I will review recent advances in grammar-based sentence realization
from logical-form meaning representations. The LOGON MT prototype
aims at the fully-automated, high-quality translation of Norwegian
instructional texts (on backcountry activities) into English. The
LOGON generator operates off underspecified meaning representations
derived from `deep' grammatical analysis (in the LFG framework) and
subsequent semantic transfer. The generator builds on the LinGO
English Resource Grammar (in the HPSG framework) and combines a
highly optimized chart-based algorithm with a rich, probabilistic
model to rank alternate realizations. Integration of the stochastic
model into the enumeration of outputs from the packed chart allows
the generator to selectively unpack n-best lists of realizations with
minimal search. Besides empirical results for the realization task
when evaluated in isolation, I will present a summary of quantitative
measures on the current development status (and promise) of the LOGON
MT pipeline as a whole.
Weblink: http://www.emmtee.net
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