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Integration of World Knowledge for Natural Language Understanding

  • Book
  • © 2012

Overview

Authors:
  1. Ekaterina Ovchinnikova

    1. University of Osnabrück, Bremen, Germany

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  • The detailed introduction to computational natural language understanding (NLU) helps the reader to obtain background knowledge necessary to perform practical NLU
  • The chapter on knowledge base construction shows how to obtain structured knowledge applicable to practical NLU from existing freely available knowledge resources
  • Includes a new algorithm for debugging inconsistent ontologies and a new methodology for ensuring conceptual consistency
  • Shows how heterogeneous knowledge can be employed in one single reasoning pipeline
  • Suggests practical application scenarios of the proposed approach
  • Includes supplementary material: sn.pub/extras

Part of the book series: Atlantis Thinking Machines (ATLANTISTM, volume 3)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Preliminaries

    • Ekaterina Ovchinnikova
    Pages 1-14

  3. Natural Language Understanding and World Knowledge

    • Ekaterina Ovchinnikova
    Pages 15-37

  4. Sources of World Knowledge

    • Ekaterina Ovchinnikova
    Pages 39-71

  5. Reasoning for Natural Language Understanding

    • Ekaterina Ovchinnikova
    Pages 73-92

  6. Knowledge Base Construction

    • Ekaterina Ovchinnikova
    Pages 93-122

  7. Ensuring Consistency

    • Ekaterina Ovchinnikova
    Pages 123-154

  8. Abductive Reasoning with the Integrative Knowledge Base

    • Ekaterina Ovchinnikova
    Pages 155-175

  9. Evaluation

    • Ekaterina Ovchinnikova
    Pages 177-214

  10. Conclusion

    • Ekaterina Ovchinnikova
    Pages 215-220

  11. Back Matter

    Pages 221-242
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Keywords

About this book

This book concerns non-linguistic knowledge required to perform computational natural language understanding (NLU). The main objective of the book is to show that inference-based NLU has the potential for practical large scale applications. First, an introduction to research areas relevant for NLU is given. We review approaches to linguistic meaning, explore knowledge resources, describe semantic parsers, and compare two main forms of inference: deduction and abduction. In the main part of the book, we propose an integrative knowledge base combining lexical-semantic, ontological, and distributional knowledge. A particular attention is payed to ensuring its consistency. We then design a reasoning procedure able to make use of the large scale knowledge base. We experiment both with a deduction-based NLU system and with an abductive reasoner. For evaluation, we use three different NLU tasks: recognizing textual entailment, semantic role labeling, and interpretation of noun dependencies.

Authors and Affiliations

  • University of Osnabrück, Bremen, Germany

    Ekaterina Ovchinnikova

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