A Lexical Alignment Model for Probabilistic Textual Entailment

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.

• Type: Conference
• Year: 2005
• Where: MLCW
• Authors: Oren Glickman, Ido Dagan, Moshe Koppel
• Keywords: Lexical Entailment, Machine Learning, MLCW 2005, Textual Entailment, Textual Entailment Challenge