Automatic Identification of Persian Light Verb Constructions

  • Bahar Salehi
  • Narjes Askarian
  • Afsaneh Fazly
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7181)

Abstract

Multiword expressions pose a challenge to the development of large-scale, semantically-rich Natural Language Processing (NLP) systems. We use a bilingual parallel corpus for automatically extracting Light Verb Constructions (LVCs), a very common type of multiword expressions in many languages, including Persian. Using two classifiers, we investigate the usefulness of seven linguistically-informed features for automatically identifying Persian LVCs. To our knowledge, this is the first attempt at the automatic detection of a broad class of Persian LVCs. Results of our experiments show that the proposed features are reasonably successful at the task.

Keywords

Machine Translation Area Under Curve Statistical Machine Translation Common Link Alignment Direction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bahar Salehi
    • 1
  • Narjes Askarian
    • 1
  • Afsaneh Fazly
    • 2
  1. 1.School of Electrical and Computer EngineeringShiraz UniversityIran
  2. 2.School of Computer ScienceInstitute for Research in Fundamental Sciences (IPM)Iran

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