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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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Toc

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

Using NLP APIs


We will use the OpenNLP and Stanford APIs to demonstrate parsing and the extraction of relation information. LingPipe can also be used, but will not be discussed here. An example of how LingPipe is used to parse biomedical literature can be found at http://alias-i.com/lingpipe-3.9.3/demos/tutorial/medline/read-me.html.

Using OpenNLP

Parsing text is simple using the ParserTool class. Its static parseLine method accepts three arguments and returns a Parser instance. These arguments are as follows:

  • A string containing the text to be parsed
  • A Parser instance
  • An integer specifying how many parses are to be returned

The Parser instance holds the elements of the parse. The parses are returned in order of their probability. To create a Parser instance, we will use the ParserFactory class' create method. This method uses a ParserModel instance that we will create using the en-parser-chunking.bin file.

This process is shown here, in which an input stream for the model file is created using...

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