Michael C. McCord

Bio: Michael C. McCord is an academic researcher from University of Kentucky. The author has contributed to research in topics: Natural language & Rule-based machine translation. The author has an hindex of 5, co-authored 7 publications receiving 238 citations.

Slot grammars

Abstract: This paper presents an approach to natural language grammars and parsing in which slots and rules for filling them play a major role. The system described provides a natural way of handling a wide variety of grammatical phenomena, such as WH-movement, verb dependencies, and agreement.

Treating coordination in logic grammars

Abstract: Logic grammars are grammars expressible in predicate logic. Implemented in the programming language Prolog, logic grammar systems have proved to be a good basis for natural language processing. One of the most difficult constructions for natural language grammars to treat is coordination (construction with conjunctions like 'and'). This paper describes a logic grammar formalism, modifier structure grammars (MSGs), together with an interpreter written in Prolog, which can handle coordination (and other natural language constructions) in a reasonable and general way. The system produces both syntactic analyses and logical forms, and problems of scoping for coordination and quantifiers are dealt with. The MSG formalism seems of interest in its own right (perhaps even outside natural language processing) because the notions of syntactic structure and semantic interpretation are more constrained than in many previous systems (made more implicit in the formalism itself), so that less burden is put on the grammar writer.

Procedural systemic grammars

Abstract: A formalism PSGL for writing natural language grammars has been developed, along with a computer system for interpreting it and parsing sentences. PSGL combines ideas from augmented transition network theory, systemic grammar, and Chomsky's recent trace theory, in a way that allows one to write compact and linguistically apt grammars.

An introduction to unification-based approaches to grammar

Abstract: This book surveys the important concept of unification as it relates to linguistic theory and, in particular, to Functional Unification Grammar, Definite-Clause Grammars, Lexical-Function Grammar, Generalized Phrase Struture Grammar, and Head-Driven Phrase Structure Grammar. The notes include careful and correct definitions, as well as well-chosen examples of actual grammars, and a discussion of the relationships of computational systems and linguistic theories which use ideas from unification.

An efficient easily adaptable system for interpreting natural language queries

Abstract: This paper gives an overall account of a prototype natural language question answering system, called Chat-80. Chat-80 has been designed to be both efficient and easily adaptable to a variety of applications. The system is implemented entirely in Prolog, a programming language based on logic. With the aid of a logic-based grammar formalism called extraposition grammars, Chat-80 translates English questions into the Prolog subset of logic. The resulting logical expression is then transformed by a planning algorithm into efficient Prolog, cf. "query optimisation" in a relational database. Finally, the Prolog form is executed to yield the answer. On a domain of world geography, most questions within the English subset are answered in well under one second, including relatively complex queries.

Prolog and Natural-Language Analysis

Abstract: From the Publisher: A concise and practical introduction to logic programming and the logic-programming language Prolog, both as vehicles for understanding elementary computational linguistics and as tools for implementing the basic components of natural-language-processing systems.

Parsing as deduction

Abstract: By exploring the relationship between parsing and deduction, a new and more general view of chart parsing is obtained, which encompasses parsing for grammar formalisms based on unification, and is the basis of the Earley Deduction proof procedure for definite clauses. The efficiency of this approach for an interesting class of grammars is discussed.

Improving a statistical MT system with automatically learned rewrite patterns

Abstract: Current clump-based statistical MT systems have two limitations with respect to word ordering: First, they lack a mechanism for expressing and using generalization that accounts for reorderings of linguistic phrases. Second, the ordering of target words in such systems does not respect linguistic phrase boundaries. To address these limitations, we propose to use automatically learned rewrite patterns to preprocess the source sentences so that they have a word order similar to that of the target language. Our system is a hybrid one. The basic model is statistical, but we use broad-coverage rule-based parsers in two ways - during training for learning rewrite patterns, and at runtime for reordering the source sentences. Our experiments show 10% relative improvement in Bleu measure.