The proposed machine translation (MT) approach uses WordNet (Fellbaum, 1998) as a base for concepts. It identifies the concepts and dependency relations using context-free grammars (CFGs) enriched with features, role markers and dependency markers. Multiple interpretation hypotheses are generated and then are scored using a knowledge base for the dependency relations. The hypothesis with the best score is used for generating the translation. The approach has already been implemented in an MT system for seven languages, namely Bulgarian, English, French, Spanish, Italian, German, and Turkish, and also for Chinese on experimental level.