An episodic knowledge representation for narrative texts
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Using the inference tool EPILOG for a message processing application
International Journal of Expert Systems - Special Issue: knowledge: multiple aspects & applications
Natural language processing and knowledge representation
Events, Situations, and Adverbs
EPIA 89 Proceedings of the 4th Portuguese Conference on Artificial Intelligence
Interpreting Tense, Aspect and Time Adverbials: A Compositional, Unified Approach
ICTL '94 Proceedings of the First International Conference on Temporal Logic
Knowledge Representation in the TRAINS-93 Conversation System
Knowledge Representation in the TRAINS-93 Conversation System
Commonsense metaphysics and lexical semantics
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
Situated Modelling of Scenarios
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
Turing's dream and the knowledge challenge
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Presupposition incorporation in adverbial quantification
CONTEXT'03 Proceedings of the 4th international and interdisciplinary conference on Modeling and using context
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I argue in favor of associating situations (events, episodes, eventualities, etc.) with arbitrarily complex sentences, not just atomic predicates, in NL interpretation. In that respect, a Situation Semantics approach to incorporating situations into semantic representations is preferable to a Davidsonian one. However, I will further argue that beyond the notion of further or falsity of a sentence in a situation, as in Situation Semantics, we also need the notion of a sentence characterizing a situation, in order to deal adequately with causal relations mentioned or implied in NL texts. I propose a way of doing this that essentially reduces complex situations to joins of basic, Davidsonian ones, along with basic situations corresponding to negated predications. The resulting situational logic, called FOL**, captures many of the essential features of both Davidsonian and Situation Semantics approaches to representing the content of sentences describing situations. The proposed semantics supports common intuitions about truth-in-situations, about the existence of situations characterized by sentences, and about persistence of information from parts of situations to the whole. I allow for temporal parts of situations as well as concurrent parts, and distinguish persistence properties or telic and atelic sentences. The development of FOL** is part of a continuing effort to fully formalize Episodic Logic, an implemented knowledge representation designed to support language understanding.