• DocumentCode
    1909908
  • Title

    Non-negative Matrix Factorisation-Based Verb Semantics for 3rd Person Pronoun Resolution

  • Author

    Tuggener, Don ; Klenner, Manfred

  • Author_Institution
    Inst. of Comput. Linguistics, Univ. of Zurich, Zurich, Switzerland
  • fYear
    2012
  • fDate
    19-21 Sept. 2012
  • Firstpage
    250
  • Lastpage
    254
  • Abstract
    We present an initial utility study of a distributionalmodel of verb selectional preferences for 3rd personpronoun resolution in German. We investigate cases in which3rd person pronouns occur as subjects of transitive verbs. Ineach such case, the likelihood of inserting one of the antecedentcandidates is calculated as the conditional probability of theantecedent candidate given either the verb governing thepronoun or the object of the verb. These probabilities areestimated using a matrix derived from frequency counts ina large corpus. Non-negative matrix factorisation is appliedas a sort of semantic smoothing to address the sparsity issueinherent in the approach.
  • Keywords
    matrix decomposition; natural language processing; probability; smoothing methods; 3rd person pronoun resolution; German; antecedent candidates; conditional probability; distributional model; nonnegative matrix factorisation; semantic smoothing; transitive verbs; verb selectional preference; verb semantics; Accuracy; Computational linguistics; Probabilistic logic; Semantics; Smoothing methods; Sparse matrices; Vectors; verb semantics; anaphora resolution; distributional;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing (ICSC), 2012 IEEE Sixth International Conference on
  • Conference_Location
    Palermo
  • Print_ISBN
    978-1-4673-4433-3
  • Type

    conf

  • DOI
    10.1109/ICSC.2012.64
  • Filename
    6337112