Python NLTK | nltk.tokenize.mwe()

With the help of NLTK nltk.tokenize.mwe() method, we can tokenize the audio stream into multi_word expression token which helps to bind the tokens with underscore by using nltk.tokenize.mwe() method. Remember it is case sensitive.

Syntax : MWETokenizer.tokenize()
Return : Return bind tokens as one if declared before.

Example #1 :
In this example we are using MWETokenizer.tokenize() method, which used to bind the tokens which is defined before. We can also add the predefined tokens by using tokenizer.add_mwe() method.



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# import MWETokenizer() method from nltk
from nltk.tokenize import MWETokenizer
   
# Create a reference variable for Class MWETokenizer
tk = MWETokenizer([('g', 'f', 'g'), ('geeks', 'for', 'geeks')])
   
# Create a string input
gfg = "geeks for geeks g f g"
   
# Use tokenize method
geek = tk.tokenize(gfg.split())
   
print(geek)

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Output :

[‘geeks_for_geeks’, ‘g_f_g’]

Example #2 :

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# import MWETokenizer() method from nltk
from nltk.tokenize import MWETokenizer
   
# Create a reference variable for Class MWETokenizer
tk = MWETokenizer([('g', 'f', 'g'), ('geeks', 'for', 'geeks')])
tk.add_mwe(('who', 'are', 'you'))
   
# Create a string input
gfg = "who are you at geeks for geeks"
   
# Use tokenize method
geek = tk.tokenize(gfg.split())
   
print(geek)

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Output :

[‘who_are_you’, ‘at’, ‘geeks_for_geeks’]



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