Semantic interpretation and the resolution of ambiguity
Semantic interpretation and the resolution of ambiguity
The self-extending phrasal lexicon
Computational Linguistics - Special issue of the lexicon
Logic for Problem Solving
The organization of knowledge in a multi-lingual, integrated parser (natural language, translation)
The organization of knowledge in a multi-lingual, integrated parser (natural language, translation)
PHRAN: a knowledge-based natural language understander
ACL '80 Proceedings of the 18th annual meeting on Association for Computational Linguistics
Concretion: assumption-based understanding
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
Interactive incremental chart parsing
EACL '89 Proceedings of the fourth conference on European chapter of the Association for Computational Linguistics
Incremental dependency parsing
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Incremental parsing and reason maintenance
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Concretion: assumption-based understanding
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
Disambiguation by prioritized circumscription
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Analyzing Completeness and Correctness of Utterances Using an ATMS
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
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In natural language, as in other computational task domains it is important to operate by default assumptions. First, many constraints required for constraint propagation are initially unspecified. Second, in highly ambiguous tasks such as text analysis, ambiguity can be reduced by considering more plausible scenarios first. Default reasoning is problematic for first-order logic when allowing non-monotonic inferences. Whereas in monotonic logic facts can only be asserted, in non-monotonic logic a system must be maintained consistent even as previously assumed defaults are being retracted.Non-monotonicty is pervasive in natural language due to the serial nature of utterances. When reading text left-to-right, it happens that default assumptions made early in the sentence must be withdrawn as reading proceeds. Truth maintenance, which accounts for non-monotonic inferences, can resolve this issue and address important linguistic phenomena. In this paper we describe how in NMG (Non-Monotonic Grammar), by monitoring a logic parser, a truth maintenance system can significantly, enhance the parser's capabilities.