Fr. 210.00

Annotation-Based Semantics for Space and Time in Language

English · Hardback

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Description

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"Aimed at linguists and computer scientists working on natural language processing, this is the first book that shows, at a large scale, how to do semantics for spatio-temporal information based on annotation structures that conform to ISO international standards such as ISO-TimeML or ISO-Space"--

List of contents










Foreword; Preface; Acknowledgments; Part I. Fundamentals: 1. What is a semantic annotation?; 2. Data segmentation; 3. Modeling a semantic annotation scheme; 4. Representation and serialization; 5. What does semantics do for annotation?; 6. Annotation-based semantics; Part II. Time and Events: 7. Temporal ontology; 8. Normalizing TimeML with some modifications; 9. Extending the range of temporal annotation; 10. Proper interpretation of temporal relators; Part III. Motion Space, and Time: 11. ISO-Space evolving from SpatialML; 12. Dynamic paths, projection, and orientation; 13. Toward a dynamic annotation scheme.

About the author

Kiyong Lee is Professor Emeritus of Linguistics at Korea University in Seoul. He was President of the Linguistic Society of Korea and the Korean Society for Cognitive Science, and has worked on creating standards for semantic annotation as an ISO working group Convenor and Project Leader. In 1974, he published his University of Texas at Austin dissertation, On Montague Grammar. His published works include Computational Morphology and a three-volume book, Language and the World: Formal Semantics; Tense and Modality: Possible-Worlds Semantics; and Situation and Information: Situation Semantics.

Summary

Aimed at linguists and computer scientists working on natural language processing, this is the first book that shows, at a large scale, how to do semantics for spatio-temporal information based on annotation structures that conform to ISO international standards such as ISO-TimeML or ISO-Space.

Foreword

This book develops natural language semantics for spatio-temporal information based on annotation structures rather than syntax.

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