Paper: Discriminative Training Of A Neural Network Statistical Parser

ACL ID P04-1013
Title Discriminative Training Of A Neural Network Statistical Parser
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2004
Authors

Discriminative methods have shown signi cant improvements over traditional generative meth- ods in many machine learning applications, but there has been di culty in extending them to natural language parsing. One problem is that much of the work on discriminative methods con ates changes to the learning method with changes to the parameterization of the problem. We show how a parser can be trained with a dis- criminative learning method while still param- eterizing the problem according to a generative probability model. We present three methods for training a neural network to estimate the probabilities for a statistical parser, one gen- erative, one discriminative, and one where the probability model is generative but the training criteria is discriminative. The latter model out- perfor...