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Interfacing Constraint-Based Grammars and Generation Algorithms

Stephan Busemann
In: Workshop "Analysis for Generation". 1st International Conference on Natural Language Generation, June 12-16. International Conference on Natural Language Generation, 2000.


Constraint-based grammars can, in principle, serve as the major linguistic knowledge source for both parsing and generation. Surface generation starts from input semantics representations that may vary across grammars. For many declarative grammars, the concept of derivation implicitly built in is that of parsing. They may thus not be interpretable by a generation algorithm. We show that linguistically plausible semantic analyses can cause severe problems for semantic-head-driven approaches for generation (SHDG). We use SeReal, a variant of SHDG and the DISCO grammar of German as our source of examples. We propose a new, general approach that explicitly accounts for the interface between the grammar and the generation algorithm by adding a control-oriented layer to the linguistic knowledge base that reorganizes the semantics in a way suitable for generation.