What is the difference between tokenization and segmentation?
An example of an AI chatbot conversation about tokenization and segmentation in NLP.
What is the difference between tokenization and segmentation?
Tokenization is the process of breaking text into individual units, like words or phrases, while segmentation divides text into meaningful segments, such as sentences or paragraphs.
Can you give me an example of tokenization?
Sure! For the sentence 'I love AI!', tokenization would result in the tokens: ['I', 'love', 'AI', '!'].
And what about segmentation?
In segmentation, the same sentence would be treated as one segment, but if you had multiple sentences, like 'I love AI! Do you?', it would segment into ['I love AI!', 'Do you?'].
Why is tokenization important in NLP?
Tokenization is crucial because it helps in understanding the structure of the text, enabling further analysis like sentiment analysis or language modeling.
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