This paper describes briefly the overall architecture of a machine translation system between French and Arabic in the sub-world of cooking recipes. It continues to describe in more detail the design of the generation component and how this design allows a variety of outputs all expressing the same conceptual meaning. This system is of the family of knowledge-based interlingua translation systems as it emphasises the importance of the meaning of the text being processed and articulates all its available knowledge-bases in order to achieve one major goal: flexible meaningful wording. We agree with S. Nirenburg that "the ability and the right to subdivide sentences or to combine them together in the Target language are powerful tools in the hands of human translators." These are some tools that we want our MT systems to be able to use. The way the system is modularised allowed us to experiment with the generation of: sentence to sentence translations, text to text translations, more concise as opposed to more generalised wording, and varying word orders. The modules are declarative and loosely coupled. This strategy allowed us to experiment with regenerating back the French text. As a matter of fact, the generation component of this MT system is multilingual and capable of accommodating Arabic and French; two languages belonging to two different origins, namely Indo-European and Semitic. This system, being functional in the domain of cooking recipes, allowed us to concentrate on the lexical semantics of its vocabulary and on the modularisation of its linguistic knowledge, whether it is morphological, syntactic or stylistic, as opposed to its pragmatic knowledge. Now that we have tested the design on different languages, we are studying its feasibility in new domains where texts are mainly constituted of verbal phrases, such as in gardening and Chemistry laboratory manuals.