Winograd, T.



An overview of KRL, a knowledge representation language

Classics

The formalism for declarative knowledge is based on structured conceptual objects with associated descriptions. The control structure of krl is based on the belief that the next generation of intelligent programs will integrate data-directed and goal-directed processing by using multiprocessing. It provides procedure directories which operate along with process frameworks to allow procedural parameterization of the fundamental system processes for building, comparing, and retrieving memory structures. Future development of krl will include integrating procedure definition with the descriptive formalism.


GUS, a frame-driven dialog system

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GUS is the first of a series of experimental computer systems that we intend to construct as part of a program of research on language understanding. GUS (Genial Understander System) is intended to engage a sympathetic and highly cooperative human in an English dialog, directed towards a specific goal within a very restricted domain of discourse. There is good reason for restricting the domain of discourse for a computer system which is to engage in an English dialog. Specializing the subject matter that the system can talk about permits it to achieve some measure of realism without encompassing all the possibilities of human knowledge or of the English language.



A procedural model of language understanding

Classics

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Understanding natural language

Classics

This paper describes a computer system for understanding English. It is based on the belief that in modeling language understanding, we must deal in an integrated way with all of the aspects of language--syntax, semantics, and inference. It enters into a dialog with a person, responding to English sentences with actions and English replies, asking for clarification when its heuristic programs cannot understand a sentence through the use of syntactic, semantic, contextual, and physical knowledge. By developing special procedural representations for syntax, semantics, and inference, we gain flexibility and power.