• DocumentCode
    3452363
  • Title

    A class-based acceptability measure for persian light verb constructions

  • Author

    Taslimipoor, Shiva ; Fazly, Afsaneh ; Hamzeh, Ali

  • Author_Institution
    Electerical & Comput. Eng., Shiraz Univ., Shiraz, Iran
  • fYear
    2012
  • fDate
    2-3 May 2012
  • Firstpage
    250
  • Lastpage
    255
  • Abstract
    Light verb constructions (LVCs), also known as compound verbs, require spacial treatment within a computational system. Recently, there has been some work on the automatic identification of LVCs, in resource-rich languages, such as English. Our goal is to adapt such existing techniques for the automatic treatment of LVCs in an under-resourced language, such as Persian. We focus on the most common subclass of Persian LVCs which are noun+verb constructions. LVCs are often formed semi-productively: Although a light verb occurs with a wide range of nouns, it tends to productively combine with certain semantic classes to form LVCs. We expand an existing measure of determining LVC acceptability (for English) to make explicit use of semantic classes of nouns (in Persian). We show that this new class-based acceptability measure outperforms the original measure, when applied to Persian candidate LVCs.
  • Keywords
    natural language processing; English; Persian LVC; Persian light verb constructions; class-based acceptability measure; compound verbs; noun semantic class; noun-verb constructions; resource-rich languages; underresourced language; Educational institutions; Electronic mail; Estimation; Frequency estimation; Semantics; Vectors; Light Verb Constructions; Multiword Expressions; Natural Language Processing; Semi-productivity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on
  • Conference_Location
    Shiraz, Fars
  • Print_ISBN
    978-1-4673-1478-7
  • Type

    conf

  • DOI
    10.1109/AISP.2012.6313753
  • Filename
    6313753