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Medical language processing depends on large-coverage, finegrained specialized lexicons. The vast majority of existing electronic lexicons concern the English language; for other languages such as French, resources are scarce. In contrast, large medical thesauri exist in numerous languages, including French. Our goal was to study what kind of linguistic information could be extracted from thesauri into a lexicon, in which places human intervention is necessary, and what kind of issues arise in this process. We designed in this purpose a method to build a semantic lexicon from a subset of the SNOMED axes in their French translation.
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