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Báo cáo khoa học: "A Revised Design for an Understanding Machine"

This paper argues that machine translation programs will be able to solve certain problems, e.g., the resolution of polysemy, only by storing the meaning of natural language words in a medium and a format providing properties similar to those of human “understanding”. | Mechanical Translation Vol.7 no.1 July 1962 A Revised Design for an Understanding Machine by Ross Quillian Research Laboratory of Electronics Massachusetts Institute of Technology This paper argues that machine translation programs will be able to solve certain problems e.g. the resolution of polysemy only by storing the meaning of natural language words in a medium and a format providing properties similar to those of human understanding . It also maintains that all human meaning may be exhaustively represented in terms of readings on a practically infinite number of calibrated standards or alternatively by elaborate constellations of readings on a very small number of element standards. It is proposed that representing the meanings of natural language words in terms of such constellations is to represent them in a medium appropriate to serve as a mechanical equivalent of human understanding at least for the purposes of mechanical translation. Such representation of meaning would also permit the overall body of semantic information to be stratified in accord with the dimensional complexity of concepts. This would allow encyclopedic amounts of information about the meaning of each natural language word to be stored in memory for use when a decision dependent on understanding arose while at the same time only very brief summational symbols of this information would ordinarily be adequate as a translation interlingua. Several general characteristics of such representation and storage of semantic information and some of the standards possibly usable as element standards are described. 1. The Nature of Semantic Understanding and Its Indispensability in Machine Translation This paper will attempt to outline a way of representing any given unit of semantic content in a form which would maintain an invariance during combination. This is not generally the case for the representation of meaning in natural languages but would appear to be the case for the way meaning is .