Can Subcategorisation Probabilities Help a Statistical Parser

Research into the automatic acquisition of lexical information from corpora is starting to produce large-scale computational lexicons containing data on the relative frequencies of subcategorisation alternatives for individual verbal predicates. However, the empirical question of whether this type of frequency information can in practice improve the accuracy of a statistical parser has not yet been answered. In this paper we describe an experiment with a wide-coverage statistical grammar and parser for English and subcategorisation frequencies acquired from ten million words of text which shows that this information can significantly improve parse accuracy.

• Publication year

  1998

• Venue

  VLC@COLING/ACL

• Publication date

  1998-06-01

• Fields of study

  Linguistics, Computer Science

• Identifiers
  arXiv cmp-lg/9806013
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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