In knowledge-based machine translation, syntactic structures and conceptual structures are combined to produce an intermediate semantic representation of the source language text. In order to combine these two structures, we need mapping rules to unite them. The main contribution of this thesis is to give a full-fledged model of interpretive mapping for knowledge-based machine translation, and to offer guidance that makes it easier to develop new translation domains.
