Book:

 

COMPUTATIONAL LINGUISTICS:
Models, Resources, Applications

 

Igor A. Bolshakov and Alexander Gelbukh

IPN-UNAM-FCE, 2004, 186 pp.
ISBN 970-36-0147- 2

 

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Abstract: Can computers meaningfully process human language? If this is difficult, why? If this is possible, how? This book introduces the reader to the fascinating science of computational linguistics and automatic natural language processing, which combines linguistics and artificial intelligence. The main part of the book is devoted to the explanation of the inner working of a linguistic processor, a software module in charge of translating natural language input into a representation directly usable by traditional artificial intelligence applications and, vice versa, of translating their answer into human language. Overall emphasis in the book is made on a well-elaborated, thoughŚfor a number of historical reasonsŚso far little-known in the literature computational linguistic model called Meaning-Text Theory. For comparison, other models and formalisms are considered in detail. The book is mainly oriented to researchers and students interested in applications of natural language processing techniques to Spanish language. In particular, most of the examples given in the book deal with Spanish language materialŚwhich is a feature of the book distinguishing it from other books on natural language processing. However, our main exposition is sufficiently general to be applicable to a wide range of languages. Specifically, it was taken into account that many readers of the book will be Spanish native speakers. For them, some comments on the English terminology, as well as a short English-Spanish dictionary of technical terms used in the book, were included. Still, reading the book in English will help Spanish-speaking readers to become familiar with the style and terminology used in the scientific literature on the subject.

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Contents

Preface

A new book on computational linguistics

Objectives and intended readers of the book

Coordination with computer science

Coordination with artificial intelligence

Selection of topics

Web resources for this book

Acknowledgments

I.    Introduction

The role of natural language processing

Linguistics and its structure

What we mean by computational linguistics

Word, what is it?

The important role of the fundamental science

Current state of applied research on Spanish

Conclusions

II.   A Historical Outline

The structuralist approach

Initial contribution of Chomsky

A simple context-free grammar

Transformational grammars

The linguistic research after Chomsky: Valencies and interpretation

Linguistic research after Chomsky: Constraints

Head-driven Phrase Structure Grammar

The idea of unification

The Meaning Text Theory: Multistage transformer and government patterns

The Meaning Text Theory: Dependency trees

The Meaning Text Theory: Semantic links

Conclusions

III.  Products of Computational Linguistics: Present and Prospective

Classification of applied linguistic systems

Automatic hyphenation

Spell checking

Grammar checking

Style checking

References to words and word combinations

Information retrieval

Topical summarization

Automatic translation

Natural language interface

Extraction of factual data from texts

Text generation

Systems of language understanding

Related systems

Conclusions

IV.  Language as a Meaning  Text Transformer

Possible points of view on natural language

Language as a bi-directional transformer

Text, what is it?

Meaning, what is it?

Two ways to represent Meaning

Decomposition and atomization of Meaning

Not-uniqueness of Meaning Ů Text mapping: Synonymy

Not-uniqueness of Text Ů Meaning mapping: homonymy

More on homonymy

Multistage character of the Meaning Text transformer

Translation as a multistage transformation

Two sides of a sign

Linguistic sign

Linguistic sign in the mmt

Linguistic sign in hpsg

Are signifiers given by nature or by convention?

Generative, mtt, and constraint ideas in comparison

Conclusions

V.   Linguistic Models

What is modeling in general?

Neurolinguistic models

Psycholinguistic models

Functional models of language

Research linguistic models

Common features of modern models of language

Specific features of the Meaning  Text Model

Reduced models

Do we really need linguistic models?

Analogy in natural languages

Empirical versus rationalist approaches

Limited scope of the modern linguistic theories

Conclusions

Exercises

Review questions

Problems recommended for exams

Literature

Recommended literature

Additional literature

General grammars and dictionaries

References

Appendices

Some Spanish-oriented groups and resources

English-Spanish dictionary of terminology

Index of illustrations

Index of authors, systems, and terminology

 

ERRATA

  1. Page 41 (49 in PDF), line 7: "roles stay the same, bit it is not clear" should read "but" instead of "bit." Thanks to Carlos Silla, Brazil.
  2. "Why automatic natural language processing (npl) is important for the humankind?" should be "Why is ..." (and some other questions).