Probabilistic LR Parsing for General Context-Free Grammars

See-Kiong Ng, Masaru Tomita


Abstract
To combine the advantages of probabilistic grammars and generalized LR parsing, an algorithm for constructing a probabilistic LR parser given a probabilistic context-free grammar is needed. In this paper, implementation issues in adapting Tomita’s generalized LR parser with graph-structured stack to perform probabilistic parsing are discussed. Wright and Wrigley (1989) has proposed a probabilistic LR-table construction algorithm for non-left-recursive context-free grammars. To account for left recursions, a method for computing item probabilities using the generation of systems of linear equations is presented. The notion of deferred probabilities is proposed as a means for dealing with similar item sets with differing probability assignments.
Anthology ID:
1991.iwpt-1.18
Volume:
Proceedings of the Second International Workshop on Parsing Technologies
Month:
February 13-25
Year:
1991
Address:
Cancun, Mexico
Editors:
Masaru Tomita, Martin Kay, Robert Berwick, Eva Hajicova, Aravind Joshi, Ronald Kaplan, Makoto Nagao, Yorick Wilks
Venue:
IWPT
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
154–163
Language:
URL:
https://aclanthology.org/1991.iwpt-1.18
DOI:
Bibkey:
Cite (ACL):
See-Kiong Ng and Masaru Tomita. 1991. Probabilistic LR Parsing for General Context-Free Grammars. In Proceedings of the Second International Workshop on Parsing Technologies, pages 154–163, Cancun, Mexico. Association for Computational Linguistics.
Cite (Informal):
Probabilistic LR Parsing for General Context-Free Grammars (Ng & Tomita, IWPT 1991)
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PDF:
https://aclanthology.org/1991.iwpt-1.18.pdf