A dependency-based method for evaluating broad-coverage parsers

  • Authors:
  • Dekang Lin

  • Affiliations:
  • Department of Computer Science, University of Manitoba, Winnipeg, Manitoba, Canada

  • Venue:
  • IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1995

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Abstract

With the emergence of broad-coverage parsers, quantitative evaluation of parsers becomes increasingly more important. We propose a dependency-based method for evaluating broad-coverage parsers. The method offers several advantages over previous methods that are based on phrase boundaries The error count score. We propose here is not only more intuitively meaningful than other scores, but also more relevant to semantic interpretation. We will also present an algorithm for transforming constituency trees into dependency trees so that the evaluation method is applicable to both dependency and constituency grammars. Finally, we discuss a set of operations for modifying dependency trees that can be used lo eliminate inconsequential differences among different parse trees and allow us to selectively evaluate different aspects of a parser.