Knowledge representation issues in computational linguistics
Presuppositions of existence in logical formalisms: A problem that arose in some of our earlier research on intelligent retrieval of legal texts is the representation of existence in logical formalisms. Many of the texts talked about whether or not something exists, usually an abstract entity like liability. It has been generally accepted in philosophy since Kant that existence is not a simple predicate---that is, one cannot say things like exists(liability) as one would say red(ball). Taking existence as a predicatable property leads to logical fallacies. The problem in AI, then, is how existence can be represented without the danger of obtaining fallacious inferences. Unfortunately, the now-conventional Russellian approach of making existence a quantifier also causes many problems in representing natural language. But we have identified one philosophical theory (by Terence Parsons) that may be adaptable for NLU. This approach uses two different kinds of predication, one of which has special behaviour and may be used for existence and certain other properties that are not normally well behaved. Graeme Hirst has made this approach meet up with conventional AI approaches by refining the notion of existence into about eight different types, each a separate predicate, and dividing the universe into kosher and tref parts. Quantifiers may scope only over the kosher area, and entities in the tref area may be mentioned but not used.
Reference:
- Hirst, Graeme. ``Existence assumptions in knowledge representation.'' Artificial Intelligence, 49, May 1991, 199--242. (Reprinted in: Brachman, Ronald J.; Levesque, Hector J.; and Reiter, Raymond (editors). Knowledge Representation. Cambridge, MA: The MIT Press, 1992.) PDF (2.6Mb).
Context in language is not the same as context in knowledge representation: AI formalizations of context, particularly the formalization by McCarthy and Buvac, regard context as an undefined primitive whose formalization can be the same in many different kinds of AI tasks. This is not appropriate. Any theory of context in natural language must take the special nature of natural language into account and cannot regard context simply as an undefined primitive. Graeme Hirst has shown that there is no such thing as a coherent theory of context simpliciter---context pure and simple---and that context in natural language is not the same kind of thing as context in KR. In natural language, context is constructed by the speaker and the interpreter, and both have considerable discretion in so doing. Therefore, a formalization based on pre-defined contexts and pre-defined `lifting axioms' cannot account for how context is used in real-world language.
Reference:
- Hirst, Graeme. ``Context as a spurious concept.'' Proceedings, Conference on Intelligent Text Processing and Computational Linguistics, Mexico City, February 2000, 273--287. PDF. PostScript.
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