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.