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Learning probabilistic context-free grammars from treebanks

  • Jose L. Verdú-Mas
  • Jorge Calera-Rubio
  • Rafael C. Carrasco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2905)

Abstract

This paper describes the application of a new model to learn probabilistic context-free grammars (PCFGs) from a tree bank corpus. The model estimates the probabilities according to a generalized k-gram scheme for trees.It allows for faster parsing,decreases considerably the perplexity of the test samples and tends to give more structured and refined parses.In addition,it also allows several smoothing techniques such as backing-off or interpolation that are used to avoid assigning zero probability to any sentence.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jose L. Verdú-Mas
    • 1
  • Jorge Calera-Rubio
    • 1
  • Rafael C. Carrasco
    • 1
  1. 1.Departamento de Lenguajes y Sistemas InformáticosUniversidad de AlicanteAlicanteSpain

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