A lightweight dependency analyzer for partial parsing

  • Authors:
  • Bangalore Srinivas

  • Affiliations:
  • AT&T Labs –– Research, 180 Park Avenue, Florham Park, NJ 07932, USA

  • Venue:
  • Natural Language Engineering
  • Year:
  • 2000

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Abstract

In this paper, we present a novel approach to partial parsing that produces dependency links between words of a sentence. The partial parser called a lightweight dependency analyzer uses information encoded in supertags and hence can produce constituency-based as well as dependency-based analyses. The lightweight dependency analyzer has been used for text chunking, including noun and verb group chunking. We also present a proposal for a general framework for parser evaluation that is applicable for evaluating both constituency-based and dependency-based, partial and complete parsers. The performance results of the lightweight dependency analyzer on Wall Street Journal and Brown corpus using the proposed evaluation metrics are discussed.