A Novel Composite Kernel Approach to Chinese Entity Relation Extraction

  • Ji Zhang
  • You Ouyang
  • Wenjie Li
  • Yuexian Hou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5459)


Relation extraction is the task of finding semantic relations between two entities from the text. In this paper, we propose a novel composite kernel for Chinese relation extraction. The composite kernel is defined as the combination of two independent kernels. One is the entity kernel built upon the non-content-related features. The other is the string semantic similarity kernel concerning the content information. Three combinations, namely linear combination, semi-polynomial combination and polynomial combination are investigated. When evaluated on the ACE 2005 Chinese data set, the results show that the proposed approach is effective.


Kernel-based Chinese Relation Extraction Composite Kernel Entity Kernel String Semantic Similarity Kernel 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ji Zhang
    • 1
    • 2
  • You Ouyang
    • 1
  • Wenjie Li
    • 1
  • Yuexian Hou
    • 2
  1. 1.Department of ComputingThe Hong Kong Polytechnic UniversityHong Kong
  2. 2.School of Computer Science and TechnologyTianjin UniversityChina

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