Abstract
Creating and maintaining terminologies by human experts is known to be a resource-expensive task. We here report on efforts to computationally support this process by treating term acquisition as a machine translation-guided classification problem capitalizing on parallel multilingual corpora. Experiments are described for French, German, Spanish and Dutch parts of a multilingual biomedical terminology, for which we generated 18k, 23k, 19k and 12k new terms and synonyms, respectively; about one half relate to concepts that have not been lexically labeled before. Based on expert assessment of a sample of the novel German segment about 80% of these newly acquired terms were judged as linguistically correct and bio-medically reasonable additions to the terminology.
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