PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Instance-based Evaluation of Entailment Rule Acquisition
Idan Szpektor, Eyal Shnarch and Ido Dagan
In: 45th Annual Meeting of the Association for Computational Linguistics, 23-30 June 2007, Prague, Czech Republic.

Abstract

Obtaining large volumes of inference knowledge, such as entailment rules, has become a major factor in achieving robust semantic processing. While there has been substantial research on learning algorithms for such knowledge, their evaluation methodology has been problematic, hindering further research. We propose a novel evaluation methodology for entailment rules which explicitly addresses their semantic properties and yields satisfactory human agreement levels. The methodology is used to compare two state of the art learning algorithms, exposing critical issues for future progress.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:2988
Deposited By:Idan Szpektor
Deposited On:09 February 2008