Abstract
As far as lexical ambiguity is concerned, Semantic Domains may be considered from two points of view: (i) as a linguistic notion, that can be modeled independently, and then applied uniformly to describe sense distinctions for any word in the lexicon; and (ii) as a useful coarse-grained level of sense distinction, to be profitably used in a wide range of applications that do not require the finer grained sense distinctions typically reported in dictionaries.
A major portion of the information required for sense disambiguation corresponds to domain relations among words. Many of the features that contribute to disambiguation identify the domains that characterize a particular sense or subset of senses. For example, economics terms provide characteristic features for the financial senses of words like bank and interest, while legal terms characterize the judicial sense of sentence and court.
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These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2009 Springer-Verlag Berlin Heidelberg
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Gliozzo, A., Strapparava, C. (2009). Semantic Domains in Word Sense Disambiguation. In: Semantic Domains in Computational Linguistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68158-8_5
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DOI: https://doi.org/10.1007/978-3-540-68158-8_5
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