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- W1497485341 abstract "In this paper, an approach to semantic disambiguation based on machine learning and semantic classes for Spanish is presented. A critical issue in a corpus-based approach for Word Sense Disambiguation (WSD) is the lack of wide-coverage resources to automatically learn the linguistic information. In particular, all-words sense annotated corpora such as SemCor do not have enough examples for many senses when used in a machine learning method. Using semantic classes instead of senses allows to collect a larger number of examples for each class while polysemy is reduced, improving the accuracy of semantic disambiguation. Cast3LB, a SemCor-like corpus, manually annotated with Spanish WordNet 1.5 senses, has been used in this paper to perform semantic disambiguation based on several sets of classes: lexicographer files of WordNet, WordNet Domains, and SUMO ontology." @default.
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- W1497485341 date "2006-01-01" @default.
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- W1497485341 title "Spanish All-Words Semantic Class Disambiguation Using Cast3LB Corpus" @default.
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- W1497485341 doi "https://doi.org/10.1007/11925231_84" @default.
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