NLTK Tokenize: Tokenize words, sentence wise
NLTK Tokenize: Exercise-5 with Solution
Write a Python NLTK program to tokenize words, sentence wise.
Sample Solution:
Python Code :
from nltk.tokenize import sent_tokenize, 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("\nTokenize words sentence wise:")
result = [word_tokenize(t) for t in sent_tokenize(text)]
print("\nRead the list:")
for s in result:
print(s)
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. Tokenize words sentence wise: Read the list: ['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', '.']
Have another way to solve this solution? Contribute your code (and comments) through Disqus.
Previous: Write a Python NLTK program to split all punctuation into separate tokens.
Next: Write a Python NLTK program to tokenize a twitter text.
What is the difficulty level of this exercise?
Test your Programming skills with w3resource's quiz.
It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.
https://www.w3resource.com/python-exercises/nltk/nltk-tokenize-exercise-5.php
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics