Representing Knowledge of Large-scale Space
Representing Knowledge of Large-scale Space
Computer Understanding of Physics Problems Stated in Natural Language.(Dissertation), also Technical Report NL-30
Computational interpretation of english spatial prepositions.
Computational interpretation of english spatial prepositions.
TINLAP '75 Proceedings of the 1975 workshop on Theoretical issues in natural language processing
TINLAP '75 Proceedings of the 1975 workshop on Theoretical issues in natural language processing
On the spatial uses of prepositions
ACL '80 Proceedings of the 18th annual meeting on Association for Computational Linguistics
Natural language driven image generation
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Research at the U. of Illinois
ACM SIGART Bulletin
Toward a detailed model of processing for language describing the physical world
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Some basic mechanisms for common sense reasoning about stories environments
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
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The language of scene descriptions must allow a hearer to build structures of schemas similar (to some level of detail) to those the speaker has built via perceptual processes. The understanding process in general requires a hearer to create and run "event simulations" to check the consistency and plausibility of a "picture" constructed from a speaker's description. A speaker must also run similar event simulations on his own descriptions in order to be able to judge when the hearer has been given sufficient information to construct an appropriate "picture", and to be able to respond appropriately to the hearer's questions about or responses to the scene description.In this paper I explore some simple scene description examples in which a hearer must make judgements involving reasoning about scenes, space, common-sense physics, cause-effect relationships, etc. While I propose some mechanisms for dealing with such scene descriptions, my primary concern at this time is to flesh out our understanding of just what the mechanisms must accomplish: what information will be available to them and what information must be found or generated to account for the inferences we know are actually made.