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<big><b><br>
</b><b>Call for participation</b><b><br>
</b><b><br>
</b></big>
<div align="center"><big><b>Semantic Textual Similarity (STS)</b><b><br>
</b><b>SemEval 2013 - </b><b>Task 6</b></big><br>
<a href="http://www.cs.york.ac.uk/semeval-2013/task6/"><br>
http://www.cs.york.ac.uk/semeval-2013/task6/</a><br>
<a href="http://groups.google.com/group/STS-semeval">http://groups.google.com/group/STS-semeval</a><br>
</div>
<br>
Following the success of the 2012 task on STS
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(<a href="ixa2.si.ehu.es/starsem/proc/pdf/STARSEM-SEMEVAL051.pdf">Agirre
et al. 2012</a>), with 35 teams and 88 runs, we solicit
participation in the second STS task, which will held at SemEval
2013, co-located with the *SEM and NAACL-2013 conferences.<br>
<br>
<br>
<strong>STS in 2013</strong><br>
<br>
Participants will submit systems that examine the degree of semantic
equivalence between two sentences. The goal of the STS task is to
create a unified framework for the evaluation of semantic textual
similarity modules and to characterize their impact on NLP
applications. We particularly encourage submissions from the lexical
semantics, summarization, machine translation evaluation metric, and
textual entailment communities.<br>
<br>
The task will follow a similar design as <a
data-cke-saved-href="http://www.cs.york.ac.uk/semeval-2012/task6/"
href="http://www.cs.york.ac.uk/semeval-2012/task6/">last year</a>,
but instead of providing train/test data from the same datasets, we
will provide all the 2012 data as training data, and the test data
will be drawn from related but different datasets. This setting is
more realistic, and the teams which prefer to train/test on the same
datasets can perfomr experiments using the 2012 data.<br>
<br>
The task will thus comprise all the <a
data-cke-saved-href="http://www.cs.york.ac.uk/semeval-2013/task6/index.php?id=data"
href="http://www.cs.york.ac.uk/semeval-2013/task6/index.php?id=data">2012
data</a> plus the following<span class="Apple-converted-space"> </span><strong>novelties</strong>:
<ul style="padding-right: 40px; color: rgb(34, 34, 34); font-size:
12px; font-style: normal; font-variant: normal; font-weight:
normal; letter-spacing: normal; line-height: normal; orphans: 2;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 2; word-spacing: 0px;">
<li>New test data similar to the datasets used last year (<strong>Paraphrase</strong>,<span
class="Apple-converted-space"> </span><strong>SMT evaluation</strong>,<span
class="Apple-converted-space"> </span><strong>gloss pairs</strong>).</li>
<li>The SMT evaluation data will include data from<span
class="Apple-converted-space"> </span><strong>HyTER graphs</strong>.</li>
<li>A dataset on<span class="Apple-converted-space"> </span><strong>typed-similarity</strong><span
class="Apple-converted-space"> </span>between semi-structured
items, comprising both train and test data.</li>
<li>An<span class="Apple-converted-space"> </span><strong>open
source baseline</strong>, comprising a pipeline to combine STS
systems and components.</li>
<li>An new measure for evaluation.</li>
</ul>
Please check <a href="http://www.cs.york.ac.uk/semeval-2013/task6/">http://www.cs.york.ac.uk/semeval-2013/task6/</a>
for a detailed task description.<br>
<br>
<strong><br>
Important dates</strong><br>
<br>
Initial training dataset - 11 November<br>
Full training dataset + test scripts ready - 31 December<br>
Registration deadline - 15 February<br>
Start of Evaluation period - 1 March<br>
End of Evaluation period - 15 March 23:59 (UTC-11)<br>
Paper due - 9 April [TBC]<br>
Reviews due - 23 April [TBC]<br>
Camera Ready - 4 May [TBC]<br>
<strong><br>
<br>
Contact</strong><br>
<br>
Use the following mailing list: <strong>sts-semeval googlegroups com</strong>.
<br>
<br>
If interested in the task please join the mailing list for updates <a
data-cke-saved-href="http://groups.google.com/group/STS-semeval"
href="http://groups.google.com/group/STS-semeval">http://groups.google.com/group/STS-semeval</a>.<br>
<br>
<br>
<strong>Organizers<br>
<br>
</strong>Eneko Agirre, University of the Basque Country, Basque
Country<br>
Daniel Cer, Stanford University, USA<br>
Mona Diab, Columbia University, USA<br>
Aitor Gonzalez-Agirre, University of the Basque Country, Basque
Country<br class="Apple-interchange-newline">
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