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

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Published inAug 2014
Reading LevelBeginner
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ISBN-139781782167853
Edition1st Edition
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Jacob Perkins
Jacob Perkins
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Jacob Perkins

Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.
Read more about Jacob Perkins

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Replacing negations with antonyms


The opposite of synonym replacement is antonym replacement. An antonym is a word that has the opposite meaning of another word. This time, instead of creating custom word mappings, we can use WordNet to replace words with unambiguous antonyms. Refer to the Looking up lemmas and synonyms in WordNet recipe in Chapter 1, Tokenizing Text and WordNet Basics, for more details on antonym lookups.

How to do it...

Let's say you have a sentence like let's not uglify our code. With antonym replacement, you can replace not uglify with beautify, resulting in the sentence let's beautify our code. To do this, we will create an AntonymReplacer class in replacers.py as follows:

from nltk.corpus import wordnet

class AntonymReplacer(object):
  def replace(self, word, pos=None):
    antonyms = set()
    for syn in wordnet.synsets(word, pos=pos):
      for lemma in syn.lemmas():
        for antonym in lemma.antonyms():
          antonyms.add(antonym.name())
    if len(antonyms...
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Python 3 Text Processing with NLTK 3 Cookbook
Published in: Aug 2014Publisher: ISBN-13: 9781782167853

Author (1)

author image
Jacob Perkins

Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.
Read more about Jacob Perkins