A Semantic Oriented Approach to Textual Entailment Using WordNet-Based Measures

  • Julio J. Castillo
Conference paper

DOI: 10.1007/978-3-642-16761-4_5

Volume 6437 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Castillo J.J. (2010) A Semantic Oriented Approach to Textual Entailment Using WordNet-Based Measures. In: Sidorov G., Hernández Aguirre A., Reyes García C.A. (eds) Advances in Artificial Intelligence. MICAI 2010. Lecture Notes in Computer Science, vol 6437. Springer, Berlin, Heidelberg

Abstract

In this paper, we present a Recognizing Textual Entailment system which uses semantic similarity metrics to sentence level only using WordNet as source of knowledge. We show how the widely used semantic measures WordNet-based can be generalized to build sentence level semantic metrics in order to be used in the RTE. We also provide an analysis of efficiency of these metrics and drawn some conclusions about their utility in the practice in recognizing textual entailment. We also show that using the proposed method to extend word semantic measures could be used in building an average score system that only uses semantic information from WordNet.

Keywords

Recognizing Textual Entailment WordNet Semantic Similarity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Julio J. Castillo
    • 1
    • 2
  1. 1.National University of Cordoba-FaMAFCordobaArgentina
  2. 2.National Technological University-FRCCordobaArgentina