Strategies for Natural Language Processing

By Wendy G. Lehnert; Martin H. Ringle | Go to book overview

4
Parsing and Comprehending with Word Experts (A Theory and its Realization)

Steve Small Chuck Rieger University of Maryland


INTRODUCTION

In Rieger ( 1977, 1978), Rieger and Small ( 1979), and Small ( 1980), we advanced a model of natural-language understanding called the Word Expert Parser (WEP). In this model, we treat each word of language as a complex procedural knowledge source -- a "word expert" -- which contains decision pathways reflecting the range of linguistic and other world knowledge about the word necessary to understand the word in a broad variety of contexts. This model's structure rests on our hypotheses that: (1) human knowledge about language is organized primarily as knowledge about words rather than as knowledge about rules; and (2) language understanding is largely the coordination of information exchange among word experts as each diagnoses its own involvement in its linguistic and conceptual environment. Rather than rule application or matching, the WEP's main concern is, therefore, one of mediating the passing of linguistic signals and concept fragments among words experts as each goes about its own comprehension activities.

This model structure derives from our theory that parsing knowledge is inseparably entwined with complex, frequently idiosyncratic word-based world knowledge. It is our belief that language is not suited for description by rules that describe general principles. It is our belief that humans do not understand language by the orderly application of rules, but rather by the controlled interchange of semaphores and concepts among internally complex "experts," one per linguistic unit (that is, word or morpheme).

The Word Expert Parser has reached a level of development that we can now characterize as a good first approximation to the general theory of language we

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Strategies for Natural Language Processing
Table of contents

Table of contents

  • Title Page iii
  • Contents vii
  • Preface xiii
  • Abstracts xvii
  • I - Introduction 1
  • 1 - The State of the Art In Natural-Language Understanding 3
  • Acknowledgments 30
  • References 30
  • II - Implementation Issues 33
  • 2 - Realistic Language Comprehension 37
  • References 53
  • 3 - Natural Communication Between Person and Computer 55
  • Acknowledgments 86
  • References 86
  • 4 - Parsing and Comprehending With Word Experts (a Theory And Its Realization) 89
  • Acknowledgments 147
  • References 147
  • 5 - An Overview of the Frump System 149
  • Acknowledgments 175
  • References 175
  • 6 - A Framework for Conceptual Analyzers 177
  • References 196
  • III - Conversation And Discourse 199
  • 7 - Conversation Failure 203
  • References 220
  • 8 - Towards an Understanding Of Coherence in Discourse 223
  • Acknowledgments 242
  • References 242
  • 9 - Beyond Question Answering 245
  • Acknowledgments 271
  • References 271
  • 10 - Adversary Arguments and The Logic of Personal Attacks 275
  • Acknowledgments 293
  • References 294
  • IV - Knowledge Representation 295
  • 11 - Inference and Learning In Computer Model of The Development of Language Comprehension in a Young Child 299
  • Acknowledgments 325
  • References 325
  • 12 - Inferring Building Blocks For Knowledge Representation 327
  • Acknowledgments 343
  • References 343
  • 13 - Points: A Theory of the Structure Of Stories in Memory 345
  • References 373
  • 14 - Plot Units: a Narrative Summarization Strategy 375
  • Acknowledgments 411
  • References 411
  • V - Theoretical Issues 413
  • 15 - Metaphor: an Inescapable Phenomenon In Natural-Language Comprehension 415
  • Acknowledgments 432
  • References 433
  • 16 - Context Recognition In Language Cornprehension 435
  • Acknowledgments 453
  • References 453
  • 17 - Reminding and Memory Organization: an Introduction To Mops 455
  • Acknowledgments 493
  • References 493
  • 18 - Some Thoughts on Procedural Semantics 495
  • Acknowledgments 515
  • Notes on Contributors 517
  • Subject Index 523
  • Index 529
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