Effectively using syntax for recognizing false entailment

Authors:
Rion Snow;Lucy Vanderwende;Arul Menezes
Affiliations:
Stanford University, Stanford, CA;Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA
Venue:
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Year:
2006

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Abstract

Recognizing textual entailment is a challenging problem and a fundamental component of many applications in natural language processing. We present a novel framework for recognizing textual entailment that focuses on the use of syntactic heuristics to recognize false entailment. We give a thorough analysis of our system, which demonstrates state-of-the-art performance on a widely-used test set.