Unbounded Dependency Recovery for Parser Evaluation

نویسندگان

  • Laura Rimell
  • Stephen Clark
  • Mark Steedman
چکیده

This paper introduces a new parser evaluation corpus containing around 700 sentences annotated with unbounded dependencies, from seven different grammatical constructions. We run a series of off-theshelf parsers on the corpus to evaluate how well state-of-the-art parsing technology is able to recover such dependencies. The overall results range from 25% accuracy to 59%. These low scores call into question the validity of using Parseval scores as a general measure of parsing capability. We discuss the importance of parsers being able to recover unbounded dependencies, given their relatively low frequency in corpora. We also analyse the various errors made on these constructions by one of the more successful parsers.

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تاریخ انتشار 2009