><i><span
lang=EN-US style='font-size:10.0pt'>Different content: prototypical example</span></i></b></h3>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'>In contrast to the examples above, the following sentences clearly
express <b>different</b> content:</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:27.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>Prime Minister
Junichiro Koizumi</span></b><span lang=EN-US style='font-size:10.0pt;
font-family:Courier;color:black'> did not have to dissolve </span><b><span
lang=EN-US style='font-size:10.0pt;font-family:Courier;color:red'>parliament</span></b><span
lang=EN-US style='font-size:10.0pt;font-family:Courier;color:black'> until next
summer , when elections for the upper house are also due .</span></p>
<p class=MsoNormal style='margin-left:27.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:27.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>Prime Minister
Junichiro Koizumi</span></b><span lang=EN-US style='font-size:10.0pt;
font-family:Courier;color:black'> has urged </span><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:red'>Nakasone</span></b><span
lang=EN-US style='font-size:10.0pt;font-family:Courier;color:black'> to give up
his seat in accordance with the new age rule .</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>While the principal agent
(<i><span style='color:black'>Koizumi</span></i><span style='color:black'>)<b> </b>is
the same, predicated actions, i.e. verbs (<i>dissolve / urge</i>) and other
arguments (<i>parliament / Nakasone</i>) are clearly different. The additional
material found in either sentence does not embellish the main proposition but
instead contains important content itself. These two sentence pairs should be
marked as <b>not equivalent</b> in that while they share an agent Koizumi,
they are about unrelated events. Again, </span>ambiguous cases should be marked
"<b>not equivalent</b>" rather than "<b>equivalent</b>.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.5.2.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><span lang=EN-US style='font-size:10.0pt'>Shared
content of the same event, etc. but lacking details (one sentence is a superset
of the other)</span></i></b></h3>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:27.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>Researchers have
identified a genetic pilot light for puberty in both mice and humans .</span></p>
<p class=MsoNormal style='margin-left:27.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'> </span></p>
<p class=MsoNormal style='margin-left:27.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>The discovery of a
gene that appears to be a key regulator of puberty in humans and mice <b>could
lead to new infertility treatments and contraceptives</b>.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial;color:black'>These
sentences are similar in content, refer to a similar key piece of information,
but cannot be marked as <b>equivalent</b>. The sentences should be tagged as
<b>not equivalent</b> because even though the </span><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>content of the sentences is similar,
one sentence is a significantly larger superset of the other: all the content
of the first sentence is in the second, but not vice-versa. The superset
sentence contains important content information (above, in bold) not present in
the second sentence.</span></p>
<p class=MsoNormal><b><span lang=EN-US style='font-size:10.0pt;font-family:
Arial'> </span></b></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'>Some
similar sentence pairs follow (missing content in superset sentence is in
bold):</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'> </span></i></p>
<p class=MsoNormal style='margin-left:18.0pt'><u><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>SOME %%NUMBER%% jobs</span></u><span
lang=EN-US style='font-size:10.0pt;font-family:Courier'> are set to go at
Cadbury Schweppes , the confectionery and drinks giant , <b>as part of a
sweeping cost reduction programme announced today .</b></span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>Confectionery group Cadbury
Schweppes has warned of further cuts to <u>its %%NUMBER%% -strong UK workforce</u> .</span></p>
<p class=MsoNormal><i><span lang=EN-US style='font-size:10.0pt;font-family:
Arial;color:navy'> </span></i></p>
<p class=MsoNormal style='margin-left:18.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial;color:black'> </span></i></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial;color:black'>This sentence
is difficult in that, while one sentence is a superset of the other, it is <i>also</i>
arguably the case that the sentences are almost paraphrases except when we
see that</span><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> the
content of the underlined portions in the two sentences above is exclusive to
one sentence. In the end, however, the material in bold is an important
difference in content between the sentences, and adds important additional
content, leading us to prefer tag them as <b>not equivalent</b>.</span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Please use your best
judgment in choosing to tag sentences as <b>equivalent</b> or <b>not
equivalent</b>. Many of the sentence pairs you see differ due to the way
editors eliminate language/content they deem unnecessary. Sometimes the two
sentences will differ in information that conveys important additional
information. Sentences like these should be tagged as <b>not equivalent</b>:</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial;
color:black'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>The former wife of
rapper Eminem has been electronically tagged after missing two court
appearances .</span></p>
<p class=MsoNormal style='margin-left:36.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:navy'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>After missing two
court appearances <b>in a cocaine possession case</b> , Eminem's ex-wife has
been placed under electronic house arrest .</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial;color:black'> </span></i></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>The issue of whether or
not the extra/missing information is significant enough to warrant treating the
sentences as not equivalent amounts to a judgment call. Minor differences
between sentences can be overlooked when determining if two sentences are
paraphrases. As seen in a previous example sentence pair, the only differences
in content between the following sentences are the reduced forms of names and
adverbial modifiers (dates). <span style='color:black'>There are no major
differences in content between these sentences. They can be marked as <b>equivalent</b>.</span></span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>An autopsy found
Hatab's death was caused by "strangulation/asphyxiation," Rawson said
%%DAY%% .</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>An autopsy found that
Nagem Sadoon Hatab's death <b>on %%DATE%%</b> was caused by "
strangulation/asphyxiation , " Marine spokesman %%NUMBER%% st Lt. Dan
Rawson said %%DAY%%.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial;color:black'> </span></i></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>The role of content
asymmetries in determining whether sentences should be marked as equivalent/not
equivalent is also linked to sentence length. In a pair of 20-word sentences,
the presence/absence of a single modifier might be lost in the noise, while in
a pair of 5 word sentences it might take on much greater significance. There is
no good way to normalize for length in such cases, so again, just depend on
your own judgment.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial;color:black'> </span></i></p>
<p class=MsoNormal><b><span lang=EN-US style='font-size:10.0pt;font-family:
Arial'> </span></b></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.5.3.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><span lang=EN-US style='font-size:10.0pt'>Cannot
determine if sentences refer to the same event</span></i></b></h3>
<p class=MsoNormal><b><span lang=EN-US style='font-size:10.0pt;font-family:
Arial'> </span></b></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>More than <b>%%NUMBER%%
acres</b> burned and more than %%NUMBER%% homes were destroyed in the <b>massive</b>
Cedar <b>Fire</b> .</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><b><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>Major fires</span></b><span
lang=EN-US style='font-size:10.0pt;font-family:Courier'> had burned <b>%%NUMBER%%
acres</b> by early last night.</span></p>
<p class=MsoNormal><i><span lang=EN-US style='font-size:10.0pt;font-family:
Arial'> </span></i></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>In this example, both
sentences could be about the same series of events (fires). However, these are
possibly about two events: one is about a specific fire, the other about a
cluster of fires. This should lead us to annotate these sentences as expressing
<b>not equivalent</b> content. Another such example follows:</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>The spokeswoman said four soldiers
were wounded in the attack, which took place just before noon around %%NUMBER%%
km ( %%NUMBER%% miles ) north of the capital Baghdad.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'>Two US soldiers were killed in a
mortar attack near the Iraqi town of Samarra yesterday , a US military spokeswoman said.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>Notice that both
sentences report the deaths of soldiers in an attack in <i>some</i> Iraqi town.
