Reversible NLP By Deriving The Grammars From The Knowledge Base
نویسنده
چکیده
We present a new architecture for reversible NLP. Separate parsing and generation grammars are constructed from the underlying application's semantic model and knowledge base. By having two grammars we are free to use process-specific representations and control techniques, thereby permitting highly efficient processing. The single semantic source ensures the parsimony of development and matched competence that make reversible NLP attractive.
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تاریخ انتشار 1991