Rule Chaining and Approximate Match in textual inference
Jonathan Berant, Eyal Shnarch, Amnon Lotan, Shachar Mirkin, Lili Kotlerman, Nahum Shimkin and Ido Dagan
In: TAC 2010 workshop, 15-Nov-2010 - 16-Nov-2010, Gaithersburg, U.S.
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 hy-
pothesis 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.