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Acknowledgement
Contents
List of Figures
Introduction
The Goals of the Thesis
A novel uniform tabular algorithm
A performance model based on uniform processing.
Implementation
Towards a competence-based performance model of natural language
Overview
Current Approaches in Reversible Systems
Arguments for Reversible Natural Language Processing
Psycholinguistic Motivations
Engineering and Computational Motivations
Consistency
Non-redundancy
Portability and Flexibility
Adaptability to Language Use of Others
Possible Arguments against Reversibility
A Classification Scheme for Reversible Systems
Problems with Existing Approaches
The Uniform Architecture of Shieber
The Head-driven Approach of Van Noord and Shieber et al.
Gerdemann's Earley Style Processing Scheme
Summary
Linguistic and Formal Foundations
Constraint-based Grammars
Constraint Logic Programming
Constraint Languages and Relational Extensions
Constraint Language
Relational Extension
Definite clauses
Operational semantics
The Constraint Language
Feature Description
Feature Graphs
Interpretation of Constraints
Readable Notation
Specification of Constraint-based Grammars in
Form of grammar rules and lexical entries
Representation of phonological information
Representation of semantic information
Representation of grammatical derivations
Readable notation
Parsing and Generation
Restricted parsing problem
Conclusion
A Uniform Tabular Algorithm for Parsing and Generation
Overview of Earley Deduction
Blocking new lemmas
Use of a restrictor
Generalizing Pereira and Warren's Earley Deduction Scheme
A Data-driven Selection Function
A Data Structure for Lemmas
Specification of Goals
The Inference Algorithm
Prediction
Completion
An Agenda-based Control Regime
Scheduling the tasks of an agenda
Performing Parsing and Generation
Indexing Derived Clauses
A Uniform Indexing Mechanism
Extending the Un-indexed Version to an Indexed Version
A Parsing and Generation Example
Processing of Empty Heads
Parsing
Generation
Properties
General flow of control
Top-down versus bottom-up
Coherence and completeness
Termination
On-line
Uniform indexing mechanism
Agenda-based control
Implementation
Representation of grammar and lexical entries
Representation of item sets
The selection function
Inference rules
The agenda control
Item Sharing Between Parsing and Generation
The Basic Idea
Adaptation of the Uniform Tabular Algorithm
An Object-Oriented Architecture
Implementation
Conclusion
A Performance Model based on Uniform Processing
The Modular Status of Natural Language Systems
Natural Language Systems and Reversible Grammars
Monitoring and Revision
The Monitoring Model of Levelt
Discussion
The Anticipation Feedback Loop Mode
Discussion
Text Revision
Discussion
A Blueprint of the New Model
What does this model contribute to system design?
Monitoring and Revision with Reversible Grammars
Locating Ambiguity with Derivation Trees
Overview of the Monitored Generation Strategy
Marking a Derivation Tree
Changing the Ambiguous Parts
Redefining Locality
Simple Attachment Example
Some More Examples
Properties and Implementation
Properties
Implementation
Generation of Paraphrases
A Naive Version
A More Suitable Strategy
A Suitable Strategy
A Simple Example
Properties
Incremental Interleaving of Parsing and Generation
Basic Problems of Incremental Monitoring
A Look-Back Strategy
Performing Revision Within the Uniform Algorithm
Performing Ambiguity Checks within the Uniform Algorithm
Determination of Context
Check ambiguity
Using Shared Items during Incremental Monitoring
Implementation
Properties of the Incremental Method
Conclusion
Summary and Future Directions
Summary
Future Directions
Application of Explanation-Based Learning for Efficient Processing of Constraint-based Grammars
Further Important Directions
Using Preference-based Strategies.
Processing of Elliptical Utterances.
Fully Incremental Text Processing.
Cognitive Processing
Aspects of Cognitive Parsing
Aspects of Cognitive Generation
A Sample Grammar
References
About this document ...
Guenter Neumann
Mon Oct 5 14:01:36 MET DST 1998