However, it is clear that the two sentences could be describing two isolated
events. The fact that there is a discrepancy in the number of reported deaths
should add to ones suspicions that this might be the case. Since the sentences
share some content, but we cannot be sure they refer to the same event, we
should seek to err on the side of caution and mark them as <b>not equivalent</b>.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.5.4.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><span lang=EN-US style='font-size:10.0pt'>Shared
content but different rhetorical structure</span></i></b></h3>
<p class=MsoNormal><i><span lang=EN-US style='font-size:10.0pt;font-family:
Arial;color:black'> </span></i></p>
<p class=MsoNormal style='margin-left:12.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>The <b>search feature</b>
works with around <b>%%NUMBER%% titles</b> from <b>%%NUMBER%% publishers</b>,
which translates into some <b>%%NUMBER%% million pages</b> of searchable text .</span></p>
<p class=MsoNormal style='margin-left:12.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'> </span></p>
<p class=MsoNormal style='margin-left:12.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>This innovative <b>search
feature</b> lets Amazon customers search the full text of a title to find a
book , supplementing the existing search by author or title .</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>In this sentence pair,
both sentences clearly make statements about a new search feature. However,
notice the emphasis placed on the amount of data in the first sentence via the
rhetorical device of reiterated citation of numbers. </span><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>The two sentences are about the same
subject matter, but they are significantly different in that the first might
occur as a detailed exploration of the second</span><span lang=EN-US
style='font-size:10.0pt;font-family:Arial'>. Therefore, this leads us to mark
the sentences as <b>not equivalent</b>.</span></p>
<p class=MsoNormal><b><span lang=EN-US style='font-size:10.0pt;font-family:
Arial'> </span></b></p>
<h3 style='margin-left:35.45pt;text-indent:-35.45pt'><b><i><span lang=EN-US
style='font-size:10.0pt'>3.5.5.<span style='font:7.0pt "Times New Roman"'>
</span></span></i></b><b><i><span lang=EN-US style='font-size:10.0pt'>Same
event but details different emphasis</span></i></b></h3>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>A Hunter Valley woman sentenced to %%NUMBER%% years jail for killing her four babies was only a
danger to children in her care, a court was told.</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>As she stood up
yesterday to receive a sentence of %%NUMBER%% years for killing her four
babies, Kathleen Folbigg showed no emotion.</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>These sentences clearly
report information related to the same event, but the first sentence emphasizes
a particular legal argument presented by the convicted womans lawyer, while
the second focuses on her apparent mental state at the trial. This type of
sentence pair should be tagged as <b>not equivalent</b>. Given the magnitude
of the semantic divergence between these two sentences both in terms of
content and emphasis they should be treated as not equivalent.</span></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><i><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></i></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial'>More example sentence
pairs which, while clearly significantly overlapping in content, should be
tagged as <b>not equivalent</b>:</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Arial'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>Authorities dubbed the
investigation Operation Rollback , a reference to Wal-Mart's name for price
reductions .</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Courier;
color:black'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>The ICE's
investigation , known as " Operation Rollback " , targeted workers at
%%NUMBER%% Wal-Mart stores in %%NUMBER%% states .</span></p>
<p class=MsoNormal><span lang=EN-US style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>Researchers also found
that women with mutations in the BRCA1 or BRCA2 gene have a %%NUMBER%% % to
%%NUMBER%% % risk of ovarian cancer , depending on which gene is affected .</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier'> </span></p>
<p class=MsoNormal style='margin-left:18.0pt'><span lang=EN-US
style='font-size:10.0pt;font-family:Courier;color:black'>Earlier studies had
suggested that the breast cancer risk from the gene mutations ranged from
%%NUMBER%% % to %%NUMBER%% % .</span></p>
<p class=MsoNormal style='margin-left:18.0pt'><i><span lang=EN-US
style='font-size:10.0pt;font-family:Arial;color:black'> </span></i></p>
<p class=MsoNormal style='text-align:justify;text-justify:inter-ideograph'><span
lang=EN-US style='font-size:10.0pt;font-family:Arial;color:black'>Note that
while the sentences may refer to the same piece of information, the inclusion
of <i>earlier studies.</i> suggests this may not be the case. Therefore,
they should be tagged as <b>not equivalent</b>.</span></p>
</div>
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</html>
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{\leveltext\'04\'00.\'01.;}{\levelnumbers\'01\'03;}\fi-567\li567\jclisttab\tx567\lin567 }{\listlevel\levelnfc0\levelnfcn0\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\'06\'00.\'01.\'02.;}{\levelnumbers\'01\'03\'05;}
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}{\listlevel\levelnfc23\levelnfcn23\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\leveltemplateid67698691\'01o;}{\levelnumbers;}\f2\fbias0 \fi-360\li3600\jclisttab\tx3600\lin3600 }{\listlevel\levelnfc23\levelnfcn23
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{\leveltext\leveltemplateid67698693\'01{\uc1\u-3929 ?};}{\levelnumbers;}\f10\fbias0 \fi-360\li6480\jclisttab\tx6480\lin6480 }{\listname ;}\listid610820163}{\list\listtemplateid-147130004{\listlevel\levelnfc23\levelnfcn23\leveljc0\leveljcn0\levelfollow0
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{\leveltext\'01o;}{\levelnumbers;}\f2\fs20\fbias0 \fi-360\li1440\jclisttab\tx1440\lin1440 }{\listlevel\levelnfc23\levelnfcn23\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\'01{\uc1\u-3929 ?};}{\levelnumbers;}
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\'01{\uc1\u-3929 ?};}{\levelnumbers;}\f10\fs20\fbias0 \fi-360\li6480\jclisttab\tx6480\lin6480 }{\listname ;}\listid679893778}{\list\listtemplateid-829655036{\listlevel\levelnfc0\levelnfcn0\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0
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\'01\'03;}\ulnone\fbias0 \fi-555\li555\jclisttab\tx555\lin555 }{\listlevel\levelnfc0\levelnfcn0\leveljc0\leveljcn0\levelfollow0\levelstartat3\levelspace0\levelindent0{\leveltext\'05\'00.\'01.\'02;}{\levelnumbers\'01\'03\'05;}\ulnone\fbias0 \fi-720\li720
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\'06\'00.\'01.\'02.;}{\levelnumbers\'01\'03\'05;}\fbias0 \fi-709\li709\jclisttab\tx709\lin709 }{\listlevel\levelnfc0\levelnfcn0\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\'08\'00.\'01.\'02.\'03.;}{\levelnumbers
\'01\'03\'05\'07;}\fbias0 \fi-851\li851\jclisttab\tx851\lin851 }{\listlevel\levelnfc0\levelnfcn0\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\'0a\'00.\'01.\'02.\'03.\'04.;}{\levelnumbers\'01\'03\'05\'07\'09;}\fbias0
\fi-992\li992\jclisttab\tx992\lin992 }{\listlevel\levelnfc0\levelnfcn0\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\'0c\'00.\'01.\'02.\'03.\'04.\'05.;}{\levelnumbers\'01\'03\'05\'07\'09\'0b;}\fbias0 \fi-1134\li1134
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{\leveltext\'02\'00.;}{\levelnumbers\'01;}\fbias0 \fi-425\li425\jclisttab\tx425\lin425 }{\listlevel\levelnfc0\levelnfcn0\leveljc0\leveljcn0\levelfollow0\levelstartat1\levelspace0\levelindent0{\leveltext\'04\'00.\'01.;}{\levelnumbers\'01\'03;}\fbias0
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\par }{\b\f1\fs20\insrsid2237966\charrsid11557177 \hich\af1\dbch\af11\loch\f1 Bill Dolan, Chris Brockett, and Chris Quirk
\par }{\b\f1\fs20\insrsid2313633\charrsid11557177 \hich\af1\dbch\af11\loch\f1 Microsoft Research
\par \hich\af1\dbch\af11\loch\f1 March 2, 2005
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This document provides some information about the creation of the corpus, along with results of the annotation effort. If you use the}{\f1\fs20\insrsid2313633\charrsid13436006 \hich\af1\dbch\af11\loch\f1 corpus\hich\af1\dbch\af11\loch\f1
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\hich\af1\dbch\af11\loch\f1 give some details of our work on paraphrase and our data annotation efforts. (A paper describing in detail how }{\f1\fs20\insrsid2313633\charrsid13436006 \hich\af1\dbch\af11\loch\f1 this corpus }{\f1\fs20\insrsid11218914
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We are continuing to tag data, and hope to release a larger version of this corpus to the research community in the future.}{\f1\fs20\insrsid2313633\charrsid11218914
\par }\pard \ql \li720\ri0\sb100\sa100\sbauto1\saauto1\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin720\itap0\pararsid2305248 {\b\f43\fs17\insrsid2956143 \hich\af43\dbch\af11\loch\f43 Quirk, C., C. Brockett, and W. B. Dolan. 2004. }
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\hich\af43\dbch\af11\loch\f43 , In }{\i\f43\fs17\insrsid2956143 \hich\af43\dbch\af11\loch\f43 Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing}{\f43\fs17\insrsid2956143 \hich\af43\dbch\af11\loch\f43
, Barcelona Spain.
