Computing Meaning: Annotation, Representation, and Inference by Harry Bunt, Johan Bos, and Stephen Pulman .- Part I Semantic Representation and Compositionality . Deterministic Statistical Mapping of Sentences to Underspecified Semantics by Hiyan Alshawi, Pi-Chuan Chang, and Michael Ringgaard .- A formal approach to linking logical form and vector-space lexical semantics by Dan Garrette, Katrin Erk, and Raymond Mooney .- Annotations that effectively contribute to semantic interpretation by Harry Bunt .- Concrete Sentence Spaces for Compositional Distributional Models of Meaning by Edward Grefenstette, Mehmoosh Sadrzadeh, Stephen Clark, Bob Coecke, and Stephen Pulman .-  Part II Inference and Understanding . Recognizing Textual Entailment and Computational Semantics by Johan Bos .- Abductive Reasoning with a Large Knowledge Base for Discourse Processing by Ekaterina Ovchinnikova, Niloofar Montazeri, Theodore Alexandrov, Jerry R. Hobbs, Michael C. McCord, and Rutu Mulkar-Mehta .- Natural logic and natural language inference by Bill MacCartney and Christopher D. Manning .- Designing Efficient Controlled Languages for Ontologies by Camilo Thorne, Raffaella Bernardi, and Diego Calvanese .- Part III Semantic Resources and Annotation . A Context-Change Semantics for Dialogue Acts by Harry Bunt .- VerbNet Class Assignment as a WSD Task by Susan Windisch Brown, Dmitriy Dligach and Martha Palmer .- Annotation of Compositional Operations with GLML by Pustejovsky, Rumshisky, Batiukova, and Moszkowicz .- Incremental Recognition and Prediction of Dialogue Acts by Volha Petukhova and Harry Bunt .- Index .

This book is a collection of papers by leading researchers in computational semantics. It presents a state-of-the-art overview of recent and current research in computational semantics, including descriptions of new methods for constructing and improving resources for semantic computation, such as WordNet, VerbNet, and semantically annotated corpora. It also presents new statistical methods in semantic computation, such as the application of distributional semantics in the compositional calculation of sentence meanings.Computing the meaning of sentences, texts, and spoken or texted dialogue is the ultimate challenge in natural language processing, and the key to a wide range of exciting applications. The breadth and depth of coverage of this book makes it suitable as a reference and overview of the state of the field for researchers in Computational Linguistics, Semantics, Computer Science, Cognitive Science, and Artificial Intelligence.

Offers a state-of-the-art overview of computational semantics written by leading researchers in the field Presents the latest developments in methods and tools for the automatic computation of the content of natural language expressions Includes discussions of WordNet, VerbNet, semantically annotated corpora and new methodologies for their construction as well as new statistical methods such as the application of distributional semantics Includes supplementary material: sn.pub/extras