DFKI-LT - Grammar Approximation as a Speed-Up Technique for Unification-Based Parsing
Grammar Approximation as a Speed-Up Technique for Unification-Based Parsing
1 Invited talks on Learning of Automata and Grammars at the Workshop on Theoretical Aspects of Grammar Induction (TAGI),
In this talk, I will present three techniques for obtaining fast grammars from a given unification-based grammar (UBG). The research is motivated by the idea that we can exploit (large-scale), hand-written UBGs not only for the purpose of describing natural language and obtaining a syntactic structure (and perhaps a semantic form), but also to address several other very practical topics. Firstly, to speed up deep parsing by having a cheap recognition pre-filter. Secondly, to obtain an indirect stochastic parsing model for the UBG. Thirdly, to generate domain-specific subgrammars for real applications. And finally, to compile context-free language models for a speech recognizer.
Files: BibTeX, krieger.ps