Understanding Natural Language
Understanding Natural Language
Assimilation of New Information by a Natural Language Understanding System
Assimilation of New Information by a Natural Language Understanding System
Computational interpretation of english spatial prepositions.
Computational interpretation of english spatial prepositions.
A system of semantic primitives
TINLAP '75 Proceedings of the 1975 workshop on Theoretical issues in natural language processing
The relation of grammar to cognition: a synopsis
TINLAP '78 Proceedings of the 1978 workshop on Theoretical issues in natural language processing
On the interdependence of language and perception
TINLAP '78 Proceedings of the 1978 workshop on Theoretical issues in natural language processing
Reference Frames for Spatial Inference in Text Understanding
Spatial Cognition, An Interdisciplinary Approach to Representing and Processing Spatial Knowledge
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In order for a natural language system to truly "know what it is talking about," it must have a connection to the real-world correlates of language. For language describing physical objects and their relations in a scene, a visual analog representation of the scene can provide a useful target structure to be shared by a language understanding system and a computer vision system. This paper discusses the generation of visual analog representations from input English sentences. It also describes the operation of a LISP program which generates such a representation from simple English sentences describing a scene. A sequence of sentences can result in a fairly elaborate model. The program can then answer questions about relationships between the objects, even though the relationships in question may not have been explicit in the original scene description. Results suggest that the direct testing of visual analog representations may be an important way to bypass long chains of reasoning and to thus avoid (he combinational problems inherent in such reasoning methods.