With the worldwide growth of the Internet, research on Cross-Language Information Retrieval (CLIR) is being paid much attention. Existing CLIR approaches based on query translation require parallel corpora or comparable corpora for the disambiguation of translated query terms. However, those natural language resources are not readily available. In this paper, we propose a disambiguation method for dictionary-based query translation that is independent of the availability of such scarce language resources, while achieving adequate retrieval effectiveness by utilizing Web documents as a corpus and using co-occurrence information between terms within that corpus. In the experiments, our method achieved 97% of manual translation case in terms of the average precision.