Annotation-Based Semantics for Space and Time in Language (Studies in Natural Language Processing)
Language: English
Published by Cambridge University Press, 2023
- Hardcover
- New

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- Title
- Annotation-Based Semantics for Space and Time in Language (Studies in Natural Language Processing)
- Author
- Lee, Kiyong
- Publisher
- Cambridge University Press
- Publication year
- 2023
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1108839592
- ISBN 13
- 9781108839594
Space and time representation in language is important in linguistics and cognitive science research, as well as artificial intelligence applications like conversational robots and navigation systems. This book is the first for linguists and computer scientists that shows how to do model-theoretic semantics for temporal or spatial information in natural language, based on annotation structures. The book covers the entire cycle of developing a specification for annotation and the implementation of the model over the appropriate corpus for linguistic annotation. Its representation language is a type-theoretic, first-order logic in shallow semantics. Each interpretation model is delimited by a set of definitions of logical predicates used in semantic representations (e.g., past) or measuring expressions (e.g., counts or k). The counting function is then defined as a set and its cardinality, involving a universal quantification in a model. This definition then delineates a set of admissible models for interpretation.
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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.
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