Introduction To Linguistic Annotation And Text Analytics

Overview

Linguistic annotation and text analytics are areas of active research and development, with regular academic conferences such as the Linguistic Annotation Workshops and industry events such as the annual Text Analytics Summits. This book provides a basic introduction to both fields, and aims to show that good linguistic annotations are the essential foundation for good text analytics. After briefly reviewing the basics of XML, with practical exercises showing the difference between in-line and stand-off ...
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Overview

Linguistic annotation and text analytics are areas of active research and development, with regular academic conferences such as the Linguistic Annotation Workshops and industry events such as the annual Text Analytics Summits. This book provides a basic introduction to both fields, and aims to show that good linguistic annotations are the essential foundation for good text analytics. After briefly reviewing the basics of XML, with practical exercises showing the difference between in-line and stand-off annotations, a chapter is devoted to explaining the different levels of linguistic annotations. The reader is encouraged to create example annotations using the WordFreak linguistic annotation tool. The next chapter shows how annotations can be created automatically using statistical NLP tools, and compares two sets of tools, the OpenNLP and Stanford NLP tools. The second half of the book describes different annotation formats and gives practical examples of how to interchange annotations between different formats using XSLT transformations. The two main text analytics architectures, GATE and UIMA, are then described and compared, with practical exercises showing how to configure and customize them. The final chapter is an introduction to text analytics, describing the main applications and functions including named entity recognition, coreference resolution and information extraction, with practical examples using both open source and commercial tools.
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Product Details

Table of Contents

1 Working with XML 1

2 Linguistic annotation 19

3 Using statistical NLP tools 45

4 Annotation interchange 63

5 Annotation architectures 95

6 Text analytics 119

Bibliography 147

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