Integration of World Knowledge for Natural Language Understanding

Front Cover
Springer Science & Business Media, Feb 15, 2012 - Computers - 242 pages
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.
 

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Contents

1 Preliminaries
1
2 Natural Language U nderstanding andWorld Knowledge
15
3 Sources of World Knowledge
39
4 Reasoning for Natural Language Understanding
73
5 Knowledge Base Construction
93
6 Ensuring Consistency
123
7 Abductive Reasoning with the Integrative Knowledge Base
155
8 Evaluation
177
9 Conclusion
215
Appendix A
221
Bibliography
225
Index
240
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