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Lexicalized Stochastic Modeling of Constraint-Based Grammars using Log-Linear Measures and EM Training

Stefan Riezler·Detlef Prescher·Jonas Kuhn·Mark Johnson
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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.

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Stefan Riezler, Detlef Prescher, Jonas Kuhn, Mark Johnson. 2000-08-30. Lexicalized Stochastic Modeling of Constraint-Based Grammars using Log-Linear Measures and EM Training. https://arxiv.org/abs/cs/0008034

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