Python 3.x python3 nltk，WordNetLemmatizer发生错误

我看了看这本书，按照书中的内容编写了代码。顺便说一下，我有以下错误。我该怎么办

from nltk.stem import PorterStemmer, WordNetLemmatizer

sent = 'The laughs you two heard were triggered by memories 
            of his own high j-flying exits for moving beasts'

lemmatizer = WordNetLemmatizer()
words = lemmatizer.lemmatize(sent, pos = 'pos')

File "D:/machine_learning/nltk_mapper.py", line 24, in <module>
    word = lemmatizer.lemmatize(words, pos='pos')
  File "D:\machine_learning\venv\lib\site-packages\nltk\stem\wordnet.py", line 40, in lemmatize
    lemmas = wordnet._morphy(word, pos)
  File "D:\machine_learning\venv\lib\site-packages\nltk\corpus\reader\wordnet.py", line 1818, in _morphy
    exceptions = self._exception_map[pos]
KeyError: 'pos'

多谢各位

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我已经解决了。 我引用了下面的url。

结果-->听到笑声是触发存储器自己的高j飞行退出移动野兽

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谢谢

引理化的目的是将一个词的不同屈折形式组合在一起，称为引理。例如，lemmatiser应该映射gone、going和go。因此，我们必须分别对每个单词进行语法化

from nltk.stem import PorterStemmer, WordNetLemmatizer

sent = 'The laughs you two heard were triggered by memories of his own high j-flying exits for moving beasts'
sent_tokenized = sent.split(" ")
lemmatizer = WordNetLemmatizer()
words = [lemmatizer.lemmatize(word) for word in sent_tokenized]

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顺便问一下，你在书的哪一章找到了那个代码片段？或者它来自另一本书，不是吗？是的，我读了一本书《Python高级机器学习》，谢谢。就像我提到的，我想提取有意义的单词。有什么办法吗？['The'，'laugh'，'two'，'hear'，'trigger'，'memory'，'high'，'fly'，'exit'，'move'，'beast'，你必须删除停止词。要删除停止词，请参阅此。非常感谢

from nltk.tag import pos_tag
from nltk.tokenize import word_tokenize
from nltk.stem import WordNetLemmatizer
def lemmatize_all(sentence):
    wnl = WordNetLemmatizer()
    for word, tag in pos_tag(word_tokenize(sentence)):
        if tag.startswith("NN"):
            yield wnl.lemmatize(word, pos='n')
        elif tag.startswith('VB'):
            yield wnl.lemmatize(word, pos='v')
        elif tag.startswith('JJ'):
            yield wnl.lemmatize(word, pos='a')
        # else:
        #     yield word

print(' '.join(lemmatize_all('The laughs you two heard were triggered by memories of his own high j-flying exits for moving beasts')))

from nltk.stem import PorterStemmer, WordNetLemmatizer

sent = 'The laughs you two heard were triggered by memories of his own high j-flying exits for moving beasts'
sent_tokenized = sent.split(" ")
lemmatizer = WordNetLemmatizer()
words = [lemmatizer.lemmatize(word) for word in sent_tokenized]