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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 (19) Chapters Close

Title Page
Dedication
Packt Upsell
Contributors
Preface
1. Introduction to NLP 2. Finding Parts of Text FREE CHAPTER 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 1. Other Books You May Enjoy Index

Chapter 10. Using Parsers to Extract Relationships

Parsing is the process of creating a parse tree for a textual unit. This unit may be for a line of code or a sentence. It is easy to do for computer languages, since they were designed to make this task easy. However, this has made it harder to write code. Natural language parsing is considerably more difficult, and this is due to the ambiguity found in natural languages. This ambiguity makes a language difficult to learn but offers great flexibility and expressive power. Here, we are not interested in parsing computer languages, but rather natural languages.

A parse tree is a hierarchical data structure that represents the syntactic structure of a sentence. Often, this is presented as a tree graph with a root, as we will illustrate shortly. We will use the parse tree to help identify relationships between entities in the tree.

Parsing is used for many tasks, including the following:

  • Machine translation of languages
  • Synthesizing speech from...
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