Searching Parallel Corpora for Contextually Equivalent Terms

In this paper, we show how a large bilingual English-French parallel corpus can be brought to bear in terminology search. First, we demonstrate that the coverage of available corpora has become substantially more extensive than that of mainstream term banks. One potential drawback in searching large unstructured corpora is that large numbers of search results may need to be examined before finding a relevant match. We argue that this problem can be alleviated by contextualizing the search process: instead of looking up isolated terms one searches for terms appearing in a context that is similar to that of the term to be translated. We present an experiment on contextbased re-ranking and report highly positive results. We conclude that translators will increasingly rely on very large scale corpora for searching term equivalents.