This paper reports on an experiment in assembling a domain-specific machine translation prototype system from off-the-shelf
components. The design goals of this experiment were to reuse existing components, to use machine-learning techniques for
parser specialization and for transfer lexicon extraction, and to use an expressive, lexicalized formalism for the transfer
component.