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

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Advances in Artificial Intelligence (MICAI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6437))

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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.

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Author information

Authors and Affiliations

  1. National University of Cordoba-FaMAF, Cordoba, Argentina

    Julio J. Castillo

  2. National Technological University-FRC, Cordoba, Argentina

    Julio J. Castillo

Authors
  1. Julio J. Castillo
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Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, Centro de Investigación en Computación, Av. Juan Dios Batiz, s/n, Zacatenco, 07738, Mexico City, México

    Grigori Sidorov

  2. Area de Computación, Centro de Investigación en Matemáticas (CIMAT), Callejón de Jalisco s/n, Mineral de Valenciana, 36240, Guanajuato, México

    Arturo Hernández Aguirre

  3. Instituto Nacional de Astrofísica, Optica y Electrónica (INAOE), Ciencias Computacionales, Luis Enrique Erro No. 1, 72840, Santa María Tonantzintla, Puebla,, México

    Carlos Alberto Reyes García

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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. https://doi.org/10.1007/978-3-642-16761-4_5

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  • DOI: https://doi.org/10.1007/978-3-642-16761-4_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16760-7

  • Online ISBN: 978-3-642-16761-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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