W08-0130 to specifying domain-specific , grammar-based generation by example . The method reduces
P06-1130 of 0.7012 . Using hand-crafted grammar-based generation systems ( Langkilde-Geary , 2002
W15-4718 simple , effective approach to grammar-based generation using Categorial Grammar as underlying
W12-1641 generation . If a dialogue system uses grammar-based generation at all , it produces complete
P11-1101 Conclusion We have presented a grammar-based generation architecture which implements
W08-1111 expertise needed to develop a grammar-based generation component for an existing system
W08-1111 expertise needed to integrate a grammar-based generation component into an existing application
N06-1032 n-gram and distortion models after grammar-based generation . The goal of this ordering model
N06-1032 investigate the contribution of grammar-based generation to dependencybased SMT2 . In
W12-2017 approach , these are obtained by a grammar-based generation process . As we shall see below
W08-1111 feasibly be deployed . In principle , grammar-based generation offers significant advantages
W02-0303 in other ways as well , e.g. by grammar-based generation of alternate forms . The heuristics
W08-1111 present a technique that opens up grammar-based generation to a wider range of practical
N06-1032 employed in our framework after grammar-based generation , thus giving preference to grammaticality
N06-1032 target text , a utilization of grammar-based generation on the output of translation
E14-1020 templates and the other using our grammar-based generation algorithm . The evaluation was
W10-0304 generally assumed that RACTER employed grammar-based generation . The poems in Chamberlain 's
P92-1000 James Rogers K Vijay-Shanker Two Grammar-Based Generation Algorithms A Case Study Miroslav
P00-1041 al. , 1999 ) , and sophisticated grammar-based generation ( Radev and McKeown , 1998 )
P10-1034 semantics framework , and fully grammar-based generation for English using HPSG . A hybrid
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