A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Inside-outside reestimation from partially bracketed corpora
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Inducing history representations for broad coverage statistical parsing
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Probabilistic CFG with latent annotations
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Learning accurate, compact, and interpretable tree annotation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Discriminative learning and spanning tree algorithms for dependency parsing
Discriminative learning and spanning tree algorithms for dependency parsing
Parsing with soft and hard constraints on dependency length
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Head-driven PCFGs with latent-head statistics
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Incremental Sigmoid Belief Networks for Grammar Learning
The Journal of Machine Learning Research
Bayesian network automata for modelling unbounded structures
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Spectral learning for non-deterministic dependency parsing
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Spectral dependency parsing with latent variables
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Multilingual joint parsing of syntactic and semantic dependencies with a latent variable model
Computational Linguistics
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This paper investigates transforms of split dependency grammars into unlexicalised context-free grammars annotated with hidden symbols. Our best unlexicalised grammar achieves an accuracy of 88% on the Penn Treebank data set, that represents a 50% reduction in error over previously published results on unlexicalised dependency parsing.