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Learning parse-free event-based features for textual entailment recognition
conference contribution
posted on 2010-01-01, 00:00 authored by Bahadorreza OfoghiBahadorreza Ofoghi, John YearwoodJohn YearwoodWe propose new parse-free event-based features to be used in conjunction with lexical, syntactic, and semantic features of texts and hypotheses for Machine Learning-based Recognizing Textual Entailment. Our new similarity features are extracted without using shallow semantic parsers, but still lexical and compositional semantics are not left out. Our experimental results demonstrate that these features can improve the effectiveness of the identification of entailment and no-entailment relationships.
History
Event
Australian Computer Society National Committee for Artificial Intelligence. Conference (23rd : 2010 : Adelaide, S. Aust.)Volume
6464Pagination
184 - 193Publisher
SpringerLocation
Adelaide, S. Aust.Place of publication
Berlin, GermanyPublisher DOI
Start date
2010-10-07End date
2010-10-10ISBN-13
978-3-642-17431-5ISBN-10
3642174310Language
engPublication classification
E1.1 Full written paper - refereed; E Conference publicationCopyright notice
2010, Springer-Verlag Berlin HeidelbergTitle of proceedings
AI 2010 : Proceedings of the 23rd Australasian Joint Conference on Artificial IntelligenceUsage metrics
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