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\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc1\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrstop18\pnrstart3\pnrpnbr1\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrstop36\adjustright\rin0\lin425\itap0\pararsid5514607
{\b\i\f1\fs28\ul\insrsid6293529\charrsid3153308 \hich\af1\dbch\af11\loch\f1 Introduction to the paraphrase tagging task}{\b\i\f1\fs28\ul\insrsid6293529
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid6293529 {\f1\fs20\insrsid12675160\charrsid9787409
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 This }{\f1\fs20\insrsid3691716 \hich\af1\dbch\af11\loch\f1 dataset}{
\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 }{\f1\fs20\insrsid15010443 \hich\af1\dbch\af11\loch\f1 consists of 5801}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1
pairs of sentences gleaned over a period of 18 months from thousa}{\f1\fs20\insrsid12675160\charrsid9787409 \hich\af1\dbch\af11\loch\f1 nds of news sources on the web.}{\f1\fs20\insrsid2569839 \hich\af1\dbch\af11\loch\f1 }{
\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 Accompanying each pa\hich\af1\dbch\af11\loch\f1 ir is judgment reflecting whether }{\f1\fs20\insrsid10960926 \hich\af1\dbch\af11\loch\f1 multiple }{
\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 human annotators considered the two sentences to be close enough in meaning to be considered close paraphrases.}{\f1\fs20\insrsid12675160\charrsid9787409
\par
\par }{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 Each pair of sentences has been examined by 2 human judges who were asked to give a binary judgment \hich\af1\dbch\af11\loch\f1 as to whether the two sentences }{
\f1\fs20\insrsid10764822 \hich\af1\dbch\af11\loch\f1 \hich\f1 could be considered \'93\loch\f1 \hich\f1 semantically equivalent\'94}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1
. Disagreements were resolved by a 3rd judge. This annotation task was carried out by an independent company, the Butler Hill Group}{\f1\fs20\insrsid3362214 \hich\af1\dbch\af11\loch\f1 , LLC}{\f1\fs20\insrsid6293529\charrsid9787409
\hich\af1\dbch\af11\loch\f1 . Mo Corston-Oliver directed the effort, wi\hich\af1\dbch\af11\loch\f1 th Jeff Stevenson, Amy Muia, and David Rojas acting as raters.}{\f1\fs20\insrsid9787409 \hich\af1\dbch\af11\loch\f1 }{\f1\fs20\insrsid4614938
\hich\af1\dbch\af11\loch\f1 Mo Corston-Oliver and Jeff Stevenson also helped with the preparation of this document.}{\f1\fs20\insrsid6293529
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid6293529 {\f1\fs20\insrsid3691716\charrsid9787409
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid3691716 \hich\af1\dbch\af11\loch\f1 After resolving differences between raters, }{\insrsid3691716 \hich\af0\dbch\af11\loch\f0 3900 }{
\f1\fs20\insrsid3691716 \hich\af1\dbch\af11\loch\f1 (67%) of the }{\f1\fs20\insrsid12335180 \hich\af1\dbch\af11\loch\f1 original }{\insrsid3691716 \hich\af0\dbch\af11\loch\f0 5801 }{\f1\fs20\insrsid3691716 \hich\af1\dbch\af11\loch\f1 pairs were }{
\f1\fs20\insrsid420013 \hich\af1\dbch\af11\loch\f1 judged}{\f1\fs20\insrsid3691716 \hich\af1\dbch\af11\loch\f1 \hich\f1 \'93}{\f1\fs20\insrsid3691716\charrsid9787409 \hich\af1\dbch\af11\loch\f1 semantica\hich\af1\dbch\af11\loch\f1 lly equivalent}{
\f1\fs20\insrsid3691716 \loch\af1\dbch\af11\hich\f1 \'94\loch\f1 .}{\f1\fs20\insrsid6293529
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid6293529 {\f1\fs20\insrsid3691716\charrsid9787409
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 \hich\f1 In many instances, the pair of sentences rated by 2 judges as \'93\loch\f1
\hich\f1 semantically equivalent\'94\loch\f1 \hich\f1 will in fact diverge semantically to at least some degree. If a full paraphrase relationship can be described as \'93\loch\f1 \hich\f1 bidirectional entailment\'94\loch\f1 , then the
\hich\af1\dbch\af11\loch\f1 \hich\f1 majority of the \'93\loch\f1 \hich\f1 equivalent\'94\loch\f1 \hich\f1 pairs in this dataset exhibit \'93\loch\f1 \hich\f1 mostly bidirectional entailments\'94\loch\f1
, with one sentence containing information that differs from or is not contained in the other. Some specific rating criteria are included in a tagging specificati\hich\af1\dbch\af11\loch\f1 o\hich\af1\dbch\af11\loch\f1 n (}{\f1\fs20\insrsid5711444
\hich\af1\dbch\af11\loch\f1 Section 3}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 \hich\f1 ), but by and large the degree of mismatch allowed before the pair was judged \'93\loch\f1 \hich\f1 non-equivalent\'94\loch\f1
was left to the discretion of the individual rater: did a particular set of asymmetries alter the meanings of the sentences enough that they couldn\hich\f1 \rquote \loch\f1 t\hich\af1\dbch\af11\loch\f1 \hich\f1 be considered \'93\loch\f1 \hich\f1
the same\'94\loch\f1 in meaning? This task was ill-defined enough that we were surprised at}{\f1\fs20\insrsid1124373\charrsid9787409 \hich\af1\dbch\af11\loch\f1 how}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 high }{
\f1\fs20\insrsid15562647 \hich\af1\dbch\af11\loch\f1 interrater}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 agreement was }{\f1\fs20\insrsid15737115 \hich\af1\dbch\af11\loch\f1 (averaging 83%}{
\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 ).
