Current phrase-based SMT systems perform poorly when using small training sets. This is a consequence of unreliable translation estimates and low coverage over source and target p...
Approaches to text processing that rely on parsing the text with a context-free grammar tend to be slow and error-prone because of the massive ambiguity of long sentences. In cont...
Douglas E. Appelt, Jerry R. Hobbs, John Bear, Davi...
Abstract. This paper is centered on the problem of merging (possibly conflicting) information coming from different sources. Though this problem has attracted much attention in pro...
This paper demonstrates how machine learning methods can be applied to deal with a realworld decipherment problem where very little background knowledge is available. The goal is ...
The Manually Annotated Sub-Corpus (MASC) project provides data and annotations to serve as the base for a communitywide annotation effort of a subset of the American National Corp...
Nancy Ide, Collin F. Baker, Christiane Fellbaum, R...