Putting pieces together: combining FrameNet, VerbNet and WordNet for robust semantic parsing

  • Authors:
  • Lei Shi;Rada Mihalcea

  • Affiliations:
  • Computer Science Department, University of North Texas, Denton, TX;Computer Science Department, University of North Texas, Denton, TX

  • Venue:
  • CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
  • Year:
  • 2005

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Abstract

This paper describes our work in integrating three different lexical resources: FrameNet, VerbNet, and WordNet, into a unified, richer knowledge-base, to the end of enabling more robust semantic parsing. The construction of each of these lexical resources has required many years of laborious human effort, and they all have their strengths and shortcomings. By linking them together, we build an improved resource in which (1) the coverage of FrameNet is extended, (2) the VerbNet lexicon is augmented with frame semantics, and (3) selectional restrictions are implemented using WordNet semantic classes. The synergistic exploitation of various lexical resources is crucial for many complex language processing applications, and we prove it once again effective in building a robust semantic parser.