A Lexical Alignment Model for Probabilistic Textual Entailment

نویسندگان

  • Oren Glickman
  • Ido Dagan
  • Moshe Koppel
چکیده

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.

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تاریخ انتشار 2005