Computing Meaning Volume 4 [Paperback]

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. 

Computing Meaning: Annotation, Representation, and Inference by Harry Bunt, Johan Bos, and Stephen Pulman . 1 Introduction . 2 About this book . 2.1 Semantic Representation and Compositionality . 2.2 Inference and Understanding . 2.3 Semantic Resources and Annotation . References .- Part I Semantic Representation and Compositionality . Deterministic Statistical Mapping of Sentences to Underspecified Semantics by Hiyan Alshawi, Pi-Chuan Chang, and Michael Ringgaard . 1 Introduction . 2 Direct Semantic Mapping . 3 Semantic Expressions . 3.1 Connectives and Examples . 4 Encoding Semantics as Dependencies . 4.1 Alignment .? 4.2 Headedness . 4.3 Label Construction . 5 Experiments . 5.1 Data Preparation . 5.2 Parser . 5.3 Results . 6 Conclusion and Further Work . References .- A formal approach to linking logical form and vector-space lexical semantics by Dan Garrette, Katrin Erk, and Raymond Mooney . 1 Introduction . 2 Background . 3 Linking logical form and vector spaces . 4 Transforming natural language text to logical form lc&