Grammatical category disambiguation by statistical optimization
Computational Linguistics
Mechanizing Multi-Agent Reasoning with Belief Contexts
FAPR '96 Proceedings of the International Conference on Formal and Applied Practical Reasoning
Formal Specification of Beliefs in Multi-Agent Systems
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Corpus-Driven Unsupervised Learning of Verb Subcategorization Frames
AI*IA '97 Proceedings of the 5th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
A stochastic parts program and noun phrase parser for unrestricted text
ANLC '88 Proceedings of the second conference on Applied natural language processing
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
NLP '00 Proceedings of the Second International Conference on Natural Language Processing
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This paper presents a definition of context for the interpretation of word-structure that is based on the formal relation of asymmetry. We provide evidence that morpho-conceptual complexity is optimally tractable in terms of local asymmetrical relations in formal context. We present the main features of a morpho-conceptual parser implementing our proposal. We show, on the basis of the comparison with existing morphological parsers, that the accuracy of the analysis increases when the operations of the parser are oriented by the recognition of local asymmetries in formal contexts. We predict that the inclusion of modules scanning local asymmetries in information processing systems will increase their precision.