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Python 3 Text Processing with NLTK 3 Cookbook

You're reading from   Python 3 Text Processing with NLTK 3 Cookbook

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Product type Paperback
Published in Aug 2014
Publisher
ISBN-13 9781782167853
Length 304 pages
Edition 2nd Edition
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Author (1):
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Jacob Perkins Jacob Perkins
Author Profile Icon Jacob Perkins
Jacob Perkins
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Table of Contents (12) Chapters Close

Preface 1. Tokenizing Text and WordNet Basics FREE CHAPTER 2. Replacing and Correcting Words 3. Creating Custom Corpora 4. Part-of-speech Tagging 5. Extracting Chunks 6. Transforming Chunks and Trees 7. Text Classification 8. Distributed Processing and Handling Large Datasets 9. Parsing Specific Data Types A. Penn Treebank Part-of-speech Tags
Index

Introduction

Now that you know how to get chunks/phrases from a sentence, what do you do with them? This chapter will show you how to do various transforms on both chunks and trees. The chunk transforms are for grammatical correction and rearranging phrases without loss of meaning. The tree transforms give you ways to modify and flatten deep parse trees. The functions detailed in these recipes modify data, as opposed to learning from it. This means it's not safe to apply them indiscriminately. A thorough knowledge of the data you want to transform, along with a few experiments, should help you decide which functions to apply and when.

Whenever the term chunk is used in this chapter, it could refer to an actual chunk extracted by a chunker, or it could simply refer to a short phrase or sentence in the form of a list of tagged words. What's important in this chapter is what you can do with a chunk, not where it came from.

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