The KBMT Project - 1st Edition - ISBN: 9781558601291, 9780080518909

The KBMT Project

1st Edition

A Case Study in Knowledge-Based Machine Translation

Editors: Kenneth Goodman Sergei Nirenburg
Paperback ISBN: 9781558601291
eBook ISBN: 9780080518909
Imprint: Morgan Kaufmann
Published Date: 1st July 1991
Page Count: 331
85.95 + applicable tax
54.95 + applicable tax
43.99 + applicable tax
72.95 + applicable tax
Unavailable
Compatible Not compatible
VitalSource PC, Mac, iPhone & iPad Amazon Kindle eReader
ePub & PDF Apple & PC desktop. Mobile devices (Apple & Android) Amazon Kindle eReader
Mobi Amazon Kindle eReader Anything else

Institutional Access


Description

Machine translation of natural languages is one of the most complex and comprehensive applications of computational linguistics and artificial intelligence. This is especially true of knowledge-based machine translation (KBMT) systems, which require many knowledge resources and processing modules to carry out the necessary levels of analysis, representation and generation of meaning and form. The number of real-world problems, tasks, and solutions involved in developing any realistic-size knowledge-based machine translation system is enormous. It is thus difficult for researchers in the field to learn what a system "really does".

This book fills that need with a detailed case study of a KBMT system implemented at the Center for Machine Translation at Carnegie Mellon University. The research consists in part of the creation of a system for translation between English and Japanese. The corpora used in the project were manuals for installing and maintaining IBM personal computers (sponsorship by IBM, through its Tokyo Research Laboratory) Individual chapters describe the interlingua texts used in knowledge-based machine translation, the grammar formalism embodied in the system, the grammars and lexicons and their roles in the translation process, the process of source language analysis, an augmentation module that interactively and automatically resolves ambiguities remaining after source language analysis, and the generator, which produces target language sentences. Detailed appendices illustrate the process from analysis through generation.

This book is intended for developers, researchers and advanced students in natural language processing and computational linguistics, including all those who have an interest in machine translation and machine-aided translation.

Table of Contents

The KBMT Project: A Case Study in Knowledge-Based Machine Translation
Edited by Kenneth Goodman and Sergei Nirenburg

    Preface
    1 Introduction

      1.1 Specifications and Architecture
      1.2 The KBMT-89 Approach to Machine Translation
      1.3 An Overview of the System and the Book
      1.4 Extensions and Prospects

    2 World Knowledge and Text Meaning

      2.1 The Concept Lexicon

        2.1.1 Knowledge Acquisition and Maintenance
        2.1.2 Ontological Postulates
        2.1.3 The Domain Ontology
      2.2 The Interlingua Text

        2.2.1 Varieties of World Knowledge in a Knowledge-Based MT System
        2.2.2 Integration of Discourse and Propositional Knowledge
        2.2.3 Representative Classes of Discourse Knowledge
        2.2.4 Combining Concept Tokens into Networks
        2.2.5 Interlingua Text and the Concept of Microtheories
        2.2.6 Meaning and Representation
        2.2.7 A Sample ILT

    3 Syntactic Theory and Processing

      3.1 Two Types of Syntactic Structure

        3.1.1 Constituent Structure
        3.1.2 Feature Structures
        3.1.3 F-Structures in Machine Translation and Linguistic Theory
      3.2 Unification: Building F-Structures during Parsing

        3.2.1 C-Structures and Their Corresponding F-Structures
        3.2.2 Names of F-Structures
        3.2.3 An Informal Characterization of Unification
        3.2.4 Building F-Structures during Parsing
        3.2.5 Constraining Grammatical Features <

Details

No. of pages:
331
Language:
English
Copyright:
© Morgan Kaufmann 1991
Published:
Imprint:
Morgan Kaufmann
eBook ISBN:
9780080518909
Paperback ISBN:
9781558601291

About the Editor

Kenneth Goodman

Sergei Nirenburg

Reviews

Machine translation of natural languages is one of the most complex and comprehensive applications of computational linguistics and artificial intelligence. This is especially true of knowledge-based machine translation (KBMT) systems, which require many knowledge resources and processing modules to carry out the necessary levels of analysis, representation and generation of meaning and form. The number of real-world problems, tasks, and solutions involved in developing any realistic-size knowledge-based machine translation system is enormous. It is thus difficult for researchers in the field to learn what a system "really does".

This book fills that need with a detailed case study of a KBMT system implemented at the Center for Machine Translation at Carnegie Mellon University. The research consists in part of the creation of a system for translation between English and Japanese. The corpora used in the project were manuals for installing and maintaining IBM personal computers (sponsorship by IBM, through its Tokyo Research Laboratory) Individual chapters describe the interlingua texts used in knowledge-based machine translation, the grammar formalism embodied in the system, the grammars and lexicons and their roles in the translation process, the process of source language analysis, an augmentation module that interactively and automatically resolves ambiguities remaining after source language analysis, and the generator, which produces target language sentences. Detailed appendices illustrate the process from analysis through generation.

This book is intended for developers, researchers and advanced students in natural language processing and computational linguistics, including all those who have an interest in machine translation and machine-aided translation.