Error-Driven Pruning of Treebank Grammars for Base Noun Phrase Identification

Finding simple, non-recursive, base noun phrases is an important subtask for many natural language processing applications. While previous empirical methods for base NP identification have been rather complex, this paper instead proposes a very simple algorithm that is tailored to the relative simplicity of the task. In particular, we present a corpus-based approach for finding base NPs by matching part-of-speech tag sequences. The training phase of the algorithm is based on two successful techniques: first the base NP grammar is read from a "treebank" corpus; then the grammar is improved by selecting rules with high "benefit" scores. Using this simple algorithm with a naive heuristic for matching rules, we achieve surprising accuracy in an evaluation on the Penn Treebank Wall Street Journal.

• Publication year

  1998

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  1998-08-10

• Fields of study

  Computer Science

• Identifiers
  DOI 10.3115/980845.980881arXiv cmp-lg/9808015
• 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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