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14

ACL
2009

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Bayesian Learning of a Tree Substitution Grammar

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Bayesian Learning of a Tree Substitution Grammar

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Tree substitution grammars (TSGs) offer many advantages over context-free grammars (CFGs), but are hard to learn. Past approaches have resorted to heuristics. In this paper, we learn a TSG using Gibbs sampling with a nonparametric prior to control subtree size. The learned grammars perform significantly better than heuristically extracted ones on parsing accuracy.

Matt Post, Daniel Gildea

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ACL 2009 | Computational Linguistics | Context-free Grammars | Grammars | Tree Substitution |

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Added	16 Feb 2011
Updated	16 Feb 2011
Type	Journal
Year	2009
Where	ACL
Authors	Matt Post, Daniel Gildea

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