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              <p>For our second participation to the Question Answering task of CLEF, we kept last year system named MUSCLEF, which uses two different translation strategies implemented in two modules. The multilingual module MUSQAT analyzes the French questions, translates “interesting parts”, and then uses these translated terms to search the reference collection. The second strategy consists in translating the question into English and applying QALC our existing English module. Our purpose in this paper is to analyze term translations and propose a mechanism for selecting correct ones. The manual evaluation of bi-terms translations leads us to the conclusion that the bi—term translations found in the corpus can conﬁrm the mono-term translations.</p>
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