• DocumentCode
    3489534
  • Title

    Improve Chinese Semantic Dependency Parsing via Syntactic Dependency Parsing

  • Author

    Meishan Zhang ; Wanxiang Che ; Yanqiu Shao ; Ting Liu

  • Author_Institution
    Res. Center for Social Comput. & Inf. Retrieval, Harbin Inst. of Technol., Harbin, China
  • fYear
    2012
  • fDate
    13-15 Nov. 2012
  • Firstpage
    53
  • Lastpage
    56
  • Abstract
    We address the problem of Chinese semantic dependency parsing. Dependency parsing is traditionally oriented to syntax analysis, which we denote by syntactic dependency parsing to distinguish it from semantic dependency parsing. In this paper, firstly we compare Chinese semantic dependency parsing and syntactic dependency parsing systematically, showing that syntactic dependency parsing can potentially improve the performance of semantic dependency parsing. Thus then we suggest an approach based on quasi-synchronous grammar to incorporate the auto-parsed syntactic dependency tree into semantic dependency parsing. We conduct experiments on the Chinese semantic dependency parsing corpus of SemEval-2012. Finally we achieve 65.25% LAS on test corpus, gaining increases of 2.45% compared to the top result of 62.80% in SemEval-2012.
  • Keywords
    grammars; natural language processing; programming language semantics; text analysis; trees (mathematics); Chinese semantic dependency parsing corpus; LAS; SemEval-2012; autoparsed syntactic dependency tree; quasisynchronous grammar; syntactic dependency parsing; syntax analysis; test corpus; Computational linguistics; Conferences; Electronic mail; Grammar; Joints; Semantics; Syntactics; Quasi-synchronous Grammar; Semantic Dependency Parsing; Syntactic Dependency Parsing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Asian Language Processing (IALP), 2012 International Conference on
  • Conference_Location
    Hanoi
  • Print_ISBN
    978-1-4673-6113-2
  • Electronic_ISBN
    978-0-7695-4886-9
  • Type

    conf

  • DOI
    10.1109/IALP.2012.42
  • Filename
    6473694