Learning Stochastic Lexicalized Tree Grammars from Hpsg

We 1 present a method for automatically extracting a Stochastic Lexicalized Tree Grammar (SLTG) from an HPSG source grammar and a given corpus. Processing of a SLTG is performed by a specialized fast parser. The approach has been tested on a large English grammar and has been shown to achieve a speed-up by a factor of better than 10 compared to parsing with a highly tuned HPSG parser. Our approach is simple and transparent, and comes with no magic tuning strategies. The extracted grammars are declaratively represented and have a high degree of practical applicability.

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