- Title
- Learning parse-free event-based features for textual entailment recognition
- Creator
- Ofoghi, Bahadorreza; Yearwood, John
- Date
- 2010
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/40927
- Identifier
- vital:3838
- Identifier
- ISBN:0302-9743
- Abstract
- We 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. © 2010 Springer-Verlag.
- Publisher
- Adelaide, SA Springer
- Relation
- Paper presented at 23rd Australasian Joint Conference on Artificial Intelligence, AI 2010 Vol. 6464 LNAI, p. 184-193
- Rights
- This metadata is freely available under a CCO license
- Subject
- Compositional semantics; Event-based; Machine-learning; Semantic features; Textual entailment; Artificial intelligence; Feature extraction; Text processing; Semantics
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