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when weamp;#39;re 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 ization which converts a sequence of characters into a sequence of s when using a standard izer in this text we get this sequence which has separated punctuation from words and also split the contraction iamp;#39;m into i and apostrophe m so now our three instances of i look the same most izers are rule-based manually designed by speakers of a language but there are different ization conventions one difference in english is how contractions are handled for example hereamp;#39;s how two ization conventions look for a few english contractions neither seems perfect donamp;#39;t and arenamp;#39;t are maybe better handled by the pantry bank convention becaus