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid6293529 {\f1\fs20\insrsid6293529\charrsid9787409
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid1124373\charrsid9787409 \hich\af1\dbch\af11\loch\f1 A}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1
series of experiments aimed at making the judging task more concrete resulted in uniformly }{\f1\fs20\insrsid941686 \hich\af1\dbch\af11\loch\f1 degraded}{\f1\fs20\insrsid12675160\charrsid9787409 \hich\af1\dbch\af11\loch\f1 }{\f1\fs20\insrsid15562647
\hich\af1\dbch\af11\loch\f1 inte\hich\af1\dbch\af11\loch\f1 rrater}{\f1\fs20\insrsid12675160\charrsid9787409 \hich\af1\dbch\af11\loch\f1
agreement. Providing a checkbox to allow judges to specify that one sentence entailed another, for instance, left the raters frustrated and had a negative impact on agreement.}{\f1\fs20\insrsid1124373\charrsid9787409 \hich\af1\dbch\af11\loch\f1
Similarly, efforts to identify classes of syntactic alternations that wou\hich\af1\dbch\af11\loch\f1 ld not count against a}{\f1\fs20\insrsid2569839 \hich\af1\dbch\af11\loch\f1 n}{\f1\fs20\insrsid1124373\charrsid9787409 \hich\af1\dbch\af11\loch\f1
\hich\f1 \'93}{\f1\fs20\insrsid2569839 \hich\af1\dbch\af11\loch\f1 equivalent}{\f1\fs20\insrsid1124373\charrsid9787409 \loch\af1\dbch\af11\hich\f1 \'94\loch\f1 judgment resulted, in most cases, in a collapse in }{\f1\fs20\insrsid15562647
\hich\af1\dbch\af11\loch\f1 interrater}{\f1\fs20\insrsid1124373\charrsid9787409 \hich\af1\dbch\af11\loch\f1 agreement. The }{\f1\fs20\insrsid799020 \hich\af1\dbch\af11\loch\f1 relatively }{\f1\fs20\insrsid1124373\charrsid9787409
\hich\af1\dbch\af11\loch\f1 few }{\f1\fs20\insrsid799020 \hich\af1\dbch\af11\loch\f1 situations}{\f1\fs20\insrsid1124373\charrsid9787409 \hich\af1\dbch\af11\loch\f1
where we found firm guidelines of this type to be helpful (e.g. in dealing with anaphora) are included in }{\f1\fs20\insrsid799020 \hich\af1\dbch\af11\loch\f1 Section 3}{\f1\fs20\insrsid1124373\charrsid9787409 \hich\af1\dbch\af11\loch\f1 .}{
\f1\fs20\insrsid6293529\charrsid9787409
\par }\pard \ql \li0\ri0\widctlpar\tx1650\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid1124373 {\f1\fs20\insrsid1124373\charrsid9787409 \tab }{\f1\fs20\insrsid6293529\charrsid9787409
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid12675160\charrsid9787409 \hich\af1\dbch\af11\loch\f1 \hich\f1 The decision to tag sentences as being \'93\loch\f1
more or less semantically equivalent}{\f1\fs20\insrsid6900316\charrsid9787409 \loch\af1\dbch\af11\hich\f1 \'94}{\f1\fs20\insrsid12675160\charrsid9787409 \hich\af1\dbch\af11\loch\f1 \hich\f1 , rather than \'93\loch\f1 \hich\f1 semantically equivalent\'94
\loch\f1 was ultimately a practical one:}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 insisting on complete sets of bidirectional entailments would}{\f1\fs20\insrsid10308052 \hich\af1\dbch\af11\loch\f1 have}{
\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 rule}{\f1\fs20\insrsid10308052 \hich\af1\dbch\af11\loch\f1 d}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1 out all but the most trivial so
\hich\af1\dbch\af11\loch\f1 rts of paraphrase relationships, such }{\f1\fs20\insrsid2569839 \hich\af1\dbch\af11\loch\f1 as }{\f1\fs20\insrsid7955676\charrsid9787409 \hich\af1\dbch\af11\loch\f1 sentence pairs differing only a single word}{
\f1\fs20\insrsid2569839 \hich\af1\dbch\af11\loch\f1 \hich\f1 or in the presence of titles like \'93\loch\f1 \hich\f1 Mr.\'94\loch\f1 \hich\f1 and \'93\loch\f1 \hich\f1 Ms.\'94}{\f1\fs20\insrsid6293529\charrsid9787409 \hich\af1\dbch\af11\loch\f1
. Our interest was in identifying more complex paraphrase relationships, which required a somewhat looser definition of wh\hich\af1\dbch\af11\loch\f1 \hich\f1 at \'93\loch\f1 \hich\f1 semantic equivalence\'94\loch\f1 means. }{\f1\fs20\insrsid10308052
\hich\af1\dbch\af11\loch\f1 In an effort to focus on }{\f1\fs20\insrsid10695583 \hich\af1\dbch\af11\loch\f1 these more }{\f1\fs20\insrsid10308052 \hich\af1\dbch\af11\loch\f1
interesting pairs, the dataset was restricted to pairs with a minimum word-based Levenshtein distance of }{\f44\fs20\insrsid10308052 \loch\af44\dbch\af11\hich\f44 \uc1\u8805\'3d}{\f1\fs20\insrsid10308052 \hich\af1\dbch\af11\loch\f1 8.}{
\f1\fs20\insrsid6293529\charrsid9787409
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid13984194 {\f1\fs20\insrsid13984194\charrsid9787409
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid13984194\charrsid9787409 \hich\af1\dbch\af11\loch\f1
Given our relatively loose definition of equivalence, any 2 of the following sentences would }{\f1\fs20\insrsid13264869\charrsid9787409 \hich\af1\dbch\af11\loch\f1 probably }{\f1\fs20\insrsid13984194\charrsid9787409 \hich\af1\dbch\af11\loch\f1 \hich\f1
have been considered \'93\loch\f1 \hich\f1 paraphrases\'94\loch\f1 , despite obvious differences in information content:
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid13984194 {\insrsid13984194
\par {\listtext\pard\plain\f3\fs20\cf1\insrsid13984194\charrsid1906673 \loch\af3\dbch\af11\hich\f3 \'b7\tab}}\pard \qj \fi-360\li720\ri0\keepn\widctlpar\jclisttab\tx720\aspalpha\aspnum\faauto\ls5
\pnrauth1\pnrdate-2037179654\pnrstart0\pnrxst1\pnrxst0\pnrxst183\pnrxst240\pnrstop4\pnrstart1\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrstop9\pnrstart2\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23
\pnrnfc23\pnrnfc23\pnrnfc0\pnrnfc0\pnrnfc1\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrstop18\pnrstart3\pnrpnbr1\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrstop36\nosnaplinegrid
\adjustright\rin0\lin720\itap0\pararsid3955478 {\f5\fs20\cf1\insrsid13984194\charrsid1906673 \hich\af5\dbch\af11\loch\f5 The genome of the fungal pathogen that causes Sudden Oak De\hich\af5\dbch\af11\loch\f5 ath has been sequenced by US scientists
\par {\listtext\pard\plain\f3\fs20\cf1\insrsid13984194\charrsid1906673 \loch\af3\dbch\af11\hich\f3 \'b7\tab}\hich\af5\dbch\af11\loch\f5
Researchers announced Thursday they've completed the genetic blueprint of the blight-causing culprit responsible for sudden oak death
\par {\listtext\pard\plain\f3\fs20\cf1\insrsid13984194\charrsid1906673 \loch\af3\dbch\af11\hich\f3 \'b7\tab}\hich\af5\dbch\af11\loch\f5 Scientists have figured out the complete genetic code of a virulent pathogen that \hich\af5\dbch\af11\loch\f5
has killed tens of thousands of California native oaks
\par {\listtext\pard\plain\f3\fs20\cf1\insrsid13984194\charrsid1906673 \loch\af3\dbch\af11\hich\f3 \'b7\tab}}\pard \qj \fi-360\li720\ri0\widctlpar\jclisttab\tx720\aspalpha\aspnum\faauto\ls5
\pnrauth1\pnrdate-2037179654\pnrstart0\pnrxst1\pnrxst0\pnrxst183\pnrxst240\pnrstop4\pnrstart1\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrstop9\pnrstart2\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23\pnrnfc23
\pnrnfc23\pnrnfc23\pnrnfc0\pnrnfc0\pnrnfc4\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrstop18\pnrstart3\pnrpnbr4\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrstop36\nosnaplinegrid
\adjustright\rin0\lin720\itap0\pararsid6293529 {\f5\fs20\cf1\insrsid13984194\charrsid1906673 \hich\af5\dbch\af11\loch\f5
The East Bay-based Joint Genome Institute said Thursday it has unraveled the genetic blueprint for the diseases that cause the sudden death of oak trees}{\f5\fs20\cf1\insrsid6293529\charrsid1906673
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid16384408 {\f1\fs20\insrsid16384408
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 Raters}{\f1\fs20\insrsid16384408\charrsid9787409 \hich\af1\dbch\af11\loch\f1
