This article presents a semi-automatic ontology construction method using various resources, and an ontology-based word sense disambiguation method in Machine Translation. To acquire a reasonably practical ontology in limited time and with less manpower, the Kadokawa thesaurus is extended by inserting additional semantic relations into its hierarchy, which are classified as case relations and other semantic relations. The former can be obtained by converting valency information and case frames from previously built computational dictionaries used in Machine Translation. The latter can be acquired from concept co-occurrence information, which is extracted automatically from large corpora. The ontology stores rich semantic constraints among 1110 concepts, and enables a natural language processing system to resolve semantic ambiguities by making inferences with the concept network of the ontology. In practical Machine Translation systems, our word sense disambiguation method achieved a 6.0 per cent and 7.9 per cent improvement over methods that do not use an ontology for each Japanese and Korean translation.