An algorithm for generating quantifier scopings
Computational Linguistics
Computational complexity of terminological reasoning in BACK
Artificial Intelligence
Terminological reasoning is inherently intractable (research note)
Artificial Intelligence
Subsumption in KL-ONE is undecidable
Proceedings of the first international conference on Principles of knowledge representation and reasoning
The relation-based knowledge representation of King Kong
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
Inside the LOOM description classifier
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A terminological simplification transformation for natural language question-answering systems
ACL '86 Proceedings of the 24th annual meeting on Association for Computational Linguistics
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Logical Forms in the core language engine
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Concretion: assumption-based understanding
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
Overview of the fourth message understanding evaluation and conference
MUC4 '92 Proceedings of the 4th conference on Message understanding
Inferential Information Extraction
Information Extraction: Towards Scalable, Adaptable Systems
MITRE: description of the Alembic system used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
Reading comprehension tests for computer-based understanding evaluation
Natural Language Engineering
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This paper is concerned with an inferential approach to information extraction reporting in particular on the results of an empirical study that was performed to validate the approach. The study brings together two lines of research (1) the RHO framework for tractable terminological knowledge representation and (2) the Alembic message understanding system. There are correspondingly two principal aspects of interest to this work From the knowledge representation perspective the present study serves to validate experimentally a normal form hypothesis that guarantees tractability of inference in the RHO framework. From the message processing perspective this study substantiates the utility of limited inference to information extraction.