This book is a collection of papers written by outstanding researchers in the newly emerging field of computational semantics. It is aimed at those linguists, computer scientists, and logicians who want to know more about the algorithmic realization of meaning in natural language and about what is happening in this field of research. It includes a general introduction by the editors.

This book provides an in-depth view of the current issues, problems and approaches in the computation of meaning as expressed in language. Aimed at linguists, computer scientists, and logicians with an interest in the computation of meaning, this book focuses on two main topics in recent research in computational semantics. The first topic is the definition and use of underspecified semantic representations, i.e. formal structures that represent part of the meaning of a linguistic object while leaving other parts unspecified. The second topic discussed is semantic annotation. Annotated corpora have become an indispensable resource both for linguists and for developers of language and speech technology, especially when used in combination with machine learning methods. The annotation in corpora has only marginally addressed semantic information, however, since semantic annotation methodologies are still in their infancy. This book discusses the development and application of such methodologies.

A contribution to the emerging discipline of computational semantics, which is concerned with computing the meanings of linguistic objects such as sentences, text fragments, and dialogue. Here researchers offer 17 studies for linguists, computer scientists, and logicians interesting in knowing more about the algorithmic realization of meaning in natural language. The topics include dynamic and underspecified interpretation without dynamic or underspecified logic, minimum description length and compositionality, semantically based ellipsis resolution with syntactic presuppositions, dynamic discourse referents for tense and modals, and a disambiguation approach for German compounds with de-verbal head. Annotation copyrighted by Book News, Inc., Portland, OR

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. ​

This book is a collection of papers written by outstanding researchers in the newly emerging field of computational semantics. It is aimed at those linguists, computer scientists, and logicians who want to know more about the algorithmic realization of meaning in natural language and about what is happening in this field of research. It includes a general introduction by the editors.

This book is a collection of papers written by outstanding researchers in the newly emerging field of computational semantics. Computational semantics is concerned with the computation of the meanings of linguistic objects such as text fragments, spoken dialogue utterances, and e-mail messages. The meaning of such an object is determined partly by linguistic information and partly by information from the context in which the object occurs. The information from these sources is combined by processes that infer which interpretation of the object applies in the given context. This applies not only to notoriously difficult aspects of interpreting linguistic objects, such as indexicals, anaphora, and metonymy, but also to establishing the precise reference of common nouns and the scopes of noun phrases. The central issue in computational semantics is how processes of finding and combining the relevant linguistic and contextual information into contextually appropriate meanings can be organised. Traditional approaches of applying context information to disambiguated natural language expressions do not work well, due to the massive ambiguity in natural language. Recent work in computational semantics suggests, alternatively, to represent linguistic semantic information in formal structures with underspecification, and to apply context information in inference processes that result in further specification of these representations. Underspecified representation and inference are therefore the key topics in this book. The book is aimed at those linguists, computer scientists, and logicians who take an interest in the computation of meaning, and who want to know what is happening in this exciting field of research.

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. ​