Semantic Structures

Semantic Structures is a large-scale study of conceptual structure and its lexical and syntactic expression in English that builds on the system of Conceptual Semantics described in Ray Jackendoff's earlier books Semantics and Cognition and Consciousness and the Computational Mind. Jackendoff summarizes the relevant arguments in his two previous books, setting out the basic parameters for the formalization of meaning, and comparing his mentalistic approach with Fodor's Language of Thought hypothesis. He then takes up the Problem of Meaning, extending the range of semantic fields encompassed by the Conceptual Semantics formalism, and the Problem of Correspondence, formalizing the relation between semantic and syntactic structure. Both of these problems must be fully addressed in order to develop a general theory of language that is concerned with syntax and semantics and their points of connection. Few books on lexical semantics present such a comprehensive analysis of such a wide range of phenomena from a unified perspective. Besides discussing the conceptual structures of hundreds of words and constructions, Jackendoff extends and deepens the theory to come to grips with such crucial issues as roles and marking; arguments, modifiers, and adjuncts; binding and control; and the thematic linking hierarchy.

This book explores the cognitive constraints and principles of variation in structures of linguistic meaning across languages. It unifies cognitive-semantic representations with formal-semantic representations to make a unique contribution to the study of typological generalizations and universals in natural language semantics. This unified approach not only helps reveal why semantic structures have the observed variation they have but also sheds light on the compelling cognitive and formal regularities and patterns in the variation of linguistic semantics. The book also advances the general principles of a cognitively oriented semantic typology. Lucid and topical, the book will be an indispensable resource for students and researchers of language typology, linguistics, cognitive linguistics and semantics. It will also be of interest to theoretical linguists of both cognitivist and formalist schools.

Natural language understanding is central to the goals of artificial intelligence. Any truly intelligent machine must be capable of carrying on a conversation: dialogue, particularly clarification dialogue, is essential if we are to avoid disasters caused by the misunderstanding of the intelligent interactive systems of the future. This book is an interim report on the grand enterprise of devising a machine that can use natural language as fluently as a human. What has really been achieved since this goal was first formulated in Turing’s famous test? What obstacles still need to be overcome?

Syntax puts our meaning (“semantics”) into sentences, and phonology puts the sentences into the sounds that we hear and there must, surely, be a structure in the meaning that is expressed in the syntax and phonology. Some writers use the phrase “semantic structure”, but are referring to conceptual structure; since we can express our conceptual thought in many different linguistic ways, we cannot equate conceptual and semantic structures. The research reported in this book shows semantic structure to be in part hierarchic, fitting the syntax in which it is expressed, and partly a network, fitting the nature of the mind, from which it springs. It is complex enough to provide for the emotive and imaginative dimensions of language, and for shifts of standard meanings in context, and the “rules” that control them. Showing the full structure of English semantics requires attention to many currently topical issues, and since the underlying theory is fresh, there are fresh implications for them. The most important of those issues is information structure, which is given full treatment, showing its overall structure, and its relation to semantics and the whole grammar of English.

An introduction to the central topics of linguistic semantics and the philosophy of language, assuming no special knowledge of philosophy or logic.

After years of mostly theoretical research, Semantic Web Technologies are now reaching out into application areas like bioinformatics, eCommerce, eGovernment, or Social Webs. Applications like genomic ontologies, semantic web services, automated catalogue alignment, ontology matching, or blogs and social networks are constantly increasing, often driven or at least backed up by companies like Google, Amazon, YouTube, Facebook, LinkedIn and others. The need to leverage the potential of combining information in a meaningful way in order to be able to benefit from the Web will create further demand for and interest in Semantic Web research. This movement, based on the growing maturity of related research results, necessitates a reliable reference source from which beginners to the field can draw a first basic knowledge of the main underlying technologies as well as state-of-the-art application areas. This handbook, put together by three leading authorities in the field, and supported by an advisory board of highly reputed researchers, fulfils exactly this need. It is the first dedicated reference work in this field, collecting contributions about both the technical foundations of the Semantic Web as well as their main usage in other scientific fields like life sciences, engineering, business, or education.