Shallow case role annotation using two-stage feature-enhanced string matching

  • Authors:
  • Samuel W. K. Chan

  • Affiliations:
  • Dept. of Decision Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China

  • Venue:
  • CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
  • Year:
  • 2006

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Abstract

A two-stage annotation method for identification of case roles in Chinese sentences is proposed. The approach makes use of a feature-enhanced string matching technique which takes full advantage of a huge number of sentence patterns in a Treebank. The first stage of the approach is a coarse-grained syntactic parsing which is complementary to a semantic dissimilarities analysis in its latter stage. The approach goes beyond shallow parsing to a deeper level of case role identification, while preserving robustness, without being bogged down into a complete linguistic analysis. The ideas described have been implemented and an evaluation of 5,000 Chinese sentences is examined in order to justify its significances.