Python NLTK pos_tag未返回正确的词性标签
machine-learning
nlp
nltk
python
7
0

有这个:

text = word_tokenize("The quick brown fox jumps over the lazy dog")

并运行:

nltk.pos_tag(text)

我得到:

[('The', 'DT'), ('quick', 'NN'), ('brown', 'NN'), ('fox', 'NN'), ('jumps', 'NNS'), ('over', 'IN'), ('the', 'DT'), ('lazy', 'NN'), ('dog', 'NN')]

这是不正确的。句子中quick brown lazy的标签应为:

('quick', 'JJ'), ('brown', 'JJ') , ('lazy', 'JJ')

通过他们的在线工具测试得出相同的结果。 quickbrownfox应该是形容词而不是名词。

参考资料:
Stack Overflow
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简而言之

NLTK并不完美。实际上,没有任何模型是完美的。

注意:

从NLTK版本3.1开始,默认的pos_tag函数不再是旧的MaxEnt English pickle

现在是@Honnibal的实现中感知器标记器 ,请参见nltk.tag.pos_tag

>>> import inspect
>>> print inspect.getsource(pos_tag)
def pos_tag(tokens, tagset=None):
    tagger = PerceptronTagger()
    return _pos_tag(tokens, tagset, tagger) 

还是更好,但并不完美:

>>> from nltk import pos_tag
>>> pos_tag("The quick brown fox jumps over the lazy dog".split())
[('The', 'DT'), ('quick', 'JJ'), ('brown', 'NN'), ('fox', 'NN'), ('jumps', 'VBZ'), ('over', 'IN'), ('the', 'DT'), ('lazy', 'JJ'), ('dog', 'NN')]

在某些时候,如果有人想要TL;DR解决方案,请参见https://github.com/alvations/nltk_cli


总而言之

尝试使用其他标记器(请参阅https://github.com/nltk/nltk/tree/develop/nltk/tag ),例如

  • 汉宝
  • 斯坦福POS
  • 番泻叶

使用NLTK的默认MaxEnt POS标记器,即nltk.pos_tag

>>> from nltk import word_tokenize, pos_tag
>>> text = "The quick brown fox jumps over the lazy dog"
>>> pos_tag(word_tokenize(text))
[('The', 'DT'), ('quick', 'NN'), ('brown', 'NN'), ('fox', 'NN'), ('jumps', 'NNS'), ('over', 'IN'), ('the', 'DT'), ('lazy', 'NN'), ('dog', 'NN')]

使用斯坦福POS标记器

$ cd ~
$ wget http://nlp.stanford.edu/software/stanford-postagger-2015-04-20.zip
$ unzip stanford-postagger-2015-04-20.zip
$ mv stanford-postagger-2015-04-20 stanford-postagger
$ python
>>> from os.path import expanduser
>>> home = expanduser("~")
>>> from nltk.tag.stanford import POSTagger
>>> _path_to_model = home + '/stanford-postagger/models/english-bidirectional-distsim.tagger'
>>> _path_to_jar = home + '/stanford-postagger/stanford-postagger.jar'
>>> st = POSTagger(path_to_model=_path_to_model, path_to_jar=_path_to_jar)
>>> text = "The quick brown fox jumps over the lazy dog"
>>> st.tag(text.split())
[(u'The', u'DT'), (u'quick', u'JJ'), (u'brown', u'JJ'), (u'fox', u'NN'), (u'jumps', u'VBZ'), (u'over', u'IN'), (u'the', u'DT'), (u'lazy', u'JJ'), (u'dog', u'NN')]

使用HunPOS (注意:默认编码是ISO-8859-1而不是UTF8):

$ cd ~
$ wget https://hunpos.googlecode.com/files/hunpos-1.0-linux.tgz
$ tar zxvf hunpos-1.0-linux.tgz
$ wget https://hunpos.googlecode.com/files/en_wsj.model.gz
$ gzip -d en_wsj.model.gz 
$ mv en_wsj.model hunpos-1.0-linux/
$ python
>>> from os.path import expanduser
>>> home = expanduser("~")
>>> from nltk.tag.hunpos import HunposTagger
>>> _path_to_bin = home + '/hunpos-1.0-linux/hunpos-tag'
>>> _path_to_model = home + '/hunpos-1.0-linux/en_wsj.model'
>>> ht = HunposTagger(path_to_model=_path_to_model, path_to_bin=_path_to_bin)
>>> text = "The quick brown fox jumps over the lazy dog"
>>> ht.tag(text.split())
[('The', 'DT'), ('quick', 'JJ'), ('brown', 'JJ'), ('fox', 'NN'), ('jumps', 'NNS'), ('over', 'IN'), ('the', 'DT'), ('lazy', 'JJ'), ('dog', 'NN')]

使用Senna (请确保您具有最新版本的NLTK,并对API进行了一些更改):

$ cd ~
$ wget http://ronan.collobert.com/senna/senna-v3.0.tgz
$ tar zxvf senna-v3.0.tgz
$ python
>>> from os.path import expanduser
>>> home = expanduser("~")
>>> from nltk.tag.senna import SennaTagger
>>> st = SennaTagger(home+'/senna')
>>> text = "The quick brown fox jumps over the lazy dog"
>>> st.tag(text.split())
[('The', u'DT'), ('quick', u'JJ'), ('brown', u'JJ'), ('fox', u'NN'), ('jumps', u'VBZ'), ('over', u'IN'), ('the', u'DT'), ('lazy', u'JJ'), ('dog', u'NN')]

或者尝试构建更好的POS标记器


关于stackoverflow的pos_tag准确性的投诉包括

有关NLTK HunPos的问题包括

NLTK和Stanford POS标记器的问题包括

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