• DocumentCode
    258691
  • Title

    Pronominal anaphora resolution using salience score for Malayalam

  • Author

    Athira, S. ; Lekshmi, T.S. ; Rajeev, R.R. ; Sherly, Elizabeth ; Reghuraj, P.C.

  • fYear
    2014
  • fDate
    17-18 Dec. 2014
  • Firstpage
    47
  • Lastpage
    51
  • Abstract
    Anaphora resolution (AR) is the process of resolving references to an entity in the discourse. The paper presents an algorithm to identify the pronominals and its antecedents in the Malayalam text input. Anaphora resolution is achieved by employing a hybrid of statistical machine learning and rule based approaches. The system is implemented by exploiting the morphological richness of the language and it makes use of parts of speech tagging, subject-object identification and person-number-gender of the NPs. We outline a simple, efficient but a naive algorithm for anaphora resolution, which computes the salience value score for each antecedents. The system performance is evaluated with precision, recall measures which produced promising results. The anaphora resolution system itself can improve the performance of many NLP applications such as text summarisation, text categorisation and term extraction.
  • Keywords
    natural language processing; text analysis; AR; Malayalam text input; NLP applications; person-number-gender; pronominal anaphora resolution system; salience score; salience value score; speech tagging; statistical machine learning; subject-object identification; term extraction; text categorisation; text summarisation; Accuracy; Decision trees; Hidden Markov models; Machine learning algorithms; Speech; Tagging; Training; Anaphora resolution; antecedents; discourse; pronominals; salience value;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Systems and Communications (ICCSC), 2014 First International Conference on
  • Conference_Location
    Trivandrum
  • Print_ISBN
    978-1-4799-6012-5
  • Type

    conf

  • DOI
    10.1109/COMPSC.2014.7032619
  • Filename
    7032619