Lexical ambiguity is one of the most intractable problems facing language processing studies and, not surprisingly, it is at the core of research in lexical semantics. The papers in this collection constitute not just a set of diverse yet related articles in this core area of research, but rather make up a unique collection of work on the relationship between logical polysemy, sense extension, and discourse structure. Each paper addresses the following questions: what is the representation of a lexical item such that it may assume different senses? What is it about the representation of a lexical item that gives rise to sense extensions and to the phenomenon of logical polysemy? Three major subthemes run through the papers: the role of pragmatics and discourse in lexical disambiguation; the analysis of logical polysemy as a compositional process; and the treament of sense extension and referential transfer phenomena.

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.

This book explains how to build Natural Language Generation (NLG) systems - computer software systems which use techniques from artificial intelligence and computational linguistics to automatically generate understandable texts in English or other human languages, either in isolation or as part of multimedia documents, Web pages, and speech output systems. Typically starting from some non-linguistic representation of information as input, NLG systems use knowledge about language and the application domain to automatically produce documents, reports, explanations, help messages, and other kinds of texts. The book covers the algorithms and representations needed to perform the core tasks of document planning, microplanning, and surface realization, using a case study to show how these components fit together. It also discusses engineering issues such as system architecture, requirements analysis, and the integration of text generation into multimedia and speech output systems.

Semantic interpretation and the resolution of ambiguity presents an important advance in computer understanding of natural language. While parsing techniques have been greatly improved in recent years, the approach to semantics has generally improved in recent years, the approach to semantics has generally been ad hoc and had little theoretical basis. Graeme Hirst offers a new, theoretically motivated foundation for conceptual analysis by computer, and shows how this framework facilitates the resolution of lexical and syntactic ambiguities. His approach is interdisciplinary, drawing on research in computational linguistics, artificial intelligence, montague semantics, and cognitive psychology.

This book is concerned with the machine-based generation of natural language text and presents a formal analysis of problems, which in the main have previously only been approached descriptively. In the process of producing discourse, speakers and writers must decide what it is that they want to say and how to present it effectively. Kathleen McKeown's main concern is to identify and formalise principles of discourse so that they can be used in a computational process. The text generation theory she describes has been embodied in a computer program, TEXT, which, given a question, can produce a paragraph length response. An Appendix to the book provides examples of the TEXT system in operation.

Lexical ambiguity is one of the most intractable problems facing language processing studies and, not surprisingly, it is at the core of research in lexical semantics. The papers in this collection constitute not just a set of diverse yet related articles in this core area of research, but rather make up a unique collection of work on the relationship between logical polysemy, sense extension, and discourse structure. Each paper addresses the following questions: what is the representation of a lexical item such that it may assume different senses? What is it about the representation of a lexical item that gives rise to sense extensions and to the phenomenon of logical polysemy? Three major subthemes run through the papers: the role of pragmatics and discourse in lexical disambiguation; the analysis of logical polysemy as a compositional process; and the treament of sense extension and referential transfer phenomena.

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.

This book explains how to build Natural Language Generation (NLG) systems - computer software systems which use techniques from artificial intelligence and computational linguistics to automatically generate understandable texts in English or other human languages, either in isolation or as part of multimedia documents, Web pages, and speech output systems. Typically starting from some non-linguistic representation of information as input, NLG systems use knowledge about language and the application domain to automatically produce documents, reports, explanations, help messages, and other kinds of texts. The book covers the algorithms and representations needed to perform the core tasks of document planning, microplanning, and surface realization, using a case study to show how these components fit together. It also discusses engineering issues such as system architecture, requirements analysis, and the integration of text generation into multimedia and speech output systems.

Semantic interpretation and the resolution of ambiguity presents an important advance in computer understanding of natural language. While parsing techniques have been greatly improved in recent years, the approach to semantics has generally improved in recent years, the approach to semantics has generally been ad hoc and had little theoretical basis. Graeme Hirst offers a new, theoretically motivated foundation for conceptual analysis by computer, and shows how this framework facilitates the resolution of lexical and syntactic ambiguities. His approach is interdisciplinary, drawing on research in computational linguistics, artificial intelligence, montague semantics, and cognitive psychology.

This book is concerned with the machine-based generation of natural language text and presents a formal analysis of problems, which in the main have previously only been approached descriptively. In the process of producing discourse, speakers and writers must decide what it is that they want to say and how to present it effectively. Kathleen McKeown's main concern is to identify and formalise principles of discourse so that they can be used in a computational process. The text generation theory she describes has been embodied in a computer program, TEXT, which, given a question, can produce a paragraph length response. An Appendix to the book provides examples of the TEXT system in operation.