Parsing with logical variables (original) (raw)

An Assumptive Logic Programming Methodology for Parsing

International Journal on Artificial Intelligence Tools, 2001

We show how two novel tools in logic programming for AI (namely, continuation-based linear and timeless assumptions, and Datalog grammars) can assist us in producing terse treatments of difficult language processing phenomena. As a proof of concept, we present a concise parser for Datalog grammars (logic grammars where strings are represented with numbered word boundaries rather than as lists of words) that uses assumptions and a combination of left-corner parsing and charting. We then study two test cases of this parser's application: complete constituent coordination, and error diagnosis and correction.

Definite clause grammars for language analysis

1980

A clear andpowerfulformalism for describing languages, both natural and artificial, follows fiom a method for expressing grammars in logic due to Colmerauer and Kowalski. This formalism, which is a natural extension of context-free grammars, we call "definite clause grammars" (DCGs).

Principles and Implementation of Deductive Parsing

Journal of Logic Programming, 1995

£ We present a system for generating parsers based directly on the metaphor of parsing as deduction. Parsing algorithms can be represented directly as deduction systems, and a single deduction engine can interpret such deduction systems so as to implement the corresponding parser. The method generalizes easily to parsers for augmented phrase structure formalisms, such as definite-clause grammars and other logic grammar formalisms, and has been used for rapid prototyping of parsing algorithms for a variety of formalisms including variants of tree-adjoining grammars, categorial grammars, and lexicalized context-free grammars.

An Operational Model for Parsing Definite Clause Grammars with Infinite Terms

Logic programs share with context-free grammars a strong reliance on well-formedness conditions. Their proof procedures can be viewed as a generalization of context-free parsing. In particular, de nite clause grammars can be interpreted as an extension of the classic contextfree formalism where the notion of nite set of non-terminal symbols is generalized to a possibly in nite domain of directed graphs. In this case, standard polynomial parsing methods may no longer be applicable as they can lead to gross ine ciency or even non-termination for the algorithms. We present a proposal to avoid these drawbacks, focusing on two aspects: avoiding limitations on the parsing process, and extending the uni cation to composed terms without overload for non-cyclic structures.

An Opterational Model for Parsing Definite Clause Grammars with Infinite Terms

1997

Logic programs share with context-free grammars a strong reliance on well-formedness conditions. Their proof procedures can be viewed as a generalization of context-free parsing. In particular, de nite clause grammars can be interpreted as an extension of the classic contextfree formalism where the notion of nite set of non-terminal symbols is generalized to a possibly in nite domain of directed graphs. In this case, standard polynomial parsing methods may no longer be applicable as they can lead to gross ine ciency or even non-termination for the algorithms. We present a proposal to avoid these drawbacks, focusing on two aspects: avoiding limitations on the parsing process, and extending the uni cation to composed terms without overload for non-cyclic structures.

GALENA: Tabular DCG Parsing for Natural Languages

1998

We present a de nite clause based parsing environment for natural languages, whose operational model is the dynamic interpretation of logical push-down automata. We attempt to brie y explain our design decisions in terms of a set of properties that practical natural language processing systems should incorporate. The aim is to show both the advantages and the drawbacks of our approach.

A Comparison for Unification-Based Parsers

1998

Uni cation-based grammars have been the object of study in computational linguistics over the last few years with the intention of creating powerful parsing environments. However, it is not common to nd practical studies about what the real interest of these techniques is, and which approaches are better adapted in each case.

On the use of advanced logic programming languages

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.