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A simple and straightforward approach to tokenization is to segment a text into individual English words and punctuation marks. For instance, given the text "I love the food here. It's amazing!", it can be broken down into the following sequence of tokens: $$\left\{ \textrm{I}, \textrm{love}, \textrm{the}, \textrm{food}, \textrm{here}, \textrm{.}, \textrm{It}, \textrm{'s}, \textrm{amazing}, \textrm{!} \right\}$$.

Example of Tokenization into Words and Punctuation

A piece of text is segmented into a sequence of smaller units by separating it into individual words and treating each punctuation mark as its own distinct unit. Given this method, which of the following options correctly represents the segmentation of the sentence: "She said, 'It's great!'"?

A text processing method involves segmenting a sentence into a sequence of its individual words and punctuation marks. Under this method, a contraction is separated into its component parts. For example, the sentence "It's amazing." would be segmented into the sequence: {It, ’, s, amazing, .}. Following this exact method, provide the complete sequence of segments for the sentence: "We're not going; it's too late!"

Applying Word and Punctuation Segmentation

A developer has written a function to segment text into a sequence of tokens. The rule for segmentation is to separate the text into individual English words and treat each punctuation mark as its own distinct unit. Analyze the function's output for the given input sentence and identify the primary logical error, explaining your reasoning based on the segmentation rule and the provided reference example.

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