Data-driven parsing with probabilistic linear context-free rewriting systems

  • Authors:
  • Laura Kallmeyer;Wolfgang Maier

  • Affiliations:
  • University of Tübingen;University of Tübingen

  • Venue:
  • COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
  • Year:
  • 2010

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Abstract

This paper presents a first efficient implementation of a weighted deductive CYK parser for Probabilistic Linear Context-Free Rewriting Systems (PLCFRS), together with context-summary estimates for parse items used to speed up parsing. LCFRS, an extension of CFG, can describe discontinuities both in constituency and dependency structures in a straightforward way and is therefore a natural candidate to be used for data-driven parsing. We evaluate our parser with a grammar extracted from the German NeGra treebank. Our experiments show that data-driven LCFRS parsing is feasible with a reasonable speed and yields output of competitive quality.