有这个:
text = word_tokenize("The quick brown fox jumps over the lazy dog")
并运行:
nltk.pos_tag(text)
我明白了:
[('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
的标签应该是:
('quick', 'JJ'), ('brown', 'JJ') , ('lazy', 'JJ')
通过他们的online tool 进行测试给出相同的结果; quick
、brown
和 fox
应该是形容词而不是名词。
最佳答案
简而言之:
NLTK is not perfect. In fact, no model is perfect.
注意:
从 NLTK 3.1 版开始,默认的 pos_tag
函数不再是 old MaxEnt English pickle .
现在是 @Honnibal's implementation 中的 感知器标记器 ,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)
仍然更好但并不完美:
>>> 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,请参阅 https://github.com/alvations/nltk_cli
长期:
尝试使用其他标记器(参见 https://github.com/nltk/nltk/tree/develop/nltk/tag),例如:
- HunPos
- 斯坦福 POS
- 塞纳
使用来自 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')]
使用斯坦福词性标注器:
$ 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(确保您拥有最新版本的 NLTK,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')]
或者尝试构建一个更好的词性标注器:
- Ngram 标记器:http://streamhacker.com/2008/11/03/part-of-speech-tagging-with-nltk-part-1/
- 词缀/正则表达式标记器:http://streamhacker.com/2008/11/10/part-of-speech-tagging-with-nltk-part-2/
- 构建你自己的 Brill(阅读代码,这是一个非常有趣的标记器,http://www.nltk.org/_modules/nltk/tag/brill.html),参见 http://streamhacker.com/2008/12/03/part-of-speech-tagging-with-nltk-part-3/
- 感知器标记器:https://honnibal.wordpress.com/2013/09/11/a-good-part-of-speechpos-tagger-in-about-200-lines-of-python/
- LDA 标记器:http://scm.io/blog/hack/2015/02/lda-intentions/
提示 pos_tag
在 stackoverflow 上的准确性包括:
- POS tagging - NLTK thinks noun is adjective
- python NLTK POS tagger not behaving as expected
- How to obtain better results using NLTK pos tag
- pos_tag in NLTK does not tag sentences correctly
关于 NLTK HunPos 的问题包括:
- How do I tag textfiles with hunpos in nltk?
- Does anyone know how to configure the hunpos wrapper class on nltk?
NLTK 和斯坦福词性标注器的问题包括:
- trouble importing stanford pos tagger into nltk
- Java Command Fails in NLTK Stanford POS Tagger
- Error using Stanford POS Tagger in NLTK Python
- How to improve speed with Stanford NLP Tagger and NLTK
- Nltk stanford pos tagger error : Java command failed
- Instantiating and using StanfordTagger within NLTK
- Running Stanford POS tagger in NLTK leads to "not a valid Win32 application" on Windows
关于Python NLTK pos_tag 未返回正确的词性标记,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/30821188/