Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Automatic labeling of semantic roles
Computational Linguistics
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Assigning function tags to parsed text
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A connectionist architecture for learning to parse
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
More accurate tests for the statistical significance of result differences
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Function tagging
Generalised PP-attachment disambiguation using corpus-based linguistic diagnostics
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
The necessity of parsing for predicate argument recognition
ACL '02 Proceedings of the 40th 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
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Information extraction for question answering: improving recall through syntactic patterns
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
The necessity of syntactic parsing for semantic role labeling
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A statistical semantic parser that integrates syntax and semantics
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
The integration of syntactic parsing and semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Fully parsing the Penn Treebank
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Parsing Discontinuous Phrase Structure with Grammatical Functions
GoTAL '08 Proceedings of the 6th international conference on Advances in Natural Language Processing
Semantic parsing for high-precision semantic role labelling
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Accurate parsing of the proposition bank
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
Multilingual joint parsing of syntactic and semantic dependencies with a latent variable model
Computational Linguistics
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In this paper, we explore two extensions to an existing statistical parsing model to produce richer parse trees, annotated with function labels. We achieve significant improvements in parsing by modelling directly the specific nature of function labels, as both expressions of the lexical semantics properties of a constituent and as syntactic elements whose distribution is subject to structural locality constraints. We also reach state-of-the-art accuracy on function labelling. Our results suggest that current statistical parsing methods are sufficiently robust to produce accurate shallow functional or semantic annotation, if appropriately biased.