Abstract
This paper describes the Bar-Ilan system participating in the Recognising Textual Entailment Challenge. The paper proposes first a general probabilistic setting that formalizes the notion of textual entailment. We then describe a concrete alignment-based model for lexical entailment, which utilizes web co-occurrence statistics in a bag of words representation. Finally, we report the results of the model on the Recognising Textual Entailment challenge dataset along with some analysis. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Glickman, O., Dagan, I., & Koppel, M. (2006). A lexical alignment model for probabilistic textual entailment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3944 LNAI, pp. 287–298). Springer Verlag. https://doi.org/10.1007/11736790_16
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