presupposition fails, we now give a short introduction into Unification Grammar. Since all implementations discussed in this volume use PROLOG (with the exception of BlockjHaugeneder), we felt that it would also be useful to explain the difference between unification in PROLOG and in UG. After the introduction to UG we briefly summarize the main arguments for using linguistic theories in natural language processing. We conclude with a short summary of the contributions to this volume. UNIFICATION GRAMMAR 3 Feature Structures or Complex Categories. Unification Grammar was developed by Martin Kay (Kay 1979). Martin Kay wanted to give a precise defmition (and implementation) of the notion of 'feature'. Linguists use features at nearly all levels of linguistic description. In phonetics, for instance, the phoneme b is usually described with the features 'bilabial', 'voiced' and 'nasal'. In the case of b the first two features get the value +, the third (nasal) gets the value -. Feature value pairs in phonology are normally represented as a matrix. bilabial: + voiced: + I nasal: - [Feature matrix for b.] In syntax features are used, for example, to distinguish different noun classes. The Latin noun 'murus' would be characterized by the following feature-value pairs: gender: masculin, number: singular, case: nominative, pred: murus. Besides a matrix representation one frequently fmds a graph representation for feature value pairs. The edges of the graph are labelled by features. The leaves denote the value of a feature.

No detailed description available for "Syntactic Structures".

This volume provides a comprehensive view of the current issues in contemporary syntactic theory. Written by an international assembly of leading specialists in the field, these 2 original articles serve as a useful reference for various areas of grammar. Contains 23 articles written by an international assembly of specialists in the field. The lucidly written articles grant accessibility to crucial areas of syntactic theory. Contrasting theories are represented. Contains an informative introduction and extensive bibliography which serves as a reference tool for both students and professional linguists.

This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natural language and the creation of effective language technologies Serves as an invaluable state-of-the-art reference source for computational linguists and software engineers developing NLP applications in industrial research and development labs of software companies

By formalizing recent syntactic theories for natural languages Stabler shows how their complexity can be handled without guesswork or oversimplification. By formalizing recent syntactic theories for natural languages in the tradition of Chomsky's Barriers, Stabler shows how their complexity can be handled without guesswork or oversimplification. He introduces logical representations of these theories together with special deductive techniques for exploring their consequences that will provide linguists with a valuable tool for deriving and testing theoretical predictions and for experimenting with alternative formulations of grammatical principles. Stabler's novel approach allows results to be deduced with straightforward calculations and provides a systematic framework for tackling the problem of how speakers can infer the properties of an utterance from principles of the grammar. The special treatment of equality, induction principles, and inclusion of a general method for collecting structures from proofs means that sophisticated linguistic arguments can be carried out in detail, giving a rich perspective to issues in linguistic theory and parsing.

This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.

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This volume is intended to be used by practicing scholars as well as students. It represents all major and some of the minor trends that have evolved during the past decade. Book titles from all available sources have been included, as well as periodical articles from the major journals, whenever there was evidence of a theoretical approach. To ensure maximum accessibility of the entries listed, books and articles in language other than English and unpublished dissertations and working papers have been excluded. All entries are fully annotated and the volume is completed by indices of authors and subjects.