This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...
This paper explores the contribution of a broad range of syntactic features to WSD: grammatical relations coded as the presence of adjuncts/arguments in isolation or as subcategor...
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
As part of a forthcoming planetarium show about the human brain, we are producing realistic models of the central nervous system at a variety of scales, from whole brain images to...
In this paper we introduce a programming language for Web document processing called WebL. WebL is a high level, object-oriented scripting language that incorporates two novel fea...