Mapping Roget’s Thesaurus and WordNet to French

Abstract

Roget’s Thesaurus and WordNet are very widely used lexical reference works. We describe an automatic mapping procedure that effectively produces French translations of the terms in these two resources. Our approach to the challenging task of disambiguation is based on structural statistics as well as measures of semantic relatedness that are utilized to learn a classification model for associations between entries in the thesaurus and French terms taken from bilingual dictionaries. By building and applying such models, we have produced French versions of Roget’s Thesaurus and WordNet with a considerable level of accuracy, which can be used for a variety of different purposes, by humans as well as in computational applications.

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