  We present an approach to syntax-based machine translation that combines
unification-style interpretation with statistical processing. This approach
enables us to translate any Japanese newspaper article into English, with
quality far better than a word-for-word translation. Novel ideas include the
use of feature structures to encode word lattices and the use of unification to
compose and manipulate lattices. Unification also allows us to specify abstract
features that delay target-language synthesis until enough source-language
information is assembled. Our statistical component enables us to search
efficiently among competing translations and locate those with high English
fluency.
