This paper reports the work of NTU on bilingual-retrieval task at CLEF 2001. We proposed five models. Model 1 used co-occurrence information to disambiguate translation equivalents; Model 2 augmented restriction terms to the original queries; Model 3 used C-E WordNet to translate queries; Model 4 combined Model 3 with Model 2; Model 5 merged the queries constructed by Model 2 and 3. The best one is Model 5. The average precision of Model 5 is 0.1135, which is 53.06% of monolingual information retrieval.