Evaluation of dependency parsers on unbounded dependencies

  • Authors:
  • Joakim Nivre;Laura Rimell;Ryan McDonald;Carlos Gómez-Rodríguez

  • Affiliations:
  • Uppsala University;Univ. of Cambridge;Google Inc.;Universidade da Coruña

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

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Abstract

We evaluate two dependency parsers, MSTParser and MaltParser, with respect to their capacity to recover unbounded dependencies in English, a type of evaluation that has been applied to grammar-based parsers and statistical phrase structure parsers but not to dependency parsers. The evaluation shows that when combined with simple post-processing heuristics, the parsers correctly recall unbounded dependencies roughly 50% of the time, which is only slightly worse than two grammar-based parsers specifically designed to cope with such dependencies.