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@inproceedings{1308719,
author = {Baisa, Vít and Bradbury, Jane and Cinková, Silvie and El Maarouf, Ismaïl and Kilgarriff, Adam and Popescu, Octavian},
address = {Denver, Colorado},
booktitle = {Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)},
keywords = {semeval; corpus pattern analysis; concordance clustering; semantic evaluation},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Denver, Colorado},
isbn = {978-1-941643-40-2},
pages = {315-324},
publisher = {Association for Computational Linguistics},
title = {SemEval-2015 Task 15: A CPA dictionary-entry-building task},
url = {http://www.aclweb.org/anthology/S15-2053},
year = {2015}
}
TY - JOUR
ID - 1308719
AU - Baisa, Vít - Bradbury, Jane - Cinková, Silvie - El Maarouf, Ismaïl - Kilgarriff, Adam - Popescu, Octavian
PY - 2015
TI - SemEval-2015 Task 15: A CPA dictionary-entry-building task
PB - Association for Computational Linguistics
CY - Denver, Colorado
SN - 9781941643402
KW - semeval
KW - corpus pattern analysis
KW - concordance clustering
KW - semantic evaluation
UR - http://www.aclweb.org/anthology/S15-2053
N2 - This paper describes the first SemEval task to explore the use of Natural Language Processing systems for building dictionary entries, in the framework of Corpus Pattern Analysis. CPA is a corpus-driven technique which provides tools and resources to identify and represent unambiguously the main semantic patterns in which words are used. Task 15 draws on the Pattern Dictionary of English Verbs (www.pdev.org.uk), for the targeted lexical entries, and on the British National Corpus for the input text. Dictionary entry building is split into three subtasks which all start from the same concordance sample: 1) CPA parsing, where arguments and their syntactic and semantic categories have to be identified, 2) CPA clustering, in which sentences with similar patterns have to be clustered and 3) CPA automatic lexicography where the structure of patterns have to be constructed automatically. Subtask 1 attracted 3 teams, though none could beat the baseline (rule-based system). Subtask 2 attracted 2 teams, one of which beat the baseline (majority-class classifier). Subtask 3 did not attract any participant. The task has produced a major semantic multidataset resource which includes data for 121 verbs and about 17,000 annotated sentences, and which is freely accessible.
ER -
BAISA, Vít, Jane BRADBURY, Silvie CINKOVÁ, Ismaïl EL MAAROUF, Adam KILGARRIFF a Octavian POPESCU. SemEval-2015 Task 15: A CPA dictionary-entry-building task. Online. In \textit{Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)}. Denver, Colorado: Association for Computational Linguistics, 2015, s.~315-324. ISBN~978-1-941643-40-2.
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