What are the different types of tokenization in NLP?
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What are the different types of tokenization in NLP?
In NLP, tokenization is the process of breaking text into smaller units called tokens. The main types include word tokenization, sentence tokenization, and subword tokenization.
Can you explain word tokenization in more detail?
Sure! Word tokenization splits text into individual words. For example, the sentence 'I love AI!' would be tokenized into ['I', 'love', 'AI', '!'].
What about sentence tokenization?
Sentence tokenization divides text into sentences. For instance, 'I love AI! It's fascinating.' would be tokenized into ['I love AI!', 'It's fascinating.'].
And what is subword tokenization?
Subword tokenization breaks words into smaller parts, which helps in handling rare words. For example, 'unhappiness' might be tokenized into ['un', 'happiness'].
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