Strategies for Natural Language Processing

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

Still Fig. 2.3 does show how the basic ideas interrelate in an RLC system. Knowledge structures are used to drive the analysis in an error-tolerant way, judge the reasonability of what is produced, and organize the results in coherent form. There is a very strong top-down component to this system. Things that are predicted are used to fill out the structure that predicted them. Things that are not predicted either generate new structures that drive the analysis, or are part of phrasal frames that tie the text together.

Any new structure built is tested for reasonability in the domain and modified if something is wrong and there is a known way to reinterpret it. This checkand-correct facility must be part of any near-term RLC program, I think, although its function in human understanding is more controversial. In an RLC program, things have to be reformed because of mistakes in the text, indirect and metaphoric constructions, and mistakes and inadequacies in the program. In my research, I assume that people almost always find the best interpretation first, and look for ways they might do this. But any practical RLC program built now will have to take a longer way round, I fear.


REFERENCES

Becker J. ( 1974) "The phrasal lexicon". In R. C. Schank & B. L. Nash-Webber (Eds.), Theoretical issues in natural language processing. Cambridge, Mass.: Bolt, Beranek and Newman.

Birnbaum L., & Selfridge M. ( 1979) Problems in conceptual analysis of natural language (Research Rep. #168). Computer Science Department, Yale University, New Haven.

Bullwinkle C. ( 1977) "Levels of complexity in discourse for anaphora disambiguation and speech act interpretation". Proc. Fifth International Joint Conference on Artificial Intelligence. Cambridge, Mass.

Charniak E. ( 1972) Towards a model of children's story, comprehension. Doctoral dissertation, Rep. A1 TR-266, Massachusetts Institute of Technology, Cambridge, Mass.

DeJong G. ( 1979) Skimming stories in real time: An experiment in integrated understanding. Doctoral dissertation, Research Rep. #158, Department of Computer Science, Yale University, New Haven.

Gershman A. ( 1979) Knowledge-based parsing. Doctoral dissertation, Research Rep. #156, Computer Science Department, Yale University, New Haven.

Nash-Webber B., & Reiter R. ( 1977) "Anaphora and logical form: On formal meaning representations for natural language". Proc. Fifth International Joint Conference on Artificial Intelligence. Cambridge, Mass.

Riesbeck C., & Charniak E. ( 1978) Micro-SAM and Micro-ELI: Exercises in popular cognitive mechanics (Research Rep. #139). Computer Science Department, Yale University, New Haven.

Riesbeck C., & Schank R. C. ( 1976) Comprehension by computer: Expectation-based analysis of sentences in context (Research Rep. #78). Computer Science Department, Yale University, New Haven. Also, in W. J. M. Levelt & G. B. Flores d'Arcais (Eds.) ( 1979), Studies in the perception of language. Chichester, Eng.: Wiley.

Schank R. C. ( 1979) Reminding and memory organization: An introduction to MOPs (Research Rep. #170); Computer Science Department, Yale University, New Haven.

Schank R., Lebowitz M., & Birnbaum L. ( 1978) Integrated partial parsing (Research Rep. #143). Computer Science Department, Yale University, New Haven.

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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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