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 entail-ment 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. © 2006 Association for Computational Linguistics.
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CITATION STYLE
Snow, R., Vanderwende, L., & Menezes, A. (2006). Effectively using syntax for recognizing false entailment. In HLT-NAACL 2006 - Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings of the Main Conference (pp. 33–40). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1220835.1220840
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