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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

Chunk extraction, or partial parsing, is the process of extracting short phrases from a part-of-speech tagged sentence. This is different from full parsing in that we're interested in standalone chunks, or phrases, instead of full parse trees (for more on parse trees, see https://en.wikipedia.org/wiki/Parse_tree). The idea is that meaningful phrases can be extracted from a sentence by looking for particular patterns of part-of-speech tags.

As in Chapter 4, Part-of-speech Tagging, we'll be using the Penn Treebank corpus for basic training and testing chunk extraction. We'll also be using the CoNLL2000 corpus as it has a simpler and more flexible format that supports multiple chunk types (for more details on the conll2000 corpus and IOB tags, see the Creating a chunked phrase corpus recipe in Chapter 3, Creating Custom Corpora).

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