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General Word Sense Disambiguation Method Based on a Full Sentential Context
1998
Journal of Natural Language Processing
This paper presents a new general supervised word sense disambiguation method based on a relatively small syntactically parsed and semantically tagged training corpus.The method exploits a full sentential context and all the explicit semantic relations in a sentence to identify the senses of all of that sentence's content words. It solves the sparse data problem of a small training corpus by substituting the words by their semantic classes.In spite of a very small training corpus,we report an
doi:10.5715/jnlp.5.2_47
fatcat:2niac5taprettapaslweaw57om