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Instance-based Evaluation of Entailment Rule Acquisition

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If you have a question about this talk, please contact Diarmuid Ó Séaghdha.

At the next meeting of the NLIP Reading Group we’ll be discussing the following paper:

Idan Szpektor, Eyal Shnarch and Ido Dagan. 2007. Instance-based Evaluation of Entailment Rule Acquisition. Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-07).


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.

This talk is part of the Natural Language Processing Reading Group series.

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