Annotation-Based Semantics for Space and Time in Language

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

Kiyong Lee (Author)

9781108839594, Cambridge University Press

Hardback, published 29 June 2023

413 pages
23.5 x 15.8 x 3.5 cm, 0.88 kg

'This is a significant contribution to both formal semantics and computational linguistics, providing a situated and small world-based approach. Its event-driven representation of time and space lays the foundation for elegant formal semantics to facilitate language processing. It offers a valuable end-to-end discussion of the role of semantics annotation – from the minimal linguistic units to the automatic processing of texts. Readers will find it succinct, timely, and expansive in the topics covered.' Chu-Ren Huang, Hong Kong Polytechnic University

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.

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.

Subject Areas: Artificial intelligence [UYQ]