Stochastic HPSG Parse Selection using the Redwoods Corpus
- Kristina Toutanova ,
- Christopher D. Manning ,
- Stephan Oepen ,
- Dan Flickinger
Journal of Logic and Computation |
This article details our experiments on HPSG parse disambiguation, based on the Redwoods treebank. Using existing and novel stochastic models, we evaluate the usefulness of different information sources for disambiguation – lexical, syntactic, and semantic. We perform careful comparisons of generative and discrimintative models using equivalent features and show the consistent advantage of discriminatively trained models. Our best system performs at 76% sentence exact march accuracy.