Probabilistic Normalisation and Unpacking of Packed Parse Forests for Unification-based Grammars
John M. Carroll, Ted Briscoe · 1992
The research described below forms part of a wider programme to develop a practical parser for naturally-occurring natural language input which is capable of returning the n-best syntacticallydeterminate analyses, containing that which is semantically and pragmatically most appropriate (preferably as the highest ranked) from the exponential (in sentence length) syntactically legitimate possibilities (Church & Patil 1983), which can frequently run into the thousands with realistic sentences and grammars. We have opted to develop a domain-independent solution to this problem based on integrating statistical Markov modelling techniques, which offer the potential for rapid tuning to different sublanguages / corpora on the basis of supervised training, with linguistically-adequate grammatical (language) models, capable of returning analyses detailed enough to support semantic interpretation.