Handbook Of Linguistic Annotation

This handbook offers a thorough treatment of the science of linguistic annotation. Leaders in the field guide the reader through the process of modeling, creating an annotation language, building a corpus and evaluating it for correctness. Essential reading for both computer scientists and linguistic researchers.Linguistic annotation is an increasingly important activity in the field of computational linguistics because of its critical role in the development of language models for natural language processing applications. Part one of this book covers all phases of the linguistic annotation process, from annotation scheme design and choice of representation format through both the manual and automatic annotation process, evaluation, and iterative improvement of annotation accuracy. The second part of the book includes case studies of annotation projects across the spectrum of linguistic annotation types, including morpho-syntactic tagging, syntactic analyses, a range of semantic analyses (semantic roles, named entities, sentiment and opinion), time and event and spatial analyses, and discourse level analyses including discourse structure, co-reference, etc. Each case study addresses the various phases and processes discussed in the chapters of part one.

This handbook offers a thorough treatment of the science of linguistic annotation. Leaders in the field guide the reader through the process of modeling, creating an annotation language, building a corpus and evaluating it for correctness. Essential reading for both computer scientists and linguistic researchers.Linguistic annotation is an increasingly important activity in the field of computational linguistics because of its critical role in the development of language models for natural language processing applications. Part one of this book covers all phases of the linguistic annotation process, from annotation scheme design and choice of representation format through both the manual and automatic annotation process, evaluation, and iterative improvement of annotation accuracy. The second part of the book includes case studies of annotation projects across the spectrum of linguistic annotation types, including morpho-syntactic tagging, syntactic analyses, a range of semantic analyses (semantic roles, named entities, sentiment and opinion), time and event and spatial analyses, and discourse level analyses including discourse structure, co-reference, etc. Each case study addresses the various phases and processes discussed in the chapters of part one.

This book addresses the research, analysis, and description of the methods and processes that are used in the annotation and processing of language corpora in advanced, semi-advanced, and non-advanced languages. It provides the background information and empirical data needed to understand the nature and depth of problems related to corpus annotation and text processing and shows readers how the linguistic elements found in texts are analyzed and applied to develop language technology systems and devices. As such, it offers valuable insights for researchers, educators, and students of linguistics and language technology.

A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. "Doing language science" depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice. In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involved in data management. Part 2 presents snapshots of practices across various subfields, with each chapter presenting a unique data management project with generalizable guidance for researchers. The Open Handbook of Linguistic Data Management is an essential addition to the toolkit of every linguist, guiding researchers toward making their data FAIR: Findable, Accessible, Interoperable, and Reusable.

Includes bibliographical references (p. 305-315) and index.

A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. "Doing language science" depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice. In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involved in data management. Part 2 presents snapshots of practices across various subfields, with each chapter presenting a unique data management project with generalizable guidance for researchers. The Open Handbook of Linguistic Data Management is an essential addition to the toolkit of every linguist, guiding researchers toward making their data FAIR: Findable, Accessible, Interoperable, and Reusable.

This handbook is a comprehensive practical resource on corpus linguistics. It features a range of basic and advanced approaches, methods and techniques in corpus linguistics, from corpus compilation principles to quantitative data analyses. The Handbook is organized in six Parts. Parts I to III feature chapters that discuss key issues and the know-how related to various topics around corpus design, methods and corpus types. Parts IV-V aim to offer a user-friendly introduction to the quantitative analysis of corpus data: for each statistical technique discussed, chapters provide a practical guide with R and come with supplementary online material. Part VI focuses on how to write a corpus linguistic paper and how to meta-analyze corpus linguistic research. The volume can serve as a course book as well as for individual study. It will be an essential reading for students of corpus linguistics as well as experienced researchers who want to expand their knowledge of the field.

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