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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838987312
Length 284 pages
Edition 1st Edition
Languages
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Author (1):
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Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (10) Chapters Close

Preface 1. Chapter 1: Learning NLP Basics 2. Chapter 2: Playing with Grammar FREE CHAPTER 3. Chapter 3: Representing Text – Capturing Semantics 4. Chapter 4: Classifying Texts 5. Chapter 5: Getting Started with Information Extraction 6. Chapter 6: Topic Modeling 7. Chapter 7: Building Chatbots 8. Chapter 8: Visualizing Text Data 9. Other Books You May Enjoy

Performing named entity recognition using spaCy

In this recipe, we will parse out named entities from an article text used in Chapter 4, Classifying Texts. We will load the package and the parsing engine, and loop through the NER results.

Getting ready

In this recipe, we will use the spacy package. If you haven't installed it yet, install it using the following command:

pip install spacy

After you install spaCy, you will need to download a language model. We will download the small model:

python -m spacy download en_core_web_sm

How to do it…

The NER happens automatically with the processing that spaCy does for an input text. Accessing the entities happens through the doc.ents variable. The steps for this recipe are as follows:

  1. Import spacy:
    import spacy
  2. Initialize the spaCy engine:
    nlp = spacy.load("en_core_web_sm")
  3. Initialize the article text:
    article = """iPhone 12: Apple makes jump to 5G
    Apple has confirmed its...
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