PCFG Learning by Nonterminal Partition Search
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
New models for improving supertag disambiguation
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
A hybrid language model based on a combination of N-grams and stochastic context-free grammars
ACM Transactions on Asian Language Information Processing (TALIP)
Learning grammars for different parsing tasks by partition search
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Automated extraction of tags from the penn treebank
New developments in parsing technology
International Journal of Bioinformatics Research and Applications
A robust and hybrid deep-linguistic theory applied to large-scale parsing
ROMAND '04 Proceedings of the 3rd Workshop on RObust Methods in Analysis of Natural Language Data
Towards a framework for evaluating syntactic parsers
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Chinese treebanks and grammar extraction
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Performance of a SCFG-based language model with training data sets of increasing size
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Inducing head-driven PCFGs with latent heads: refining a tree-bank grammar for parsing
ECML'05 Proceedings of the 16th European conference on Machine Learning
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By a ``tree-bank grammar'''' we mean a context-free grammar created by reading the production rules directly from hand-parsed sentences in a tree bank. Common wisdom has it that such grammars do not perform well, though we know of no published data on the issue. The primary purpose of this paper is to show that the common wisdom is wrong. In particular we present results on a tree-bank grammar based on the Penn Wall Street Journal tree bank. To the best of our knowledge, this grammar out-performs all other non-word-based statistical parsers/grammars on this corpus. That is, it out-performs parsers that consider the input as a string of tags and ignore the actual words of the corpus.