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...
In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
Effective access to knowledge within large declarative memory stores is one challenge in the development and understanding of long-living, generally intelligent agents. We focus o...
We show for the first time that incorporating the predictions of a word sense disambiguation system within a typical phrase-based statistical machine translation (SMT) model cons...
Abstract. The Robust-WSD at CLEF 2009 aims at exploring the contribution of Word Sense Disambiguation to monolingual and multilingual Information Retrieval. The organizers of the t...
Eneko Agirre, Giorgio Maria Di Nunzio, Thomas Mand...