Dependency-based representations of natural language syntax require a fine balance between structural flexibility and computational complexity. In previous work, several constra...
We present a global discriminative statistical word order model for machine translation. Our model combines syntactic movement and surface movement information, and is discriminat...
This paper proposes a supervised learning method for detecting a semantic relation between a given pair of named entities, which may be located in different sentences. The method ...
We present a new approach to relation extraction that requires only a handful of training examples. Given a few pairs of named entities known to exhibit or not exhibit a particula...
We introduce a framework for syntactic parsing with latent variables based on a form of dynamic Sigmoid Belief Networks called Incremental Sigmoid Belief Networks. We demonstrate ...
Live closed-captions for deaf and hard of hearing audiences are currently produced by stenographers, or by voice writers using speech recognition. Both techniques can produce capt...
Patrick Cardinal, Gilles Boulianne, Michel Comeau,...
This paper examines whether a learningbased coreference resolver can be improved using semantic class knowledge that is automatically acquired from a version of the Penn Treebank ...
The aim of this paper is to present a simple yet efficient implementation of a tool for simultaneous rule-based morphosyntactic tagging and partial parsing formalism. The parser ...
Speech recognition in many morphologically rich languages suffers from a very high out-of-vocabulary (OOV) ratio. Earlier work has shown that vocabulary decomposition methods can ...