NLTK Tokenize: Create a list of words from a given string
Write a Python NLTK program to create a list of words from a given string.
Sample Solution:
Python Code-1:
from nltk.tokenize import word_tokenize
text = "Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station."
print("\nOriginal string:")
print(text)
print("\nList of words:")
print(word_tokenize(text))
Sample Output:
Original string: Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station. List of words: ['Joe', 'waited', 'for', 'the', 'train', '.', 'The', 'train', 'was', 'late', '.', 'Mary', 'and', 'Samantha', 'took', 'the', 'bus', '.', 'I', 'looked', 'for', 'Mary', 'and', 'Samantha', 'at', 'the', 'bus', 'station', '.']
It's equivalent to the following code:
Python Code-2:
from nltk.tokenize import TreebankWordTokenizer
tokenizer = TreebankWordTokenizer()
text = "Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station."
print("\nOriginal string:")
print(text)
print("\nList of words:")
print(tokenizer.tokenize(text))
Output:
Original string: Joe waited for the train. The train was late. Mary and Samantha took the bus. I looked for Mary and Samantha at the bus station. List of words: ['Joe', 'waited', 'for', 'the', 'train.', 'The', 'train', 'was', 'late.', 'Mary', 'and', 'Samantha', 'took', 'the', 'bus.', 'I', 'looked', 'for', 'Mary', 'and', 'Samantha', 'at', 'the', 'bus', 'station', '.']
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