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when were building nlp systems the input is not words or even sentences but rather just sequences of characters take this example from pride and prejudice if we were to just split this by spaces we would get this word sequence where we have three instances of i that differ because punctuation is still attached so we perform tokenization which converts a sequence of characters into a sequence of tokens when using a standard tokenizer in this text we get this sequence which has separated punctuation from words and also split the contraction im into i and apostrophe m so now our three instances of i look the same most tokenizers are rule-based manually designed by speakers of a language but there are different tokenization conventions one difference in english is how contractions are handled for example heres how two tokenization conventions look for a few english contractions neither seems perfect dont and arent are maybe better handled by the pantry bank convention because t