Python | Tokenize text using TextBlob

TextBlob module is a Python library and offers a simple API to access its methods and perform basic NLP tasks. It is built on the top of NLTK module.

Install TextBlob using the following commands in terminal:

pip install -U textblob
python -m textblob.download_corpora

This will install TextBlob and download the necessary NLTK corpora. The above installation will take quite some time due to the massive amount of tokenizers, chunkers, other algorithms, and all of the corpora to be downloaded.

Some terms that will be frequently used are :

  • Corpus – Body of text, singular. Corpora is the plural of this.
  • Lexicon – Words and their meanings.
  • Token – Each “entity” that is a part of whatever was split up based on rules. For examples, each word is a token when a sentence is “tokenized” into words. Each sentence can also be a token, if you tokenized the sentences out of a paragraph.

So basically tokenizing involves splitting sentences and words from the body of the text.





# from textblob lib. import TextBlob method
from textblob import TextBlob
text = ("Natural language processing (NLP) is a field " + 
       "of computer science, artificial intelligence " + 
       "and computational linguistics concerned with " +  
       "the interactions between computers and human " +  
       "(natural) languages, and, in particular, " +  
       "concerned with programming computers to " + 
       "fruitfully process large natural language " +  
       "corpora. Challenges in natural language " +  
       "processing frequently involve natural " + 
       "language understanding, natural language" +  
       "generation frequently from formal, machine" +  
       "-readable logical forms), connecting language " +  
       "and machine perception, managing human-" + 
       "computer dialog systems, or some combination " +  
# create a TextBlob object
blob_object = TextBlob(text)
# tokenize paragraph into words.
print(" Word Tokenize :\n", blob_object.words)
# tokenize paragraph into sentences.
print("\n Sentence Tokenize :\n", blob_object.sentences)


Output :

Word Tokenize :
[‘Natural’, ‘language’, ‘processing’, ‘NLP’, ‘is’, ‘a’, ‘field’, ‘of’, ‘computer’, ‘science’, ‘artificial’, ‘intelligence’, ‘and’, ‘computational’, ‘linguistics’, ‘concerned’, ‘with’, ‘the’, ‘interactions’, ‘between’, ‘computers’, ‘and’, ‘human’, ‘natural’, ‘languages’, ‘and’, ‘in’, ‘particular’, ‘concerned’, ‘with’, ‘programming’, ‘computers’, ‘to’, ‘fruitfully’, ‘process’, ‘large’, ‘natural’, ‘language’, ‘corpora’, ‘Challenges’, ‘in’, ‘natural’, ‘language’, ‘processing’, ‘frequently’, ‘involve’, ‘natural’, ‘language’, ‘understanding’, ‘natural’, ‘languagegeneration’, ‘frequently’, ‘from’, ‘formal’, ‘machine-readable’, ‘logical’, ‘forms’, ‘connecting’, ‘language’, ‘and’, ‘machine’, ‘perception’, ‘managing’, ‘human-computer’, ‘dialog’, ‘systems’, ‘or’, ‘some’, ‘combination’, ‘thereof’]

Sentence Tokenize :
[Sentence(“Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora.”), Sentence(“Challenges in natural language processing frequently involve natural language understanding, natural language generation frequently from formal, machine-readable logical forms), connecting language and machine perception, managing human-computer dialog systems, or some combination thereof.”)]

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