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This book aims to look at the semantics of natural languages in context.
A primary problem in the area of natural language processing has been that of semantic analysis. This book aims to look at the semantics of natural languages in context. It presents an approach to the computational processing of English text that combines current theories of knowledge representation and reasoning in Artificial Intelligence with the latest linguistic views of lexical semantics. This results in distinct advantages for relating the semantic analysis of a sentence to its context. A key feature is the clear separation of the lexical entries that represent the domain-specific linguistic information from the semantic interpreter that performs the analysis. The criteria for defining the lexical entries are firmly grounded in current linguistic theories, facilitating integration with existing parsers. This approach has been implemented and tested in Prolog on a domain for physics word problems and full details of the algorithms and code are presented. Semantic Processing for Finite Domains will appeal to postgraduates and researchers in computational linguistics, and to industrial groups specializing in natural language processing.
Table of contents:
List of figures; Acknowledgements; 1. Problems in semantic analysis of text; 2. Previous computational approaches to semantic analysis; 3. A domain formalization; 4. Inference-driven mapping; 5. Results of inference-driven semantic analysis; Appendices; References.
A primary problem in the area of natural language processing has been that of semantic analysis. This book aims to look at the semantics of natural languages in context. It presents an approach to the computational processing of English text that combines current theories of knowledge representation and reasoning in Artificial Intelligence with the latest linguistic views of lexical semantics. This results in distinct advantages for relating the semantic analysis of a sentence to its context. A key feature is the clear separation of the lexical entries that represent the domain-specific linguistic information from the semantic interpreter that performs the analysis. The criteria for defining the lexical entries are firmly grounded in current linguistic theories, facilitating integration with existing parsers. This approach has been implemented and tested in Prolog on a domain for physics word problems and full details of the algorithms and code are presented. Semantic Processing for Finite Domains will appeal to postgraduates and researchers in computational linguistics, and to industrial groups specializing in natural language processing.
Table of contents:
List of figures; Acknowledgements; 1. Problems in semantic analysis of text; 2. Previous computational approaches to semantic analysis; 3. A domain formalization; 4. Inference-driven mapping; 5. Results of inference-driven semantic analysis; Appendices; References.