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» Unsupervised Parse Selection for HPSG
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EMNLP
2006
13 years 6 months ago
Extremely Lexicalized Models for Accurate and Fast HPSG Parsing
This paper describes an extremely lexicalized probabilistic model for fast and accurate HPSG parsing. In this model, the probabilities of parse trees are defined with only the pro...
Takashi Ninomiya, Takuya Matsuzaki, Yoshimasa Tsur...
EMNLP
2004
13 years 6 months ago
Active Learning and the Total Cost of Annotation
Active learning (AL) promises to reduce the cost of annotating labeled datasets for trainable human language technologies. Contrary to expectations, when creating labeled training...
Jason Baldridge, Miles Osborne
ACL
2011
12 years 9 months ago
Effective Measures of Domain Similarity for Parsing
It is well known that parsing accuracy suffers when a model is applied to out-of-domain data. It is also known that the most beneficial data to parse a given domain is data that ...
Barbara Plank, Gertjan van Noord
EMNLP
2006
13 years 6 months ago
Better Informed Training of Latent Syntactic Features
We study unsupervised methods for learning refinements of the nonterminals in a treebank. Following Matsuzaki et al. (2005) and Prescher (2005), we may for example split NP withou...
Markus Dreyer, Jason Eisner