A high-level representation language for the construction and use of large knowledge bases

作者:

Highlights:

摘要

The “conceptual” Knowledge Representation Language (KRL) proper to a general environment for the construction of Large Knowledge Bases (LKBs) involves two different but complementary aspects. The coding of the elementary events occurring in the real world (“descriptive” data = “Snoopy is Charlie Brown's beagle”) is organized around a “semantic predicate”; the conceptual units constructed in this way take the name of “predictive occurrences.” Moreover, the predicative occurrences can be associated, giving rise to “binding occurrences.” On the other hand, the “classes” representing the “general categories”, to which can be reduced all the basic entities of the application domain which appear in the predicative occurrences, are defined in terms ofa specialization hierarchy (“lexicon” = “A beagle is a sort of hound/a hound is a dog. . .); analogously, the occurrences (and their generic “templates”) are classified according to their own specialized hierarchy (“grammar”). The “lexicon” and the “grammar,” together, set up the “definitional” component of the language.

论文关键词:

论文评审过程:Available online 26 February 2003.

论文官网地址:https://doi.org/10.1016/0957-4174(90)90021-L