The model used by the CCG parser of Hockenmaier and Steedman (2002b) would fail to capture the correct bilexical dependencies in a language with freer word order, such as Dutch. T...
We present a generative model for the unsupervised learning of dependency structures. We also describe the multiplicative combination of this dependency model with a model of line...
We describe a generative probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorporates...
Ezra Black, Frederick Jelinek, John D. Lafferty, D...
In this paper we present methods for improving the disambiguation of noun phrase (NP) coordination within the framework of a lexicalised history-based parsing model. As well as re...
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...