Automatic Relation Extraction with Model Order Selection and Discriminative Label Identification

  • Chen Jinxiu
  • Ji Donghong
  • Tan Chew Lim
  • Niu Zhengyu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3651)


In this paper, we study the problem of unsupervised relation extraction based on model order identification and discriminative feature analysis. The model order identification is achieved by stability-based clustering and used to infer the number of the relation types between entity pairs automatically. The discriminative feature analysis is used to find discriminative feature words to name the relation types. Experiments on ACE corpus show that the method is promising.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Chen Jinxiu
    • 1
  • Ji Donghong
    • 1
  • Tan Chew Lim
    • 2
  • Niu Zhengyu
    • 1
  1. 1.Institute of Infocomm ResearchSingapore
  2. 2.Department of Computer ScienceNational University of SingaporeSingapore

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