Plans for a task-oriented evaluation of natural language understanding systems
HLT '89 Proceedings of the workshop on Speech and Natural Language
An intelligent analyzer and understander of English
Communications of the ACM
Integrating top-down and bottom-up strategies in a text processing system
ANLC '88 Proceedings of the second conference on Applied natural language processing
The TICC: parsing interesting text
ANLC '88 Proceedings of the second conference on Applied natural language processing
Recovering implicit information
ACL '86 Proceedings of the 24th annual meeting on Association for Computational Linguistics
Analysis and processing of compact text
COLING '82 Proceedings of the 9th conference on Computational linguistics - Volume 1
Preference semantics for message understanding
HLT '89 Proceedings of the workshop on Speech and Natural Language
Evaluating parsing strategies using standardized parse files
ANLC '92 Proceedings of the third conference on Applied natural language processing
New York University: description of the PROTEUS system as used for MUC-3
MUC3 '91 Proceedings of the 3rd conference on Message understanding
New York University: description of the Proteus system as used for MUC-5
MUC5 '93 Proceedings of the 5th conference on Message understanding
New York University: description of the PROTEUS system as used for MUC-4
MUC4 '92 Proceedings of the 4th conference on Message understanding
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We consider the problem of extracting specified types of information from natural language text. To properly analyze the text, we wish to apply semantic (selectional) constraints whenever possible; however, we cannot expect to have semantic patterns for all the input we may encounter in real texts. We therefore use preference semantics: selecting the analysis which maximizes the number of semantic patterns matched. We describe a specific information extraction task, and report on the benefits of using preference semantics for this task.