Improving Question Answering Tasks by Textual Entailment Recognition

Authors:
Óscar Ferrández;Rafael Muñoz;Manuel Palomar
Affiliations:
Natural Language Processing and Information Systems Group Department of Computing Languages and Systems, University of Alicante,;Natural Language Processing and Information Systems Group Department of Computing Languages and Systems, University of Alicante,;Natural Language Processing and Information Systems Group Department of Computing Languages and Systems, University of Alicante,
Venue:
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Year:
2008

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Abstract

This paper explores a suitable way to integrate a Textual Entailment (TE) system, which detects unidirectional semantic inferences, into Question Answering (QA) tasks. We propose using TE as an answer validation engine to improve QA systems, and we evaluate its performance using the Answer Validation Exerciseframework. Results point out that our TE system can improve the QA task considerably.