Procedure for quantitatively comparing the syntactic coverage of English grammars
HLT '91 Proceedings of the workshop on Speech and Natural Language
A Maximum-Entropy-Inspired Parser
A Maximum-Entropy-Inspired Parser
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Three new probabilistic models for dependency parsing: an exploration
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Computational complexity of probabilistic disambiguation by means of tree-grammars
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Decision tree parsing using a hidden derivation model
HLT '94 Proceedings of the workshop on Human Language Technology
Statistical parsing with a context-free grammar and word statistics
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Natural Language Engineering
An efficient implementation of a new DOP model
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
What is the minimal set of fragments that achieves maximal parse accuracy?
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Fast LR parsing using rich (Tree Adjoining) Grammars
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Robust data oriented spoken language understanding
New developments in parsing technology
Alternative approaches for generating bodies of grammar rules
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Shallow semantic labeling using two-phase feature-enhanced string matching
Expert Systems with Applications: An International Journal
Simple, accurate parsing with an all-fragments grammar
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
The surprising variance in shortest-derivation parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Shallow case role annotation using two-stage feature-enhanced string matching
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Extraction of shallow language patterns: an approximation of data oriented parsing
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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This paper explores the kinds of probabilistic relations that are important in syntactic disambiguation. It proposes that two widely used kinds of relations, lexical dependencies and structural relations, have complementary disambiguation capabilities. It presents a new model based on structural relations, the Tree-gram model, and reports experiments showing that structural relations should benefit from enrichment by lexical dependencies.