Abstract
We propose a strategy to support Word Sense Disambiguation (WSD) which is designed specifically for multilingual applications, such as Machine Translation. Co-occurrence information extracted from the translation context, i.e., the set of words which have already been translated, is used to define the order in which disambiguation rules produced by a machine learning algorithm are applied. Experiments on the English-Portuguese translation of seven verbs yielded a significant improvement on the accuracy of a rule-based model: from 0.75 to 0.79.
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Specia, L., das Graças Volpe Nunes, M. (2006). Exploiting the Translation Context for Multilingual WSD. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2006. Lecture Notes in Computer Science(), vol 4188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11846406_34
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DOI: https://doi.org/10.1007/11846406_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39090-9
Online ISBN: 978-3-540-39091-6
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