###Run this cell. Do not change the code in this cell from nltk.tokenize import sent_tokenize, word_tokenize from nltk.corpus import gutenberg def get_rawtext(filename='carroll-alice.txt'): text=gutenberg.raw(filename) return text def get_text(filename='carroll-alice.txt'): text=gutenberg.raw(filename) sentences=sent_tokenize(text) tokenized= [word_tokenize(sent.lower()) for sent in sentences] normalised=[["Nth" if (token.endswith( ("nd","st","th")) and token [:-2].isdigit()) else token for token in sent] for sent in tokenized] normalised=[["NUM" if token.isdigit() else token for token in sent] for sent in normalised] filtered=[[word for word in sent if word.isalpha()] for sent in normalised] return filtered
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