A theory for the representation of knowledge

Journal Article · Wed Jan 01 04:00:00 EST 1986 · IBM J. Res. Dev.; (United States)

DOI:https://doi.org/10.1147/rd.301.0039· OSTI ID:5724684

Guenthner, F; Lehmann, H; Schonfeld, W

How to represent knowledge is one of the key questions in the construction of expert systems. Its solution depends on a number of factors, the most important of which are how knowledge is to be acquired and how it is to be used. Since the authors are interested in the use of natural language for communication with computers, they require from a formalism suggested for knowledge representation that it be suitable as a target for the systematic translation from natural language expressions. They propose a theory, called Discourse Representation Theory (DRT), which was originally developed by Kamp to analyze natural language discourse, as a means to represent knowledge in an expert system. With Discourse Representation Theory it has been possible to solve certain cases of contextual relations which have puzzled linguists and logicians for a long time. In this paper they give a precise definition of DRT and describe the rules used to translate from natural language to Discourse Representation Structures (DRSs), the central notion of the theory. They show how the notation used in DRT relates to standard predicate logic and define its deductive theory. They also outline ways of implementing DRT and the proof procedures they use.

• OSTI ID: 5724684
• Journal Information: IBM J. Res. Dev.; (United States), Journal Name: IBM J. Res. Dev.; (United States) Vol. 30:1; ISSN IBMJA
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
ARTIFICIAL INTELLIGENCE
COMPUTERS
EXPERT SYSTEMS
PROGRAMMING
PROGRAMMING LANGUAGES