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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 60 recipes for building powerful NLP solutions using Python and LLM libraries

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781803245744
Length 312 pages
Edition 2nd Edition
Languages
Concepts
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Authors (2):
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Saurabh Chakravarty Saurabh Chakravarty
Author Profile Icon Saurabh Chakravarty
Saurabh Chakravarty
Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (13) 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: Visualizing Text Data 8. Chapter 8: Transformers and Their Applications 9. Chapter 9: Natural Language Understanding 10. Chapter 10: Generative AI and Large Language Models 11. Index 12. Other Books You May Enjoy

Dividing text into sentences

When we work with text, we can work with text units on different scales: the document itself, such as a newspaper article, the paragraph, the sentence, or the word. Sentences are the main unit of processing in many NLP tasks. For example, when we send data over to Large Language Models (LLMs), we frequently want to add some context to the prompt. In some cases, we would like that context to include sentences from a text so that the model can extract some important information from that text. In this section, we will show you how to divide a text into sentences.

Getting ready

For this part, we will be using the text of the book The Adventures of Sherlock Holmes. You can find the whole text in the book’s GitHub file (https://github.com/PacktPublishing/Python-Natural-Language-Processing-Cookbook-Second-Edition/blob/main/data/sherlock_holmes.txt). For this recipe we will need just the beginning of the book, which can be found in the file at https...

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