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EMNLP
2009

Self-Training PCFG Grammars with Latent Annotations Across Languages

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Self-Training PCFG Grammars with Latent Annotations Across Languages
We investigate the effectiveness of selftraining PCFG grammars with latent annotations (PCFG-LA) for parsing languages with different amounts of labeled training data. Compared to Charniak's lexicalized parser, the PCFG-LA parser was more effectively adapted to a language for which parsing has been less well developed (i.e., Chinese) and benefited more from selftraining. We show for the first time that self-training is able to significantly improve the performance of the PCFG-LA parser, a single generative parser, on both small and large amounts of labeled training data. Our approach achieves stateof-the-art parsing accuracies for a single
Zhongqiang Huang, Mary P. Harper
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where EMNLP
Authors Zhongqiang Huang, Mary P. Harper
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