A Case Study in Knowledge-Based Machine Translation To order this title, and for more information, click here
Edited By Kenneth Goodman Sergei Nirenburg
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.
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
3.2.6 F-Structures and Mapping Rules
4 Grammars in Analysis and
Generation
4.1
4.1.1 Identifying Linguistic Generalizations
4.1.2 The Scope of the Grammar
4.1.3
The Content and Structure of Feature Structures
4.1.4 Undergeneration
4.1.5 Overgeneration
4.2
Basic English Sentence Structure
4.2.1 Heads and Projections
4.2.2 Noun Phrases
4.2.2.1 NP Rules and Structures
4.2.2.2 Compound Nouns
4.2.3 Verb Phrases
4.2.3.1 Syntactic Subcategorization
4.2.3.2 Auxiliary
Verbs
4.2.3.3 Projections of V
4.2.4 Other Constructions in English Grammar
4.2.4.2 Relative Clauses
4.2.4.3 Passivization
4.2.5 Unexpressed Subjects
4.3 Japanese Word Order
4.3.1
Japanese Morphological Rules
4.3.2 Japanese Case Markers and Grammatical Functions
4.4 Generation Grammars
4.4.1 Ordering of Equations within Rules
4.4.2 Rule Ordering
4.5 Bidirectionality
5 Analysis Lexicons
5.1 Introduction and Overview
5.2 Structure of the Lexicon Entries
5.3 Notation
5.4 English Inflectional Morphology
5.5 Lexical Mapping Rules
5.6 Closed-Class Lexical
Mapping
5.7 Structural Mapping Rules
5.8 Special Mapping Rules
6 Generation Lexicons
6.1 Differences in Analysis and Generation Lexicons
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