Paper: Better Binarization for the CKY Parsing

ACL ID D08-1018
Title Better Binarization for the CKY Parsing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

We present a study on how grammar binariza- tion empirically affects the efficiency of the CKY parsing. We argue that binarizations af- fect parsing efficiency primarily by affecting the number of incomplete constituents gener- ated, and the effectiveness of binarization also depends on the nature of the input. We pro- pose a novel binarization method utilizing rich information learnt from training corpus. Ex- perimental results not only show that differ- ent binarizations have great impacts on pars- ing efficiency, but also confirm that our learnt binarization outperforms other existing meth- ods. Furthermore we show that it is feasible to combine existing parsing speed-up techniques with our binarization to achieve even better performance.