Word sense disambiguation using pairwise alignment

Yamashita, Koichi; Yoshida, Keiichi; Itoh, Yukihiro

doi:10.3115/1075178.1075205

Cited by 1 publication

(2 citation statements)

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“…That remains the case for most systems that participated in Senseval-2 (Preiss and Yarowsky (2001)). Some recent work (Stetina et al (1998); Agirre et al (2002);Yamashita et al (2003)) attempts to change this situation and presents a directed effort to investigate the impact of using syntactic features for WSD learning algorithms. Agirre et al (2002) and Yamashita et al (2003) report resulting improvement in precision.…”

Section: Word Sense Disambiguation: Currentmentioning

confidence: 99%

“…Some recent work (Stetina et al (1998); Agirre et al (2002);Yamashita et al (2003)) attempts to change this situation and presents a directed effort to investigate the impact of using syntactic features for WSD learning algorithms. Agirre et al (2002) and Yamashita et al (2003) report resulting improvement in precision. Stevenson and Wilks (2001) propose a somewhat related technique to handle WSD, based on integrating LDOCE classes with simulated annealing.…”

Section: Word Sense Disambiguation: Currentmentioning

confidence: 99%

See 1 more Smart Citation

Automated induction of sense in context

Pustejovsky

Hanks

Rumshisky

2004

Proceedings of the 20th International Conference on Computational Linguistics - COLING '04

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In this paper, we introduce a model for sense assignment which relies on assigning senses to the contexts within which words appear, rather than to the words themselves. We argue that word senses as such are not directly encoded in the lexicon of the language. Rather, each word is associated with one or more stereotypical syntagmatic patterns, which we call selection contexts. Each selection context is associated with a meaning, which can be expressed in any of various formal or computational manifestations. We present a formalism for encoding contexts that help to determine the semantic contribution of a word in an utterance. Further, we develop a methodology through which such stereotypical contexts for words and phrases can be identified from very large corpora, and subsequently structured in a selection context dictionary, encoding both stereotypical syntactic and semantic information. We present some preliminary results.

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Section: Word Sense Disambiguation: Currentmentioning

confidence: 99%