Title:
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SemEval-2016 Task 1: Semantic textual similarity, monolingual and cross-lingual evaluation
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Author:
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Agirre, Eneko; Banea, Carmen; Cer, Daniel; Diab, Mona; Gonzalez Agirre, Aitor; Mihalcea, Rada; Rigau Claramunt, German; Wiebe, Janyce
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Abstract:
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Comunicació presentada al 10th International Workshop on Semantic Evaluation (SemEval-2016), celebrat els dies 16 i 17 de juny de 2016 a San Diego, Califòrnia. |
Abstract:
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Semantic Textual Similarity (STS) seeks to
measure the degree of semantic equivalence
between two snippets of text. Similarity is expressed
on an ordinal scale that spans from
semantic equivalence to complete unrelatedness.
Intermediate values capture specifically
defined levels of partial similarity. While
prior evaluations constrained themselves to
just monolingual snippets of text, the 2016
shared task includes a pilot subtask on computing
semantic similarity on cross-lingual
text snippets. This year’s traditional monolingual
subtask involves the evaluation of English
text snippets from the following four domains:
Plagiarism Detection, Post-Edited Machine
Translations, Question-Answering and
News Article Headlines. From the questionanswering
domain, we include both questionquestion
and answer-answer pairs. The
cross-lingual subtask provides paired SpanishEnglish
text snippets drawn from the same
sources as the English data as well as independently
sampled news data. The English subtask
attracted 43 participating teams producing
119 system submissions, while the crosslingual
Spanish-English pilot subtask attracted
10 teams resulting in 26 systems. |
Abstract:
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This material is based in part upon work supported by DARPA-BAA-12-47 DEFT grant to George Washington University, by DEFT grant #12475008 to the University of Michigan, and by a MINECO grant to the University of the Basque Country (TUNER project TIN2015-65308-C5-1-R). Aitor Gonzalez Agirre is supported by a doctoral grant from MINECO (PhD grant FPU12/06243). |
Subject(s):
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-Lingüística computacional |
Rights:
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© ACL, Creative Commons Attribution 4.0 License
http://creativecommons.org/licenses/by/4.0/ |
Document type:
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Conference Object Article - Published version |
Published by:
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ACL (Association for Computational Linguistics)
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