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Learning and Inference for Hierarchically Split PCFGs





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Published on Feb 29, 2008

Google Tech Talks
February, 28 2008


Treebank parsing can be seen as the search for an optimally refined grammar consistent with a coarse training treebank. We describe a method in which a minimal grammar is hierarchically refined using EM to give accurate, compact grammars. The resulting grammars are extremely compact compared to other high-performance parsers, yet the parser gives the best published accuracies on several languages, as well as the best generative parsing numbers in English. In addition, we give an associated coarse-to-fine inference scheme which vastly improves inference time with no loss in test set accuracy.


Speaker: Slav Petrov
Slav Petrov is a Ph.D. Candidate at University of California Berkeley Dept of Computer Science, where he is also a research assistant working with Dan Klein and Jitendra Malik on inducing latent structure for perception problems in vision and language.


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