were presented with sentences in which }{\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 s\hich\af1\dbch\af11\loch\f1 everal}{\f1\fs20\insrsid16384408\charrsid9787409 \hich\af1\dbch\af11\loch\f1 classes of named entities }{\f1\fs20\insrsid16384408
\hich\af1\dbch\af11\loch\f1 were}{\f1\fs20\insrsid16384408\charrsid9787409 \hich\af1\dbch\af11\loch\f1 \hich\f1 replaced by generic tags, so that \'93\loch\f1 \hich\f1 Tuesday\'94\loch\f1 \hich\f1 became %%DAY%%, \'93\loch\f1 $10,000}{
\f1\fs20\insrsid16384408 \loch\af1\dbch\af11\hich\f1 \'94\loch\f1 \hich\f1 became \'93\loch\f1 %%MONEY%%, and so on.}{\f1\fs20\insrsid14156 \hich\af1\dbch\af11\loch\f1 T}{\f1\fs20\insrsid16384408\charrsid9787409 \hich\af1\dbch\af11\loch\f1
he release versions}{\f1\fs20\insrsid14156 \hich\af1\dbch\af11\loch\f1 , however,}{\f1\fs20\insrsid16384408\charrsid9787409 \hich\af1\dbch\af11\loch\f1 preserve the }{\f1\fs20\insrsid16384408\charrsid1336933 \hich\af1\dbch\af11\loch\f1 original strings.}
{\f1\fs20\insrsid16384408
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid16384408 {\f1\fs20\insrsid16384408\charrsid1336933
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 Note that many of the sentence pairs judged to be }{\f1\fs20\insrsid15358814
\loch\af1\dbch\af11\hich\f1 \'93}{\b\f1\fs20\insrsid16384408\charrsid15358814 \hich\af1\dbch\af11\loch\f1 not }{\b\f1\fs20\insrsid15009449\charrsid15358814 \hich\af1\dbch\af11\loch\f1 equivalent}{\f1\fs20\insrsid15358814 \loch\af1\dbch\af11\hich\f1 \'94}{
\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 will still overlap significantly in information content}{\f1\fs20\insrsid12864072 \hich\af1\dbch\af11\loch\f1 and even wording}{\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1
. A variety of automatic filtering techniques were used to create an initial dataset that was rich in paraphrase relationships, and the success of these techniques meant th\hich\af1\dbch\af11\loch\f1
at approximately 70% of the pairs examined by raters were, by our criteria, semantically equivale}{\f1\fs20\insrsid12413466 \hich\af1\dbch\af11\loch\f1 nt. The remaining 30% represent}{\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 a }{
\f1\fs20\insrsid1654934 \hich\af1\dbch\af11\loch\f1 range of relationships, from }{\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 pairs that are }{\f1\fs20\insrsid1654934 \hich\af1\dbch\af11\loch\f1
completely unrelated semantically, to those that are}{\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 partially overlapping, }{\f1\fs20\insrsid1654934 \hich\af1\dbch\af11\loch\f1 to th\hich\af1\dbch\af11\loch\f1
ose that are almost-but-not-quite semantically equivalent.}{\f1\fs20\insrsid16384408 \hich\af1\dbch\af11\loch\f1 \hich\f1 For this reason, this \'93}{\b\f1\fs20\insrsid4261794\charrsid15358814 \hich\af1\dbch\af11\loch\f1 not equivalent}{
\f1\fs20\insrsid16384408 \loch\af1\dbch\af11\hich\f1 \'94\loch\f1 set should not be used as negative training data.
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid6293529 {\f1\fs20\insrsid6293529\charrsid1336933
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid6293529\charrsid1336933 \hich\af1\dbch\af11\loch\f1
We have made every effort to ensure that each sentence in this dataset has been given proper attribution. I\hich\af1\dbch\af11\loch\f1 f you encounter any errors/omissions, please contact Bill Dolan }{\f1\fs20\insrsid1336933 \hich\af1\dbch\af11\loch\f1 (}
{\field{\*\fldinst {\f1\fs20\insrsid1336933 \hich\af1\dbch\af11\loch\f1 HYPERLINK "mailto:billdol@microsoft.com" }{\f1\fs20\insrsid1336933\charrsid8801882 {\*\datafield
00d0c9ea79f9bace118c8200aa004ba90b020000001700000016000000620069006c006c0064006f006c0040006d006900630072006f0073006f00660074002e0063006f006d000000e0c9ea79f9bace118c8200aa004ba90b3a0000006d00610069006c0074006f003a00620069006c006c0064006f006c0040006d006900
630072006f0073006f00660074002e0063006f006d000000}}}{\fldrslt {\cs15\f1\fs20\ul\cf2\insrsid1336933\charrsid8801882 \hich\af1\dbch\af11\loch\f1 billdol@microsoft.com}}}{\f1\fs20\insrsid1336933 \hich\af1\dbch\af11\loch\f1 ), and }{
\f1\fs20\insrsid6293529\charrsid1336933 \hich\af1\dbch\af11\loch\f1 we will promptly modify the }{\f1\fs20\insrsid13183636 \hich\af1\dbch\af11\loch\f1 data}{\f1\fs20\insrsid6293529\charrsid1336933 \hich\af1\dbch\af11\loch\f1 to reflect the }{
\f1\fs20\insrsid7955676\charrsid1336933 \hich\af1\dbch\af11\loch\f1 correct}{\f1\fs20\insrsid6293529\charrsid1336933 \hich\af1\dbch\af11\loch\f1 information.}{\f1\fs20\insrsid6049540\charrsid1336933
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid11557177 {\b\i\f1\fs28\ul\insrsid11557177
\par }{\b\i\f1\fs28\ul\insrsid6049540
\par
\par }{\b\i\f1\fs28\ul\insrsid6049540\charrsid11557177
\par {\listtext\pard\plain\b\i\f1\fs28\insrsid3362214 \hich\af1\dbch\af11\loch\f1 2.\tab}}\pard \ql \fi-425\li425\ri0\widctlpar\jclisttab\tx425\aspalpha\aspnum\faauto\ls1
\pnrauth1\pnrdate-2037179654\pnrstart0\pnrxst2\pnrxst0\pnrxst0\pnrxst0\pnrxst46\pnrxst0\pnrstop6\pnrstart1\pnrrgb1\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrstop9\pnrstart2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0
\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrstop18\pnrstart3\pnrpnbr2\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrstop36\adjustright\rin0\lin425\itap0\pararsid5514607
{\b\i\f1\fs28\ul\insrsid3362214 \hich\af1\dbch\af11\loch\f1 Methodology and Results
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid12138041 {\f1\fs20\insrsid3362214\charrsid12138041
\par \hich\af1\dbch\af11\loch\f1 This data set consi\hich\af1\dbch\af11\loch\f1 sts of 5801 sentence pairs, with a binary human judgment of whether or not the pairing constitutes a paraphrase.}{\f1\fs20\insrsid3362214
\par }{\f1\fs20\insrsid3362214\charrsid12138041
\par {\listtext\pard\plain\b\i\f1\insrsid3362214\charrsid11557177 \hich\af1\dbch\af11\loch\f1 2.1.\tab}}\pard \ql \fi-567\li567\ri0\widctlpar\jclisttab\tx567\jclisttab\tx720\aspalpha\aspnum\faauto\ls1\ilvl1
\pnrauth1\pnrdate-2037179654\pnrstart0\pnrxst4\pnrxst0\pnrxst0\pnrxst0\pnrxst46\pnrxst0\pnrxst1\pnrxst0\pnrxst46\pnrxst0\pnrstop10\pnrstart1\pnrrgb1\pnrrgb3\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrstop9
\pnrstart2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc1\pnrnfc0\pnrnfc0\pnrstop18\pnrstart3\pnrpnbr2\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr1\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrstop36\adjustright\rin0\lin567\itap0\pararsid11557177 {\b\i\f1\ul\insrsid3362214\charrsid11557177 \hich\af1\dbch\af11\loch\f1 Methodology
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid12138041 {\f1\fs20\insrsid3362214\charrsid12138041
\par }\pard \qj \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15738572 {\f1\fs20\insrsid3362214\charrsid12138041 \hich\af1\dbch\af11\loch\f1 To generate the judgments, we used 3 raters to score the sentence }{
\f1\fs20\insrsid5514607 \hich\af1\dbch\af11\loch\f1 pairs }{\f1\fs20\insrsid3362214\charrsid12138041 \hich\af1\dbch\af11\loch\f1 according to a given specification. Rater 1 scored all 58\hich\af1\dbch\af11\loch\f1
01 sentences. Rater 2 scored 3533 sentences, and Rater 3 scored 2268 sentences. For the sentences where Rater 1 and 2 did not agree on the judgment, Rater 3 gave a final judgment, while Rater 2 gave the final judgment on sentences where Rater 1 and Rater
\hich\af1\dbch\af11\loch\f1 3\hich\af1\dbch\af11\loch\f1 did not agree.
