PKU-HIT: An event detection system based on instances expansion and rich syntactic features

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

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

1 Citation (Scopus)

Abstract

This paper describes the PKU-HIT system on event detection in the SemEval-2010 Task. We construct three modules for the three sub-tasks of this evaluation. For target verb WSD, we build a Naïve Bayesian classifier which uses additional training instances expanded from an untagged Chinese corpus automatically. For sentence SRL and event detection, we use a feature-based machine learning method which makes combined use of both constituent-based and dependencybased features. Experimental results show that the Macro Accuracy of the WSD module reaches 83.81% and F-Score of the SRL module is 55.71%.
Original languageEnglish
Title of host publicationACL 2010 - SemEval 2010 - 5th International Workshop on Semantic Evaluation, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages304-307
Number of pages4
ISBN (Electronic)1932432701, 9781932432701
Publication statusPublished - 1 Jan 2010
Event5th International Workshop on Semantic Evaluation, SemEval 2010 - Uppsala University, Uppsala, Sweden
Duration: 15 Jul 201016 Jul 2010

Conference

Conference5th International Workshop on Semantic Evaluation, SemEval 2010
CountrySweden
CityUppsala
Period15/07/1016/07/10

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Theoretical Computer Science

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