Implementing contexts in logic programming

1993

Computational Linguistics and Logic Programming have strong connections, but the former uses concepts that are absent from the most familiar implementations of the latter. We advocate that a Logic Programming language need not feature the Computational Linguistics concepts exactly, it must only provide a logical way of dealing with them. We focus on the manipulation of higher-order terms and the logical handling of context, and we show that the advanced features of Prolog II and Prolog are useful for dealing with these concepts. Higher-order terms are native in Prolog, and Prolog II's in nite trees provide a handy data-structure for manipulating them. The formula language of Prolog can be transposed in the Logic Grammar realm to allow for a logical handling of context. < Logic Programming has connections with Computational Linguistics at both the syntactic level and the semantic level. Logic Programming, via Prolog, can be considered as a by-product of studies on automating the analysis of natural language 10]. The relationship was re ned through the notion of Logic Grammars 46, 1], but eventually natural language formalisms became more sophisticated independently. We are now at a stage in which more sophisticated natural language grammar formalisms like Generalized Phrase Structure Grammar (GPSG 21]) have no clear counterpart in Prolog, the standard incarnation of Logic Programming.

Standardization for Prolog came during the 1990's, initially and deliberately leaving out one aspect which is essential for real world application development: the modularity mechanism. This situation has in the meantime been remedied in the current ISO proposal for modules in Prolog. In this article we build on our previous work on Contextual Logic Programming (CxLP) and introduce mechanisms which provide much needed functionality: on one hand, a stricter specification for acceptable program structure when using contexts and, on the other, a mechanism which more effectively promotes OO-style code reuse and concealment, while retaining a lightweight syntax.

Lecture Notes in Computer Science, 1994

The Journal of Logic Programming, 1992

Declarative Programming for Knowledge …, 2006

Artificial Intelligence, 2002

In this paper we give a short introduction to logic programming approach to knowledge representation and reasoning. The intention is to help the reader to develop a 'feel' for the field's history and some of its recent developments. The discussion is mainly limited to logic programs under the answer set semantics. For understanding of approaches to logic programming built on well-founded semantics, general theories of argumentation, abductive reasoning, etc., the reader is referred to other publications.  (M. Gelfond), [email protected] (N. Leone). 0004-3702/02/$ -see front matter  2002 Elsevier Science B.V. All rights reserved. PII: S 0 0 0 4 -3 7 0 2 ( 0 2 ) 0 0 2 0 7 -2

Software: Practice and Experience, 1991

By using practical examples, this paper outlines the power of reflection mechanisms for logic programming systems in the domain of knowledge structuring. In particular, it presents an extension of Prolog, where separate databases can be handled as first-class objects. Different forms of database combination such as inheritance and dynamic context extension/contraction are specified and implemented in a dynamic and flexible way through reflection. The main aim is to broaden the application area of logic programming to encompass most of the paradigms needed by systems that use artificial intelligence techniques. Practical results presented in the paper show that logic programs that use reflection can be shorter, more readable and efficient than those using more conventional full meta-interpretation techniques. Full metainterpretation, however, is more general than reflection.

saber.ula.ve

Theoretical Computer Science, 1992

The linguistic theory of Richard Montague (variously referred to as Montague Grammar or Montague Semantics) provides a comprehensive formalized account of natural language semantics. It appears to be particularly applicable to the problem of natural language understanding by computer systems. However the theory does not deal with meaning at the lexical level. With few exceptions, lexical items are treated simply as unanalyzed basic expressions. As a result, comparison of distinct lexical meanings or of semantic expressions containing these lexical meanings falls outside the theory. In this paper, I attempt to provide a compatible theory of lexical semantics which may serve as an extension of Montague Semantics.

1995

Prolog has been marketed as a declarative programming language. In practical programming, however, this pretension is seldom justi ed. There are many reasons for the gap between the theory of logic programming and the practice of Prolog, the most important being the lack of a type system and the fact that the hitherto developed declarative semantics for Prolog makes no attempt to capture the meaning of the cut operator. This paper shows a way of equipping Prolog with a declarative semantics that takes the e ects of the cut operator into consideration. This approach o ers a possibility of reconciling Prolog and logic programming.