Estimators for Stochastic "Unification-Based'' Grammars

Mark Johnson, Stuart Geman, Stephen Canon, Zhiyi Chi, Stefan Riezler

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

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Log-linear models provide a statistically sound framework for Stochastic "Unification-Based" Grammars (SUBGs) and stochastic versions of other kinds of grammars. We describe two computationally-tractable ways of estimating the parameters of such grammars from a training corpus of syntactic analyses, and apply these to estimate a stochastic version of Lexical-Functional Grammar.
Original languageEnglish
Title of host publicationProceedings of the 37th Annual Conference of the Association for Computational Linguistics
Place of PublicationSan Francisco
PublisherAssociation for Computational Linguistics (ACL)
Number of pages7
ISBN (Print)1-55860-609-2
Publication statusPublished - 1999
Externally publishedYes
EventAnnual Meeting of the Association for Computational Linguistics (37th : 1999) - University of Maryland, College Park, United States
Duration: 20 Jun 199926 Jun 1999


ConferenceAnnual Meeting of the Association for Computational Linguistics (37th : 1999)
CountryUnited States
CityCollege Park

Bibliographical note

Copyright the Publisher 1999. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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