CU-PROLOG FOR CONSTRAINT-BASED NATURAL-LANGUAGE PROCESSING

This paper introduces a constraint logic programming (CLP) language cu-Prolog as an implementation framework for constraint-based natural language processing. Compared to other CLP languages, cu-Prolog has several unique features. Most CLP languages take algebraic equations or inequations as constraints. cu-Prolog, on the other hand, takes Prolog atomic formulas in terms of user-defined predicates. cu-Prolog, thus, can describe symbolic and combinatorial constraints occurring in the constraint-based grammar formalisms. As a constraint solver, cu-Prolog uses the unfold/fold transformation, which is well known as a program transformation technique, dynamically with some heuristics. To treat the information partiality described with feature structures, cu-Prolog uses PST (Partially Specified Term) as its data structure. Sections 1 and 2 give an introduction to the constraint-based grammar formalisms on which this paper is based and the outline of cu-Prolog is explained in Sect. 3 with implementation issues described in Sect. 4. Section 5 illustrates its linguistic application to disjunctive feature structure (DFS) and parsing constraint-based grammar formalisms such as Japanese Phrase Structure Grammar (JPSG). In either application, a disambiguation process is realized by transforming constraints, which gives a picture of constraint-based NLP.