Abstract and Keywords
WordNet, a large lexical database of English, was conceived as a model of human semantic organization. Evidence from timing experiments, association norms, and distributional properties of words supported a semantic network model in which words are interlinked via a small number of lexical and conceptual relations. Its large coverage and unique structure, which allows automatic systems to detect and quantify semantic relatedness among words, soon made WordNet an invaluable tool for natural language processing tasks. Information retrieval, document summarization, and machine translation crucially require word sense discrimination and disambiguation. Wordnets have been built in dozens of languages and for specific technical sublanguages, and the number of applications in research, language technology and pedagogy has grown. Although WordNet’s central focus has shifted from its psycholinguistic origins, its design, based on theories about the structure of the human mental lexicon, is validated as a sound approach to representing the meanings of words.
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