import nltk
nltk.download()

输入: Everything is all about money.
输出: [('Everything', 'NN'), ('is', 'VBZ'),
          ('all', 'DT'),('about', 'IN'),
          ('money', 'NN'), ('.', '.')]

import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize, sent_tokenize
stop_words = set(stopwords.words('english'))
// 虚拟文字
txt = "Sukanya, Rajib and Naba are my good friends. " \
    "Sukanya is getting married next year. " \
    "Marriage is a big step in one’s life." \
    "It is both exciting and frightening. " \
    "But friendship is a sacred bond between people." \
    "It is a special kind of love between us. " \
    "Many of you must have tried searching for a friend "\
    "but never found the right one."
# sent_tokenize是来自nltk.tokenize.punkt模块的PunktSentenceTokenizer的实例之一
tokenized = sent_tokenize(txt)
for i in tokenized:
    # 单词分词器用于查找字符串中的单词和标点符号
    wordsList = nltk.word_tokenize(i)
    # 从wordList中删除停用词
    wordsList = [w for w in wordsList if not w in stop_words]
    #  使用匕首，这是词性标记器或POS标记器的一部分.
    tagged = nltk.pos_tag(wordsList)
    print(tagged)

[('Sukanya', 'NNP'), ('Rajib', 'NNP'), ('Naba', 'NNP'), ('good', 'JJ'), ('friends', 'NNS')]
[('Sukanya', 'NNP'), ('getting', 'VBG'), ('married', 'VBN'), ('next', 'JJ'), ('year', 'NN')]
[('Marriage', 'NN'), ('big', 'JJ'), ('step', 'NN'), ('one', 'CD'), ('’', 'NN'), ('life', 'NN')]
[('It', 'PRP'), ('exciting', 'VBG'), ('frightening', 'VBG')]
[('But', 'CC'), ('friendship', 'NN'), ('sacred', 'VBD'), ('bond', 'NN'), ('people', 'NNS')]
[('It', 'PRP'), ('special', 'JJ'), ('kind', 'NN'), ('love', 'VB'), ('us', 'PRP')]
[('Many', 'JJ'), ('must', 'MD'), ('tried', 'VB'), ('searching', 'VBG'), ('friend', 'NN'),
('never', 'RB'), ('found', 'VBD'), ('right', 'RB'), ('one', 'CD')]