Lexicalized Stochastic Modeling of Constraint-Based Grammars using Log-Linear Measures and EM Training (2000)
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| Venue: | IN PROCEEDINGS OF THE 38TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL'00), HONG KONG |
| Citations: | 58 - 9 self |
BibTeX
@INPROCEEDINGS{Riezler00lexicalizedstochastic,
author = {Stefan Riezler and Detlef Prescher and Jonas Kuhn and Mark Johnson},
title = {Lexicalized Stochastic Modeling of Constraint-Based Grammars using Log-Linear Measures and EM Training},
booktitle = {IN PROCEEDINGS OF THE 38TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL'00), HONG KONG},
year = {2000},
pages = {480--487},
publisher = {}
}
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Abstract
We present a new approach to stochastic modeling of constraint-based grammars that is based on log-linear models and uses EM for estimation from unannotated data. The techniques are applied to an LFG grammar for German. Evaluation on an exact match task yields 86% precision for an ambiguity rate of 5.4, and 90% precision on a subcat frame match for an ambiguity rate of 25. Experimental comparison to training from a parsebank shows a 10% gain from EM training. Also, a new class-based grammar lexicalization is presented, showing a 10% gain over unlexicalized models.
