LIARc: Labeling Implicit ARguments in Spanish Deverbal Nominalizations

  • Aina Peris
  • Mariona Taulé
  • Horacio Rodríguez
  • Manuel Bertran Ibarz
Conference paper

DOI: 10.1007/978-3-642-37247-6_34

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7816)
Cite this paper as:
Peris A., Taulé M., Rodríguez H., Bertran Ibarz M. (2013) LIARc: Labeling Implicit ARguments in Spanish Deverbal Nominalizations. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2013. Lecture Notes in Computer Science, vol 7816. Springer, Berlin, Heidelberg

Abstract

This paper deals with the automatic identification and annotation of the implicit arguments of deverbal nominalizations in Spanish. We present the first version of the LIAR system focusing on its classifier component. We have built a supervised Machine Learning feature based model that uses a subset of AnCora-Es as a training corpus. We have built four different models and the overall F-Measure is 89.9%, which means an increase F-Measure performance approximately 35 points over the baseline (55%). However, a detailed analysis of the feature performance is still needed. Future work will focus on using LIAR to automatically annotate the implicit arguments in the whole AnCora-Es.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Aina Peris
    • 1
  • Mariona Taulé
    • 1
  • Horacio Rodríguez
    • 2
  • Manuel Bertran Ibarz
    • 1
  1. 1.CLiC, Centre de Llenguatge i ComputacióUniversity of BarcelonaBarcelonaSpain
  2. 2.Technical University of Catalonia TALP Research CenterBarcelonaSpain

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