Combining constituent and dependency syntactic views for chinese semantic role labeling

Shiqi Li, Qin Lu, Tiejun Zhao, Pengyuan Liu, Hanjing Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


This paper presents a novel feature-based semantic role labeling (SRL) method which uses both constituent and dependency syntactic views. Comparing to the traditional SRL method relying on only one syntactic view, the method has a much richer set of syntactic features. First we select several important constituent-based and dependency- based features from existing studies as basic features. Then, we propose a statistical method to select discriminative combined features which are composed by the basic features. SRL is achieved by using the SVM classifier with both the basic features and the combined features. Experimental results on Chinese Proposition Bank (CPB) show that the method outperforms the traditional constituent-based or dependency-based SRL methods.
Original languageEnglish
Title of host publicationColing 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference
Number of pages9
Publication statusPublished - 1 Dec 2010
Event23rd International Conference on Computational Linguistics, Coling 2010 - Beijing, China
Duration: 23 Aug 201027 Aug 2010


Conference23rd International Conference on Computational Linguistics, Coling 2010

ASJC Scopus subject areas

  • Language and Linguistics
  • Computational Theory and Mathematics
  • Linguistics and Language

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