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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

Creating a part-of-speech tagged word corpus


Part-of-speech tagging is the process of identifying the part-of-speech tag for a word. Most of the time, a tagger must first be trained on a training corpus. How to train and use a tagger is covered in detail in Chapter 4, Part-of-speech Tagging, but first we must know how to create and use a training corpus of part-of-speech tagged words.

Getting ready

The simplest format for a tagged corpus is of the form word/tag. The following is an excerpt from the brown corpus:

The/at-tl expense/nn and/cc time/nn involved/vbn are/ber astronomical/jj ./.

Each word has a tag denoting its part-of-speech. For example, nn refers to a noun, while a tag that starts with vb is a verb.

Note

Different corpora can use different tags to mean the same thing. For example, the treebank corpus uses different tags as compared to the brown corpus, even though both are English text. But both sets of tags can be converted into a universal tagset, described at the end of this recipe...

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