We evaluate probabilistic models of verb argument structure trained on a corpus of verbs and their syntactic arguments. Models designed to represent patterns of verb alternation b...
Abstract. Recent research has enabled important progress in developing agents aimed at real-world linguistic interaction with humans. Hence, within the general shift of research fo...
In this paper, we propose a new Bayesian model for fully unsupervised word segmentation and an efficient blocked Gibbs sampler combined with dynamic programming for inference. Our...
In this paper, with a belief that a language model that embraces a larger context provides better prediction ability, we present two extensions to standard n-gram language models ...
This paper studies the problem of sentencelevel semantic coherence by answering SATstyle sentence completion questions. These questions test the ability of algorithms to distingui...
Geoffrey Zweig, John C. Platt, Christopher Meek, C...