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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

The SBD process


The SBD process is language-dependent and is often not straightforward. Common approaches to detect sentences include using a set of rules or training a model to detect them. A set of simple rules for detecting a sentence follows. The end of a sentence is detected if the following is true:

  • The text is terminated by a period, question mark, or exclamation mark
  • The period is not preceded by an abbreviation or followed by a digit

Although this works well for most sentences, it will not work for all of them. For example, it is not always easy to determine what an abbreviation is, and sequences such as ellipses may be confused with periods.

Most search engines are not concerned with SBD. They are only interested in a query's tokens and their positions. POS-taggers and other NLP tasks that perform the extraction of data will frequently process individual sentences. The detection of sentence boundaries will help separate phrases that might appear to span sentences. For example, consider...

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