Overview

This book assesses the place of logic, mathematics, and computer science in present day, interdisciplinary areas of computational linguistics. Computational linguistics studies natural language in its various manifestations from a computational point of view, both on the theoretical level (modeling grammar modules dealing with natural language form and meaning and the relation between these two) and on the practical level (developing applications for language and speech technology). It is a collection of chapters presenting new and future research. The book focuses mainly on logical approaches to computational processing of natural language and on the applicability of methods and techniques from the study of formal languages, programming, and other specification languages. It presents work from other approaches to linguistics, as well, especially because they inspire new work and approaches.

Full Product Details

Author:   Roussanka Loukanova ,  Peter LeFanu Lumsdaine ,  Reinhard Muskens
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2023
Volume:   1081
ISBN:  

9783031217821

ISBN 10:   3031217829
Pages:   347
Publication Date:   13 March 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Complexity of the Lambek Calculus and Its Extensions.- Categorial Dependency Grammars: Analysis and Learning.- Diamonds are Forever.- A Hybrid Approach of Distributional Semantics and Event Semantics for Telicity.- Generalized Computable Models and Montague Semantics.- Multilingual Text Generation for Abstract Wikipedia in Grammatical Framework: Prospects and Challenges.- Decomposing Events into GOLOG.- Generating Pragmatically Appropriate Sentences from Logic: the Case of the Conditional and Biconditional.- White Roses, Red Backgrounds: Bringing Structured Representations to Search.- Rules Are Rules: Rhetorical Figures and Algorithms.- Integrating Deep Neural Networks with Dependent Type Semantics.- Meaning-Driven Selectional Restrictions.- A Unified Cluster of Valence Resources.

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