Model Generation for Natural Language Interpretation and Analysis

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Mathematical theorem proving has undergone an impressive development during the last two decades, resulting in a variety of powerful systems for applications in mathematical deduction and knowledge processing. Natural language processing has become a topic of outstanding relevance in information technology, mainly due to the explosive growth of the Web, where by far the largest part of information is encoded in natural language documents.

This monograph focuses on the development of inference tools tailored to applications in natural language processing by demonstrating how the model generation paradigm can be used as a framework for the support of specific tasks in natural language interpretation and natural language based inference in a natural way.

The book appears at a pivotal moment, when much attention is being paid to the task of adding a semantic layer to the Web, and representation and processing of natural language based semantic information pops up as a primary requirement for further technological progress.

Author(s): Karsten Konrad (auth.)
Series: Lecture Notes in Computer Science 2953 : Lecture Notes in Artificial Intelligence
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2004

Language: English
Pages: 174
Tags: Artificial Intelligence (incl. Robotics); Computer Science, general; Mathematical Logic and Formal Languages; Document Preparation and Text Processing; Language Translation and Linguistics

Front Matter....Pages -
1 Motivation....Pages 1-6
Front Matter....Pages 7-7
2 Model Generation....Pages 9-23
3 Higher-Order Model Generation....Pages 25-53
4 Minimal Model Generation....Pages 55-56
Front Matter....Pages 57-57
5 The Analysis of Definites....Pages 59-78
6 Reciprocity....Pages 79-103
7 Abduction....Pages 105-123
8 Implementation....Pages 125-147
9 Conclusion....Pages 149-153
A Some Example Problems....Pages 155-158
References and Index....Pages 159-165
Back Matter....Pages -