Question

我需要将单词分类为它们的词性。像动词，名词，副词等。我用

nltk.word_tokenize() #to identify word in a sentence 
nltk.pos_tag()       #to identify the parts of speech
nltk.ne_chunk()      #to identify Named entities.

它的输出是一棵树。例如

>>> sentence = "I am Jhon from America"
>>> sent1 = nltk.word_tokenize(sentence )
>>> sent2 = nltk.pos_tag(sent1)
>>> sent3 =  nltk.ne_chunk(sent2, binary=True)
>>> sent3
Tree('S', [('I', 'PRP'), ('am', 'VBP'), Tree('NE', [('Jhon', 'NNP')]), ('from', 'IN'), Tree('NE', [('America', 'NNP')])])

当访问该树中的元素时，我按如下方式进行操作：

>>> sent3[0]
('I', 'PRP')
>>> sent3[0][0]
'I'
>>> sent3[0][1]
'PRP'

但是，当访问命名实体时：

>>> sent3[2]
Tree('NE', [('Jhon', 'NNP')])
>>> sent3[2][0]
('Jhon', 'NNP')
>>> sent3[2][1]    
Traceback (most recent call last):
  File "<pyshell#121>", line 1, in <module>
    sent3[2][1]
  File "C:\Python26\lib\site-packages\nltk\tree.py", line 139, in __getitem__
    return list.__getitem__(self, index)
IndexError: list index out of range

我收到上述错误。

我想要的是获得类似于先前“ PRP”的“ NE”输出，因此我无法确定哪个单词是命名实体。有没有办法用python中的NLTK做到这一点？如果是这样，请发布命令。还是树库中有一个函数可以做到这一点？我需要节点值“ NE”