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Rule Chaining and Approximate Match in textual inference

By Asher Stern, Eyal Shnarch, Amnon Lotan, Shachar Mirkin, Lili Kotlerman, Jonathan Berant and Ido Dagan

Abstract

This paper describes the participation of Bar-Ilan university in the sixth RTE challenge. Our textual-entailment engine, BiuTee, was enhanced with new components that introduce chaining of lexical-entailment rules, and tackle the problem of approximately matching the text and the hypothesis after all available knowledge of entailment rules was utilized. We have also re-engineered our system aiming at an open-source open architecture. BiuTee’s performance is better than the median of all-submissions, and outperforms significantly an IR-oriented baseline.

Year: 2010
OAI identifier: oai:CiteSeerX.psu:10.1.1.418.7637
Provided by: CiteSeerX
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