ITRI-02-16 PCFG Learning by Nonterminal Partition Search

ITRI-02-14 Learning Grammars for Noun Phrase Extraction by Partition Search

This paper describes an application of Grammar Learning by Partition Search to noun phrase extraction, an essential task in information extraction and many other NLP applications. Grammar Learning by Partition Search is a general method for automatically constructing grammars for a range of parsing tasks; it constructs an optimised probabilistic context-free grammar by searching a space of nont...

PCFG Learning by Nonterminal Partition Search

pcfg Learning by Partition Search is a general grammatical inference method for constructing, adapting and optimising pcfgs. Given a training corpus of examples from a language, a canonical grammar for the training corpus, and a parsing task, Partition Search pcfg Learning constructs a grammar that maximises performance on the parsing task and minimises grammar size. This paper describes Partit...

ITRI-02-09 Grammar Learning by Partition Search

This paper describes Grammar Learning by Partition Search, a general method for automatically constructing grammars for a range of parsing tasks. Given a base grammar, a training corpus, and a parsing task, Partition Search constructs an optimised probabilistic context-free grammar by searching a space of nonterminal set partitions, looking for a partition that maximises parsing performance and...

ITRI-02-15 Learning Grammars for Different Parsing Tasks by Partition Search

Optimizing Spectral Learning for Parsing

We describe a search algorithm for optimizing the number of latent states when estimating latent-variable PCFGs with spectral methods. Our results show that contrary to the common belief that the number of latent states for each nonterminal in an L-PCFG can be decided in isolation with spectral methods, parsing results significantly improve if the number of latent states for each nonterminal is...