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• W614894673 abstract "This thesis investigates the use of the translation-based Mirrors method (Dyvik, 2005, inter alia) for Word Sense Disambiguation (WSD) for Norwegian. Word Sense Disambiguation is the process of determining the relevant sense of an ambiguous word in context automatically. Automated WSD is relevant for Natural Language Processing systems such as machine translation (MT), information retrieval, information extraction and content analysis. The most successful WSD approaches to date are so-called supervisedmachine learning (ML) techniques, in which the system ‘learns’ the contextual characteristics of each sense from a training corpus that contains concrete examples of contexts in which a word sense typically occurs. This approach suffers from a knowledge acquisition problem since word senses are not overtly available in corpus text. First, we therefore need a sense inventory which is computationally tractable. Subjectively defined sense distinctions have been the norm in WSD research (especially the Princeton WordNet, Fellbaum, 1998). But WSD studies increasingly show that the WordNet senses are too fine-grained for efficient WSD, which has made WordNet less attractive for machine-learned WSD. Ide and Wilks (2006) recommend instead to approximate word senses by way of cross-lingual sense definitions. Second, we need a method for sense-tagging context examples with the relevant sense given the context. Preparing such sense-tagged training corpora manually is costly and time-consuming, in particular because statistical methods require large amounts of training examples, and automated methods are therefore desirable. This thesis introduces an experimental lexical knowledge source which derives word senses and relations between word senses on the basis of translational correspondences in a parallel corpus, resulting in a structured semantic network (Dyvik, 2009). The Mirrors method is applicable for any language pair for which a parallel corpus and word alignment is available. The appeal of the Mirrors method and its translational basis for lexical semantics is that it offers an objective and consistent—and hence, testable—criterion, as opposed to the traditional" @default.
• W614894673 created "2016-06-24" @default.
• W614894673 creator A5057836864 @default.
• W614894673 date "2011-12-09" @default.
• W614894673 modified "2023-09-27" @default.
• W614894673 title "Translation-based Word Sense Disambiguation" @default.
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