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Python 3 Text Processing with NLTK 3 Cookbook

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

Product type Book
Published in Aug 2014
Publisher
ISBN-13 9781782167853
Pages 304 pages
Edition 1st Edition
Languages
Author (1):
Jacob Perkins Jacob Perkins
Profile icon Jacob Perkins

Table of Contents (17) Chapters

Python 3 Text Processing with NLTK 3 Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Tokenizing Text and WordNet Basics Replacing and Correcting Words Creating Custom Corpora Part-of-speech Tagging Extracting Chunks Transforming Chunks and Trees Text Classification Distributed Processing and Handling Large Datasets Parsing Specific Data Types 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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