The Dimensions of Context-Space

Abstract

Contexts have historically been either ignored completely or else treated as black boxes, as indivisible atoms. About a decade ago, as part of our work on building the large Cyc® knowledge base of human common sense and common knowledge, our group began to study and harness the internal structure of that “atom”. Each context was said to have assumptions and content; there was a theory of importing assertions across contexts; contexts were fully reified first-class terms in the CycL representation language; they were partially ordered by specialization to control visibility and access to content; and so on. That 1989-91 work turned out to be inadequate: it was too expensive to do nontrivial lifting (importing); to explicate the assumptions of each context; and to place each assertion/query into the proper context. Over the last few years, as the number of Cyc contexts grew into the thousands, we gained a better understanding of the problem – and a possible solution has emerged. There is a finer internal structure to a context than just those two parts, assumptions and content. There are a dozen mostly-independent dimensions along which contexts vary; conversely, each region of that 12-dimensional space implicitly defin that space is the space of assumptions, and each assertion can be me region of that space. A more advanced calculus of contexts is re imensional constructs, but it should be worth the cost: it should ena much more focused sort of “virtual lifting ” of assertions from one conte – by providing a superstructure that can serve as a principled guide to orient t lder or per user – it should make it easier to specify the proper context in which In this paper, we discuss contexts in general, introduce specific terminology for describing each dimension. We then consider what onto