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- W1547086561 abstract "In recent years, there has been a flurry of research into empirical, corpus-based learning approaches to natural language processing (NLP). Most empirical NLP work to date has focused on relatively low-level language processing such as part-of-speech tagging, text segmentation, and syntactic parsing. The success of these approaches has stimulated research in using empirical learning techniques in other facets of NLP, including semantic analysis -- uncovering the meaning of an utterance. This article is an introduction to some of the emerging research in the application of corpus-based learning techniques to problems in semantic interpretation. In particular, we focus on two important problems in semantic interpretation, namely, word-sense disambiguation and semantic parsing." @default.
- W1547086561 created "2016-06-24" @default.
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- W1547086561 date "1997-12-15" @default.
- W1547086561 modified "2023-09-24" @default.
- W1547086561 title "Corpus-Based Approaches to Semantic Interpretation in NLP" @default.
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- W1547086561 doi "https://doi.org/10.1609/aimag.v18i4.1321" @default.
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