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Natural Language Processing with Java

You're reading from   Natural Language Processing with Java Techniques for building machine learning and neural network models for NLP

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788993494
Length 318 pages
Edition 2nd Edition
Languages
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
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Table of Contents (14) Chapters Close

Preface 1. Introduction to NLP FREE CHAPTER 2. Finding Parts of Text 3. Finding Sentences 4. Finding People and Things 5. Detecting Part of Speech 6. Representing Text with Features 7. Information Retrieval 8. Classifying Texts and Documents 9. Topic Modeling 10. Using Parsers to Extract Relationships 11. Combined Pipeline 12. Creating a Chatbot 13. Other Books You May Enjoy

Building a new dataset with the NER annotation tool

There are many annotation tools available in different forms. Some are standalone and can be configured or installed on a local machine, some are cloud-based, some are free, and some are paid. In this section, we will focus on free annotation tools, get an idea of how to use them, and see what we can achieve with annotation.

To see how we can use annotations to create a dataset, we will look at these tools:

  • brat
  • Stanford Annotator

brat stands for brat rapid annotation tool and can be found at http://brat.nlplab.org/index.html. It can be used online or offline. Installing it on your local machine is simple: follow the steps listed at http://brat.nlplab.org/installation.html. Once installed and running, open the browser. You need to create a text1.txt file in the data/test directory with the following...

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