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid3362214 {\f1\fs20\insrsid3362214\charrsid12138041
\par {\listtext\pard\plain\b\i\f1\insrsid3362214\charrsid11557177 \hich\af1\dbch\af11\loch\f1 2.2.\tab}}\pard \ql \fi-567\li567\ri0\widctlpar\jclisttab\tx567\jclisttab\tx720\aspalpha\aspnum\faauto\ls1\ilvl1
\pnrauth1\pnrdate-2037179654\pnrstart0\pnrxst4\pnrxst0\pnrxst0\pnrxst0\pnrxst46\pnrxst0\pnrxst1\pnrxst0\pnrxst46\pnrxst0\pnrstop10\pnrstart1\pnrrgb1\pnrrgb3\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrstop9
\pnrstart2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc2\pnrnfc0\pnrnfc0\pnrstop18\pnrstart3\pnrpnbr2\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr2\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrstop36\adjustright\rin0\lin567\itap0\pararsid11557177 {\b\i\f1\ul\insrsid3362214\charrsid11557177 \hich\af1\dbch\af11\loch\f1 Interrater Agreement
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid12138041 {\f1\fs20\insrsid3362214\charrsid12138041
\par \hich\af1\dbch\af11\loch\f1 To test interrater agreement, we took a simple percentage:
\par }\pard \ql \li0\ri0\keepn\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid3362214 {\insrsid3362214
\par }\trowd \irow0\irowband0\ts16\trqc\trgaph108\trleft-108\trbrdrt\brdrs\brdrw10 \trbrdrl\brdrs\brdrw10 \trbrdrb\brdrs\brdrw10 \trbrdrr\brdrs\brdrw10 \trbrdrh\brdrs\brdrw10 \trbrdrv\brdrs\brdrw10
\trftsWidth1\trftsWidthB3\trftsWidthA3\trautofit1\trpaddl108\trpaddr108\trpaddfl3\trpaddft3\trpaddfb3\trpaddfr3\tbllkhdrrows\tbllklastrow\tbllkhdrcols\tbllklastcol \clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr
\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx1663\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx3434\clvertalt\clbrdrt
\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx5205\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10
\cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx6976\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0\pararsid12138041 {\f1\fs20\insrsid3362214\charrsid12138041 \cell \hich\af1\dbch\af11\loch\f1 Total scored\cell
\hich\af1\dbch\af11\loch\f1 Total agreements\cell \hich\af1\dbch\af11\loch\f1 Percentage agreement\cell }\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0 {\f1\fs20\insrsid3362214\charrsid12138041 \trowd \irow0\irowband0
\ts16\trqc\trgaph108\trleft-108\trbrdrt\brdrs\brdrw10 \trbrdrl\brdrs\brdrw10 \trbrdrb\brdrs\brdrw10 \trbrdrr\brdrs\brdrw10 \trbrdrh\brdrs\brdrw10 \trbrdrv\brdrs\brdrw10
\trftsWidth1\trftsWidthB3\trftsWidthA3\trautofit1\trpaddl108\trpaddr108\trpaddfl3\trpaddft3\trpaddfb3\trpaddfr3\tbllkhdrrows\tbllklastrow\tbllkhdrcols\tbllklastcol \clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr
\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx1663\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx3434\clvertalt\clbrdrt
\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx5205\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10
\cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx6976\row }\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0\pararsid12138041 {\f1\fs20\insrsid3362214\charrsid12138041 \hich\af1\dbch\af11\loch\f1 Raters 1 & 2\cell
\hich\af1\dbch\af11\loch\f1 3533\cell \hich\af1\dbch\af11\loch\f1 2904\cell \hich\af1\dbch\af11\loch\f1 82.20\cell }\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0 {\f1\fs20\insrsid3362214\charrsid12138041
\trowd \irow1\irowband1\ts16\trqc\trgaph108\trleft-108\trbrdrt\brdrs\brdrw10 \trbrdrl\brdrs\brdrw10 \trbrdrb\brdrs\brdrw10 \trbrdrr\brdrs\brdrw10 \trbrdrh\brdrs\brdrw10 \trbrdrv\brdrs\brdrw10
\trftsWidth1\trftsWidthB3\trftsWidthA3\trautofit1\trpaddl108\trpaddr108\trpaddfl3\trpaddft3\trpaddfb3\trpaddfr3\tbllkhdrrows\tbllklastrow\tbllkhdrcols\tbllklastcol \clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr
\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx1663\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx3434\clvertalt\clbrdrt
\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx5205\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10
\cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx6976\row }\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0\pararsid3362214 {\f1\fs20\insrsid3362214\charrsid12138041 \hich\af1\dbch\af11\loch\f1 Raters 1 & 3\cell
\hich\af1\dbch\af11\loch\f1 2268\cell \hich\af1\dbch\af11\loch\f1 1921\cell \hich\af1\dbch\af11\loch\f1 84.70\cell }\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0 {\f1\fs20\insrsid3362214\charrsid12138041
\trowd \irow2\irowband2\lastrow \ts16\trqc\trgaph108\trleft-108\trbrdrt\brdrs\brdrw10 \trbrdrl\brdrs\brdrw10 \trbrdrb\brdrs\brdrw10 \trbrdrr\brdrs\brdrw10 \trbrdrh\brdrs\brdrw10 \trbrdrv\brdrs\brdrw10
\trftsWidth1\trftsWidthB3\trftsWidthA3\trautofit1\trpaddl108\trpaddr108\trpaddfl3\trpaddft3\trpaddfb3\trpaddfr3\tbllkhdrrows\tbllklastrow\tbllkhdrcols\tbllklastcol \clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr
\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx1663\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx3434\clvertalt\clbrdrt
\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10 \cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx5205\clvertalt\clbrdrt\brdrs\brdrw10 \clbrdrl\brdrs\brdrw10 \clbrdrb\brdrs\brdrw10 \clbrdrr\brdrs\brdrw10
\cltxlrtb\clftsWidth3\clwWidth1771\clshdrawnil \cellx6976\row }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid3362214 {\f1\fs20\insrsid3362214\charrsid12138041
\par {\listtext\pard\plain\b\i\f1\insrsid3362214\charrsid11557177 \hich\af1\dbch\af11\loch\f1 2.3.\tab}}\pard \ql \fi-567\li567\ri0\widctlpar\jclisttab\tx567\jclisttab\tx720\aspalpha\aspnum\faauto\ls1\ilvl1
\pnrauth1\pnrdate-2037179654\pnrstart0\pnrxst4\pnrxst0\pnrxst0\pnrxst0\pnrxst46\pnrxst0\pnrxst1\pnrxst0\pnrxst46\pnrxst0\pnrstop10\pnrstart1\pnrrgb1\pnrrgb3\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrrgb0\pnrstop9
\pnrstart2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc2\pnrnfc0\pnrnfc0\pnrnfc0\pnrnfc3\pnrnfc0\pnrnfc0\pnrstop18\pnrstart3\pnrpnbr2\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr3\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0\pnrpnbr0
\pnrpnbr0\pnrstop36\adjustright\rin0\lin567\itap0\pararsid11557177 {\b\i\f1\ul\insrsid3362214\charrsid11557177 \hich\af1\dbch\af11\loch\f1 Overall scoring results
\par }\pard \ql \li0\ri0\widctlpar\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid12138041 {\f1\fs20\insrsid3362214\charrsid12138041
\par \hich\af1\dbch\af11\loch\f1 We computed scorin\hich\af1\dbch\af11\loch\f1 g results for each individual (raw scores, before resolving}{\insrsid3362214 \hich\af0\dbch\af11\loch\f0 differences):
