Large-scale knowledge-based machine translation requires significant amounts of lexical knowledge in order to map syntactic structures to conceptual structures. This paper presents a framework in which lexical knowledge is separated into different levels of representation, which are arranged in a hierarchical model based on principles of knowledge representation and lexical semantics. The proposed methodology is language-independent, and has been used to organize lexical knowledge for both English and Japanese.