Paraphrase Substitution for Recognizing Textual Entailment

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Paraphrase Substitution for Recognizing Textual Entailment
We describe a method for recognizing textual entailment that uses the length of the longest common subsequence (LCS) between two texts as its decision criterion. Rather than requiring strict word matching in the common subsequences, we perform a flexible match using automatically generated paraphrases. We find that the use of paraphrases over strict word matches represents an average F-measure improvement from 0.22 to 0.36 on the CLEF 2006 Answer Validation Exercise for 7 languages. Categories and Subject Descriptors I.2.7 [Artificial Intelligence]: Natural Language Processing--Language parsing and understanding General Terms Experimentation, Languages, Reliability Keywords Recognizing textual entailment, Paraphrase generation, Question answering
Wauter Bosma, Chris Callison-Burch
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where CLEF
Authors Wauter Bosma, Chris Callison-Burch
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