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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

Swapping noun cardinals


In a chunk, a cardinal word, tagged as CD, refers to a number, such as 10. These cardinals often occur before or after a noun. For normalization purposes, it can be useful to always put the cardinal before the noun.

How to do it...

The swap_noun_cardinal() function is defined in transforms.py. It swaps any cardinal that occurs immediately after a noun with the noun so that the cardinal occurs immediately before the noun. It uses a helper function, tag_equals(), which is similar to tag_startswith(), but in this case, the function it returns does an equality comparison with the given tag:

def tag_equals(tag):
  def f(wt):
    return wt[1] == tag
  return f

Now we can define swap_noun_cardinal():

def swap_noun_cardinal(chunk):
  cdidx = first_chunk_index(chunk, tag_equals('CD'))
  # cdidx must be > 0 and there must be a noun immediately before it
  if not cdidx or not chunk[cdidx-1][1].startswith('NN'):
    return chunk

  noun, nntag = chunk[cdidx-1]
  chunk[cdidx-1]...
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