\par }{\f1\fs20\insrsid3362214\charrsid12138041
\par }\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0\pararsid12138041 {\f1\fs20\insrsid3362214\charrsid12138041 \cell \hich\af1\dbch\af11\loch\f1 Total scored\cell \hich\af1\dbch\af11\loch\f1 \hich\f1 Number \'93\loch\f1
\hich\f1 yes\'94\cell \hich\af1\dbch\af11\loch\f1 \hich\f1 Percentage \'93\loch\f1 \hich\f1 yes\'94\cell }\pard \ql \li0\ri0\widctlpar\intbl\aspalpha\aspnum\faauto\adjustright\rin0\lin0 {\f1\fs20\insrsid3362214\charrsid12138041 \trowd \irow0\irowband0
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gitextract_ia7mi6tx/ ├── LICENSE ├── README.md ├── dataset/ │ ├── msr-paraphrase-corpus/ │ │ ├── MSR Paraphrase Corpus.lnk │ │ ├── Microsoft Shared Source License.htm │ │ ├── Microsoft Shared Source License.rtf │ │ ├── msr_paraphrase_README.htm │ │ ├── msr_paraphrase_README.rtf │ │ ├── msr_paraphrase_data.txt │ │ ├── msr_paraphrase_test.txt │ │ └── msr_paraphrase_train.txt │ ├── msr-video-paraphrase-corpus/ │ │ ├── test-gold.tgz │ │ ├── train-readme.txt │ │ ├── train.tgz │ │ └── trial.tgz │ ├── mt-metrics-paraphrase-corpus/ │ │ ├── README │ │ ├── msrp-annotations.csv │ │ ├── pan-annotations.csv │ │ ├── pan-test.labels │ │ ├── pan-test_s1.txt │ │ ├── pan-test_s2.txt │ │ ├── pan-train.labels │ │ ├── pan-train_s1.txt │ │ └── pan-train_s2.txt │ └── readme.md ├── source_code_in_theano/ │ ├── data/ │ │ ├── 20_news_group_sentences.txt │ │ ├── msr_paraphrase_test.txt │ │ └── msr_paraphrase_train.txt │ ├── data.py │ ├── deep_lstm.py │ ├── input.py │ ├── lstm.py │ ├── models/ │ │ ├── backward_double_layer_lstm-2016-12-09-19-49-14000-48-64.dat.npz │ │ ├── backward_single_layer_lstm-2016-11-30-21-07-14000-48-64.dat.npz │ │ ├── forward_double_layer_lstm-2016-12-09-19-34-14000-48-64.dat.npz │ │ ├── forward_single_layer_lstm-2016-12-05-13-04-14000-48-64.dat.npz │ │ └── model_trained_on_20_news_group_dataset/ │ │ ├── backward_double_layer_lstm-2017-01-07-19-12-20000-64-128.dat.npz │ │ ├── backward_single_layer_lstm-2017-01-07-19-00-20000-64-128.dat.npz │ │ ├── forward_double_layer_lstm-2017-01-07-19-06-20000-64-128.dat.npz │ │ └── forward_single_layer_lstm-2017-01-06-00-44-20000-64-128.dat.npz │ ├── news_group_data.py │ ├── readme.md │ ├── test_lstm.py │ ├── train_lstm.py │ └── utils.py └── state-of-art-details.md
SYMBOL INDEX (52 symbols across 8 files)
FILE: source_code_in_theano/data.py
function load_data (line 12) | def load_data(loc='./data/', _train=False, _test=False):
function build_dictionary (line 46) | def build_dictionary(loc='./data/', vocabulary_size=-1):
function my_tokenizer (line 122) | def my_tokenizer(input):
function get_train_data (line 130) | def get_train_data(vocabulary_size):
function get_train_data_reversed (line 154) | def get_train_data_reversed(vocabulary_size):
function get_train_sentences (line 175) | def get_train_sentences(vocabulary_size):
function get_train_sentences_reversed (line 189) | def get_train_sentences_reversed(vocabulary_size):
function get_test_data (line 203) | def get_test_data(vocabulary_size):
function get_test_data_reversed (line 227) | def get_test_data_reversed(vocabulary_size):
function get_test_sentences (line 248) | def get_test_sentences(vocabulary_size):
function get_test_sentences_reversed (line 260) | def get_test_sentences_reversed(vocabulary_size):
FILE: source_code_in_theano/deep_lstm.py
class DLSTM (line 10) | class DLSTM:
method __init__ (line 11) | def __init__(self, word_dim, hidden_dim=128, bptt_truncate=-1):
method __theano_build__ (line 45) | def __theano_build__(self):
method calculate_total_loss (line 137) | def calculate_total_loss(self, X, Y):
method calculate_loss (line 140) | def calculate_loss(self, X, Y):
FILE: source_code_in_theano/input.py
function load_data (line 15) | def load_data(loc='./data/'):
function build_dictionary (line 42) | def build_dictionary(loc='./data/', vocabulary_size=-1):
function my_tokenizer (line 118) | def my_tokenizer(input):
function get_train_data (line 125) | def get_train_data(vocabulary_size):
function get_train_data_reversed (line 148) | def get_train_data_reversed(vocabulary_size):
function get_train_sentences (line 167) | def get_train_sentences(vocabulary_size):
function get_train_sentences_reversed (line 179) | def get_train_sentences_reversed(vocabulary_size):
function get_test_data (line 192) | def get_test_data(vocabulary_size):
function get_test_data_reversed (line 216) | def get_test_data_reversed(vocabulary_size):
function get_test_sentences (line 236) | def get_test_sentences(vocabulary_size):
function get_test_sentences_reversed (line 247) | def get_test_sentences_reversed(vocabulary_size):
FILE: source_code_in_theano/lstm.py
class LSTM (line 10) | class LSTM:
method __init__ (line 11) | def __init__(self, word_dim, hidden_dim=128, bptt_truncate=-1):
method __theano_build__ (line 45) | def __theano_build__(self):
method calculate_total_loss (line 127) | def calculate_total_loss(self, X, Y):
method calculate_loss (line 130) | def calculate_loss(self, X, Y):
FILE: source_code_in_theano/news_group_data.py
function load_data (line 15) | def load_data(loc='./data/'):
function build_dictionary (line 26) | def build_dictionary(loc='./data/', vocabulary_size=-1):
function my_tokenizer (line 68) | def my_tokenizer(input):
function get_train_data (line 75) | def get_train_data(vocabulary_size):
function get_train_data_reversed (line 91) | def get_train_data_reversed(vocabulary_size):
function get_train_sentences (line 103) | def get_train_sentences(vocabulary_size):
function get_train_sentences_reversed (line 114) | def get_train_sentences_reversed(vocabulary_size):
FILE: source_code_in_theano/test_lstm.py
function generate_sentence_embedding (line 17) | def generate_sentence_embedding(model, test_sent):
function generate_sentence_embeddings (line 22) | def generate_sentence_embeddings(model, x_test):
function do_pooling (line 29) | def do_pooling(var_matrix, n_row, n_col, criterion='max'):
function combine_forward_and_backward_vectors (line 71) | def combine_forward_and_backward_vectors(sentences, sentences_r):
function generate_feature_vector (line 89) | def generate_feature_vector(first_sentences, second_sentences):
function build_classifier_and_test (line 110) | def build_classifier_and_test(train_X, train_y, test_X, test_y, clf, pri...
function test_on_forward_LSTM (line 125) | def test_on_forward_LSTM(model, classifier=MLPClassifier()):
function test_on_bidirectional_lstm (line 154) | def test_on_bidirectional_lstm(forward_model, backward_model, classifier...
