Linguistic Linked Data

Linguistic Linked Data

Author: Philipp Cimiano

Publisher: Springer Nature

Published: 2020-01-13

Total Pages: 286

ISBN-13: 3030302253

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This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.


Linked Data in Linguistics

Linked Data in Linguistics

Author: Christian Chiarcos

Publisher: Springer Science & Business Media

Published: 2012-02-21

Total Pages: 220

ISBN-13: 3642282490

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The explosion of information technology has led to substantial growth of web-accessible linguistic data in terms of quantity, diversity and complexity. These resources become even more useful when interlinked with each other to generate network effects. The general trend of providing data online is thus accompanied by newly developing methodologies to interconnect linguistic data and metadata. This includes linguistic data collections, general-purpose knowledge bases (e.g., the DBpedia, a machine-readable edition of the Wikipedia), and repositories with specific information about languages, linguistic categories and phenomena. The Linked Data paradigm provides a framework for interoperability and access management, and thereby allows to integrate information from such a diverse set of resources. The contributions assembled in this volume illustrate the band-width of applications of the Linked Data paradigm for representative types of language resources. They cover lexical-semantic resources, annotated corpora, typological databases as well as terminology and metadata repositories. The book includes representative applications from diverse fields, ranging from academic linguistics (e.g., typology and corpus linguistics) over applied linguistics (e.g., lexicography and translation studies) to technical applications (in computational linguistics, Natural Language Processing and information technology). This volume accompanies the Workshop on Linked Data in Linguistics 2012 (LDL-2012) in Frankfurt/M., Germany, organized by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation (OKFN). It assembles contributions of the workshop participants and, beyond this, it summarizes initial steps in the formation of a Linked Open Data cloud of linguistic resources, the Linguistic Linked Open Data cloud (LLOD).


Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

Author: Antonio Pareja-Lora

Publisher: MIT Press

Published: 2020-01-07

Total Pages: 273

ISBN-13: 0262536250

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Making diverse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making diverse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and diverse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. Contributors Isabelle Barrière, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zinn


Analyzing Linguistic Data

Analyzing Linguistic Data

Author: R. H. Baayen

Publisher: Cambridge University Press

Published: 2008-03-06

Total Pages: 40

ISBN-13: 1139470736

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Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.


Linguistic Ethnography

Linguistic Ethnography

Author: Fiona Copland

Publisher: SAGE

Published: 2015-01-22

Total Pages: 307

ISBN-13: 147391115X

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This is an engaging interdisciplinary guide to the unique role of language within ethnography. The book provides a philosophical overview of the field alongside practical support for designing and developing your own ethnographic research. It demonstrates how to build and develop arguments and engages with practical issues such as ethics, transcription and impact. There are chapter-long case studies based on real research that will explain key themes and help you create and analyse your own linguistic data. Drawing on the authors’ experience they outline the practical, epistemological and theoretical decisions that researchers must take when planning and carrying out their studies. Other key features include: A clear introduction to discourse analytic traditions Tips on how to produce effective field notes Guidance on how to manage interview and conversational data Advice on writing linguistic ethnographies for different audiences Annotated suggestions for further reading Full glossary This book is a master class in understanding linguistic ethnography, it will of interest to anyone conducting field research across the social sciences.


The Atlas of Pidgin and Creole Language Structures

The Atlas of Pidgin and Creole Language Structures

Author: Susanne Maria Michaelis

Publisher: Oxford University Press, USA

Published: 2013-09-05

Total Pages: 572

ISBN-13: 0199691398

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The Atlas presents commentaries and colour maps showing how 130 linguistic features - phonological, syntactic, morphological, and lexical - are distributed among the world's pidgins and creoles. Designed and written by the world's leading experts, it is a unique resource of outstanding value for linguists of all persuasions throughout the world.


Linguistic Fieldwork

Linguistic Fieldwork

Author: Jeanette Sakel

Publisher: Cambridge University Press

Published: 2012-02-02

Total Pages: 193

ISBN-13: 0521837278

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A handy beginner's guide to linguistic fieldwork - from the preparation of the work to the presentation of the results.


Classification and Modeling with Linguistic Information Granules

Classification and Modeling with Linguistic Information Granules

Author: Hisao Ishibuchi

Publisher: Springer Science & Business Media

Published: 2006-02-27

Total Pages: 308

ISBN-13: 3540268758

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Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and model ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.


Developing Linguistic Corpora

Developing Linguistic Corpora

Author: Martin Wynne

Publisher: Oxbow Books Limited

Published: 2005

Total Pages: 100

ISBN-13:

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A linguistic corpus is a collection of texts which have been selected and brought together so that language can be studied on the computer. Today, corpus linguistics offers some of the most powerful new procedures for the analysis of language, and the impact of this dynamic and expanding sub-discipline is making itself felt in many areas of language study. In this volume, a selection of leading experts in various key areas of corpus construction offer advice in a readable and largely non-technical style to help the reader to ensure that their corpus is well designed and fit for the intended purpose. This guide is aimed at those who are at some stage of building a linguistic corpus. Little or no knowledge of corpus linguistics or computational procedures is assumed, although it is hoped that more advanced users will find the guidelines here useful. It is also aimed at those who are not building a corpus, but who need to know something about the issues involved in the design of corpora in order to choose between available resources and to help draw conclusions from their studies.