• DocumentCode
    2910155
  • Title

    Research of Noun Phrase Coreference Resolution

  • Author

    Gao Junwei ; Kong Fang ; Li Peifeng ; Zhu Qiaoming

  • Author_Institution
    JiangSu Provincial Key Lab. for Comput. Inf. Process. Technol., Soochow Univ., Suzhou, China
  • fYear
    2011
  • fDate
    15-17 Nov. 2011
  • Firstpage
    93
  • Lastpage
    96
  • Abstract
    Coreference resolution is an important subtask in natural language processing systems. The process of it is to find whether two expressions in natural language refer to the same entity in the world. Machine learning approaches to this problem have been reasonably successful, operating primarily by recasting the problem as a classification task. A great deal of research has been done on this task in English, using approaches ranging from those based on linguistics to those based on machine learning. In Chinese, however, much less work has been done in this area. The lack of public resources is a big problem in the research of Chinese NLP. The other problem is that some features are more difficult to get than those features of English. In this paper, We present a noun phrase coreference system that refers to the work of Soon et al. (2001). We also explore the impact of various features on our system´s performance. Experiments on the Chinese portion of OntoNotes 3.0 show that the platform achieves a good performance.
  • Keywords
    learning (artificial intelligence); natural language processing; machine learning; natural language processing; noun phrase coreference resolution; Kernel; Machine learning; Natural language processing; Semantics; Support vector machines; Syntactics; Training; Coreference resolution; Features; Noun phrase; SVM; Similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Asian Language Processing (IALP), 2011 International Conference on
  • Conference_Location
    Penang
  • Print_ISBN
    978-1-4577-1733-8
  • Type

    conf

  • DOI
    10.1109/IALP.2011.32
  • Filename
    6121478