Efficient tabular LR parsing

  • Authors:
  • Mark-Jan Nederhof;Giorgio Satta

  • Affiliations:
  • University of Groningen, Groningen, The Netherlands;Università di Padova, Padova, Italy

  • Venue:
  • ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
  • Year:
  • 1996

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Abstract

We give a new treatment of tabular LR parsing, which is an alternative to Tomita's generalized LR algorithm. The advantage is twofold. Firstly, our treatment is conceptually more attractive because it uses simpler concepts, such as grammar transformations and standard tabulation techniques also know as chart parsing. Secondly, the static and dynamic complexity of parsing, both in space and time, is significantly reduced.