Ebook: Knowledge Representation and the Semantics of Natural Language

Natural Language is not only the most important means of communication between human beings, it is also used over historical periods for the pres- vation of cultural achievements and their transmission from one generation to the other. During the last few decades, the ?ood of digitalized information has been growing tremendously. This tendency will continue with the globali- tion of information societies and with the growing importance of national and international computer networks. This is one reason why the theoretical und- standing and the automated treatment of communication processes based on natural language have such a decisive social and economic impact. In this c- text, the semantic representation of knowledge originally formulated in natural language plays a central part, because it connects all components of natural language processing systems, be they the automatic understanding of natural language (analysis), the rational reasoning over knowledge bases, or the g- eration of natural language expressions from formal representations. This book presents a method for the semantic representation of natural l- guage expressions (texts, sentences, phrases, etc. ) which can be used as a u- versal knowledge representation paradigm in the human sciences, like lingu- tics, cognitive psychology, or philosophy of language, as well as in com- tational linguistics and in arti?cial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.

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The book presents an interdisciplinary approach to knowledge representation and the treatment of semantic phenomena of natural language, which is positioned between artificial intelligence, computational linguistics, and cognitive psychology. The proposed method is based on Multilayered Extended Semantic Networks (MultiNets), which can be used for theoretical investigations into the semantics of natural language, for cognitive modeling, for describing lexical entries in a computational lexicon, and for natural language processing (NLP).

Part I deals with fundamental problems of semantic knowledge representation and semantic interpretation of natural language phenomena. Part II provides a systematic description of the representational means of MultiNet, one of the most comprehensive and thoroughly specified collections of relations and functions used in real NLP applications.

MultiNet is embedded into a system of software tools comprising a workbench for the knowledge engineer, a semantic interpreter translating natural language expressions into formal meaning structures, and a workbench for the computer lexicographer. The book has been used for courses in artificial intelligence at several universities and is one of the cornerstones for teaching computational linguistics in a virtual electronic laboratory.

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The book presents an interdisciplinary approach to knowledge representation and the treatment of semantic phenomena of natural language, which is positioned between artificial intelligence, computational linguistics, and cognitive psychology. The proposed method is based on Multilayered Extended Semantic Networks (MultiNets), which can be used for theoretical investigations into the semantics of natural language, for cognitive modeling, for describing lexical entries in a computational lexicon, and for natural language processing (NLP).

Part I deals with fundamental problems of semantic knowledge representation and semantic interpretation of natural language phenomena. Part II provides a systematic description of the representational means of MultiNet, one of the most comprehensive and thoroughly specified collections of relations and functions used in real NLP applications.

MultiNet is embedded into a system of software tools comprising a workbench for the knowledge engineer, a semantic interpreter translating natural language expressions into formal meaning structures, and a workbench for the computer lexicographer. The book has been used for courses in artificial intelligence at several universities and is one of the cornerstones for teaching computational linguistics in a virtual electronic laboratory.

Content:
Front Matter....Pages I-XVIII
Introduction....Pages 1-11
Historical Roots....Pages 13-16
Basic Concepts....Pages 17-43
Semantic Characterization of Objects....Pages 45-83
Semantic Characterization of Situations....Pages 85-111
The Comparison of Entities....Pages 113-130
The Spatio-temporal Characterization of Entities....Pages 131-162
Modality and Negation....Pages 163-196
Quantification and Pluralities....Pages 197-217
The Role of Layer Information in Semantic Representations....Pages 219-231
Relations Between Situations....Pages 233-277
Lexicon and Knowledge Representation....Pages 279-303
Question Answering and Inferences....Pages 305-330
Software Tools for the Knowledge Engineer and Sample Applications....Pages 331-356
Comparison Between MultiNet and Other Semantic Formalisms or Knowledge Representation Paradigms....Pages 357-391
Overview and Representational Principles....Pages 395-407
Means for Expressing Classification and Stratification....Pages 409-438
Relational and Functional Means of Representation....Pages 439-591
Back Matter....Pages 593-647

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The book presents an interdisciplinary approach to knowledge representation and the treatment of semantic phenomena of natural language, which is positioned between artificial intelligence, computational linguistics, and cognitive psychology. The proposed method is based on Multilayered Extended Semantic Networks (MultiNets), which can be used for theoretical investigations into the semantics of natural language, for cognitive modeling, for describing lexical entries in a computational lexicon, and for natural language processing (NLP).

Part I deals with fundamental problems of semantic knowledge representation and semantic interpretation of natural language phenomena. Part II provides a systematic description of the representational means of MultiNet, one of the most comprehensive and thoroughly specified collections of relations and functions used in real NLP applications.

MultiNet is embedded into a system of software tools comprising a workbench for the knowledge engineer, a semantic interpreter translating natural language expressions into formal meaning structures, and a workbench for the computer lexicographer. The book has been used for courses in artificial intelligence at several universities and is one of the cornerstones for teaching computational linguistics in a virtual electronic laboratory.

Content:
Front Matter....Pages I-XVIII
Introduction....Pages 1-11
Historical Roots....Pages 13-16
Basic Concepts....Pages 17-43
Semantic Characterization of Objects....Pages 45-83
Semantic Characterization of Situations....Pages 85-111
The Comparison of Entities....Pages 113-130
The Spatio-temporal Characterization of Entities....Pages 131-162
Modality and Negation....Pages 163-196
Quantification and Pluralities....Pages 197-217
The Role of Layer Information in Semantic Representations....Pages 219-231
Relations Between Situations....Pages 233-277
Lexicon and Knowledge Representation....Pages 279-303
Question Answering and Inferences....Pages 305-330
Software Tools for the Knowledge Engineer and Sample Applications....Pages 331-356
Comparison Between MultiNet and Other Semantic Formalisms or Knowledge Representation Paradigms....Pages 357-391
Overview and Representational Principles....Pages 395-407
Means for Expressing Classification and Stratification....Pages 409-438
Relational and Functional Means of Representation....Pages 439-591
Back Matter....Pages 593-647
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