SVO triple based Latent Semantic Analysis for recognising textual entailment

Burek, Gaston; Pietsch, Christian and De Roeck, Anne (2007). SVO triple based Latent Semantic Analysis for recognising textual entailment. In: ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (WTEP), 28-29 Jun 2007, Prague, Czech Republic.

DOI: https://doi.org/10.3115/1654536.1654559

URL: http://ufal.mff.cuni.cz/acl2007/workshops/program/...

Abstract

Latent Semantic Analysis has only recently been applied to textual entailment recognition. However, these efforts have suffered from inadequate bag of words vector representations. Our prototype implementation for the Third Recognising Textual Entailment Challenge (RTE-3) improves the approach by applying it to vector representations that contain semi-structured representations of words. It uses variable size n-grams of word stems to model independently verbs, subjects and objects displayed in textual statements. The system performance shows positive results and provides insights about how to improve them further.

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About

• Item ORO ID
• 10016
• Item Type
• Conference or Workshop Item
• Extra Information
• Held in conjunction with the 45th Annual Meeting of the Association of Computational Linguistics (ACL 2007), pages 113�118
• Keywords
• textual entailment; Latent Semantic Analysis; LSA; Singular Value Decomposition; SVD; subject-verb-object triple; SVO; subject-predicate-object triple; SPO; applied semantics
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
• Depositing User
• Christian Pietsch