Adaptive Probabilistic Generalized LR Parsing

Jerry Wright, Ave Wrigley, Richard Sharman


Abstract
Various issues in the implementation of generalized LR parsing with probability are discussed. A method for preventing the generation of infinite numbers of states is described and the space requirements of the parsing tables are assessed for a substantial natural-language grammar. Because of a high degree of ambiguity in the grammar, there are many multiple entries and the tables are rather large. A new method for grammar adaptation is introduced which may help to reduce this problem. A probabilistic version of the Tomita parse forest is also described.
Anthology ID:
1991.iwpt-1.12
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:
100–109
Language:
URL:
https://aclanthology.org/1991.iwpt-1.12
DOI:
Bibkey:
Cite (ACL):
Jerry Wright, Ave Wrigley, and Richard Sharman. 1991. Adaptive Probabilistic Generalized LR Parsing. In Proceedings of the Second International Workshop on Parsing Technologies, pages 100–109, Cancun, Mexico. Association for Computational Linguistics.
Cite (Informal):
Adaptive Probabilistic Generalized LR Parsing (Wright et al., IWPT 1991)
Copy Citation:
PDF:
https://aclanthology.org/1991.iwpt-1.12.pdf