FILE: source_code_in_theano/train_lstm.py
function sgd_callback (line 41) | def sgd_callback(model, num_examples_seen):
FILE: source_code_in_theano/utils.py
function train_with_sgd (line 6) | def train_with_sgd(model, X_train, y_train, learning_rate=0.001, nepoch=...
function save_model_parameters_theano (line 21) | def save_model_parameters_theano(model, outfile):
function load_model_parameters_theano (line 32) | def load_model_parameters_theano(path, modelClass):
function gradient_check_theano (line 48) | def gradient_check_theano(model, x, y, h=0.001, error_threshold=0.01):
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Download .json
Condensed preview — 45 files, each showing path, character count, and a content snippet. Download the .json file for the full structured content (19,769K chars).
[
{
"path": "LICENSE",
"chars": 1067,
"preview": "MIT License\n\nCopyright (c) 2016 Wasi Ahmad\n\nPermission is hereby granted, free of charge, to any person obtaining a copy"
},
{
"path": "README.md",
"chars": 3918,
"preview": "# Paraphrase-Identification-Task\nParaphrase detection is the task of examining two text entities (ex. sentence) and dete"
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"path": "dataset/msr-paraphrase-corpus/Microsoft Shared Source License.htm",
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"preview": "<html>\n\n<head>\n<meta http-equiv=Content-Type content=\"text/html; charset=shift_jis\">\n<meta name=Generator content=\"Micro"
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"path": "dataset/msr-paraphrase-corpus/msr_paraphrase_README.htm",
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"preview": "<html>\n\n<head>\n<meta http-equiv=Content-Type content=\"text/html; charset=windows-1252\">\n<meta name=Generator content=\"Mi"
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{
"path": "dataset/msr-paraphrase-corpus/msr_paraphrase_data.txt",
"chars": 1936771,
"preview": "Sentence ID\tString\tAuthor\tURL\tAgency\tDate\tWeb Date\n702876\tAmrozi accused his brother, whom he called \"the witness\", of "
},
{
"path": "dataset/msr-paraphrase-corpus/msr_paraphrase_test.txt",
"chars": 431041,
"preview": "Quality\t#1 ID\t#2 ID\t#1 String\t#2 String\n1\t1089874\t1089925\tPCCW's chief operating officer, Mike Butcher, and Alex Arena,"
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{
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"chars": 1022381,
"preview": "Quality\t#1 ID\t#2 ID\t#1 String\t#2 String\n1\t702876\t702977\tAmrozi accused his brother, whom he called \"the witness\", of de"
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"path": "dataset/msr-video-paraphrase-corpus/train-readme.txt",
"chars": 5170,
"preview": "\n\t\t\t SEMEVAL-2012 TASK 17\n\n\t\t\t\t STS\n\t\t Semantic Textual Similarity:\n \n\t\t A Unified Framework for the\n\t Eval"
},
{
"path": "dataset/mt-metrics-paraphrase-corpus/README",
"chars": 1583,
"preview": "This zip file contains the following files:\n\n1) pan-train_s1.txt: The PAN training set file containing the first sentenc"
},
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"path": "dataset/mt-metrics-paraphrase-corpus/msrp-annotations.csv",
"chars": 47005,
"preview": "id,sent1,sent2,label,annotation1,annotation2\n1,\"\"\"It was a little bit embarrassing the way we played in the first two ga"
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"path": "dataset/mt-metrics-paraphrase-corpus/pan-annotations.csv",
"chars": 45309,
"preview": "id,sent1,sent2,label,annotation1,annotation2\n1,\"Here was the second period of Hebraic influence, an influence wholly mor"
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"path": "dataset/mt-metrics-paraphrase-corpus/pan-test_s1.txt",
"chars": 607087,
"preview": "Dense fogs wrapped the mountains that shut in the little hamlet, but overhead the stars were shining in the near heaven."
},
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"path": "dataset/mt-metrics-paraphrase-corpus/pan-test_s2.txt",
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"preview": "The hamlet is surrounded by mountains which is wrapped with dense fogs, though above it, near heaven, the stars were shi"
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"preview": "Hare lays great stress on the necessity of circumcision wherever there is an indication of preputial local irritation.\nT"
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"chars": 1929766,
"preview": "Hare lays great stress onto the necessity of circumcision wherever there is an sign of preputial locally irritation.\nIn "
},
{
"path": "dataset/readme.md",
"chars": 6505,
"preview": "\n## List of dataset used in state-of-art techniques\n#### [Quora Question Pairs](https://data.quora.com/First-Quora-Datas"
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"path": "source_code_in_theano/data/20_news_group_sentences.txt",
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"preview": "i was wondering if anyone out there could enlighten me on this car i saw the other day\nit was a 2 door sports car looked"
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"chars": 431041,
"preview": "Quality\t#1 ID\t#2 ID\t#1 String\t#2 String\n1\t1089874\t1089925\tPCCW's chief operating officer, Mike Butcher, and Alex Arena,"
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"chars": 1022381,
"preview": "Quality\t#1 ID\t#2 ID\t#1 String\t#2 String\n1\t702876\t702977\tAmrozi accused his brother, whom he called \"the witness\", of de"
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{
"path": "source_code_in_theano/data.py",
"chars": 10471,
"preview": "import numpy as np\nfrom nltk import wordpunct_tokenize\nimport operator\nimport re, string\nimport math\n\nSENTENCE_START_TOK"
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"path": "source_code_in_theano/deep_lstm.py",
"chars": 6394,
"preview": "import numpy as np\nimport theano as theano\nimport theano.tensor as T\nfrom theano.gradient import grad_clip\nimport time\ni"
},
{
"path": "source_code_in_theano/input.py",
"chars": 9724,
"preview": "import numpy as np\nfrom nltk import wordpunct_tokenize\nimport nltk\nimport itertools\nimport operator\nimport sklearn\nimpor"
},
{
"path": "source_code_in_theano/lstm.py",
"chars": 5735,
"preview": "import numpy as np\nimport theano as theano\nimport theano.tensor as T\nfrom theano.gradient import grad_clip\nimport time\ni"
},
{
"path": "source_code_in_theano/news_group_data.py",
"chars": 3950,
"preview": "import numpy as np\nfrom nltk import wordpunct_tokenize\nimport nltk\nimport itertools\nimport operator\nimport sklearn\nimpor"
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{
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"chars": 992,
"preview": "## Deep Bidirectional Long Short Term Memory for Paraphrase Identification\n\n<p align=\"justify\">\nIn this work, we present"
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{
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"chars": 11441,
"preview": "import os, data\nfrom sklearn.neural_network import MLPClassifier\nfrom sklearn.svm import LinearSVC\nfrom sklearn.linear_m"
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"preview": "import numpy as np\nimport sys\nimport operator\n\n\ndef train_with_sgd(model, X_train, y_train, learning_rate=0.001, nepoch="
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"chars": 22483,
"preview": "## [Paraphrase Identification (State of the art)](https://aclweb.org/aclwiki/index.php?title=Paraphrase_Identification_("
}
]
// ... and 12 more files (download for full content)
About this extraction
This page contains the full source code of the wasiahmad/paraphrase_identification GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 45 files (156.6 MB), approximately 4.9M tokens, and a symbol index with 52 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.