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Representation and Inference for Natural Language: A First Course in Computational Semantics

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This book developed out of courses on computational semantics that the authors jointly taught at the Department of Computational Linguistics, University of the Saarland, Saarbrucken, Germany, in 1995 and 1998, and at ESSLLI'97, the 9th European Summer School in Logic, Language and Information, Aix-en-Provence, France, in August 1997. When designing these courses, we found no single source containing all the material we wanted to present. At that time, the only notes exclusively devoted to computational semantics that we knew of were Cooper ct al. (1993), probably the first systematic introduction to modern computational semantics. Like the present book, these notes are Prolog based, and cover some of the same ground, often using interestingly different tools and techniques. However we wanted to teach the subject in a way that emphasized inference, underspecification, and grammar engineering and architectural issues. By the end of the 1990s we had a first version of the book, influenced by Pereira and Shieber (1987) and Johnson and Kay (1990) for semantic construction, and Fitting (1996) for inference, which partially realised these goals.

How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.
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