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Partial Predicate Argument Structure Matching for Entailment Determination

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Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment (MLCW 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3944))

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Abstract

The Computational Linguistics at Concordia laboratory system for textual entailment determination is based on shallow, partial predicate-argument structure matching combined with a WordNet-based lexical similarity measure. In this paper we describe experiments with different system settings conducted to assess the potential and limitations of partial predicate-argument structures in textual entailment determination.

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Author information

Authors and Affiliations

  1. Concordia University, 1455 De Maisonneuve Blvd. West, Montreal, Quebec, H3G 1M8, Canada

    Alina Andreevskaia, Zhuoyan Li & Sabine Bergler

Authors
  1. Alina Andreevskaia
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  2. Zhuoyan Li
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  3. Sabine Bergler
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Editor information

Editors and Affiliations

  1. Max Planck Institute for Biological Cybernetics, Spemannstr. 38, Tübingen, Germany

    Joaquin Quiñonero-Candela

  2. Bar Ilan University, 52900, Ramat Gan, Israel

    Ido Dagan

  3. ITC-IRST, Trento, Italy

    Bernardo Magnini

  4. Université d’Evry-Val d’Essonne, IBISC CNRS FRE 2873 and GENPOLE, 523, Place des terrasses, 91000, Evry, France

    Florence d’Alché-Buc

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© 2006 Springer-Verlag Berlin Heidelberg

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Andreevskaia, A., Li, Z., Bergler, S. (2006). Partial Predicate Argument Structure Matching for Entailment Determination. In: Quiñonero-Candela, J., Dagan, I., Magnini, B., d’Alché-Buc, F. (eds) Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment. MLCW 2005. Lecture Notes in Computer Science(), vol 3944. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11736790_19

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  • DOI: https://doi.org/10.1007/11736790_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33427-9

  • Online ISBN: 978-3-540-33428-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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