NLTK v3.2: Unable to nltk.pos_tag()

Hi text mining champions,

I'm using Anaconda with NLTK v3.2 on Windows 10.(client's environment)

When I try to POS tag, I keep getting a URLLIB2 error:

URLError: <urlopen error unknown url type: c>

It seems urllib2 is unable to recognize windows paths? How can I work around this?

The command is simple as:

nltk.pos_tag(nltk.word_tokenize("Hello World"))

edit: There is a duplicate question, however I think the answers obtained here by manan and alvas are a better fix.

Solution 1:

EDITED

This issue has been resolved from NLTK v3.2.1. Upgrading your NLTK version would resolve the issue, e.g. pip install -U nltk.

I faced the same issue and the error encountered was as follows;

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Python27\lib\site-packages\nltk-3.2-py2.7.egg\nltk\tag\__init__.py", line 110, in pos_tag
tagger = PerceptronTagger()
  File "C:\Python27\lib\site-packages\nltk-3.2-py2.7.egg\nltk\tag\perceptron.py", line 141, in __init__
self.load(AP_MODEL_LOC)
  File "C:\Python27\lib\site-packages\nltk-3.2-py2.7.egg\nltk\tag\perceptron.py", line 209, in load
self.model.weights, self.tagdict, self.classes = load(loc)
  File "C:\Python27\lib\site-packages\nltk-3.2-py2.7.egg\nltk\data.py", line 801, in load
opened_resource = _open(resource_url)
  File "C:\Python27\lib\site-packages\nltk-3.2-py2.7.egg\nltk\data.py", line 924, in _open
return urlopen(resource_url)
  File "C:\Python27\lib\urllib2.py", line 126, in urlopen
return _opener.open(url, data, timeout)
  File "C:\Python27\lib\urllib2.py", line 391, in open
response = self._open(req, data)
  File "C:\Python27\lib\urllib2.py", line 414, in _open
'unknown_open', req)
  File "C:\Python27\lib\urllib2.py", line 369, in _call_chain
result = func(*args)
  File "C:\Python27\lib\urllib2.py", line 1206, in unknown_open
raise URLError('unknown url type: %s' % type)
urllib2.URLError: <urlopen error unknown url type: c>

The URLError that you mentioned was due to a bug in the perceptron.py file within the NLTK library for Windows. In my machine, the file is at this location

C:\Python27\Lib\site-packages\nltk-3.2-py2.7.egg\nltk\tag\perceptron.py

(Basically look at an equivalent location within yours wherever you have the Python27 folder)

The bug was basically in the code to find the corresponding location for the averaged_perceptron_tagger within your machine. One can have a look at the line 801 and 924 mentioned in the data.py file regarding this.

I think the NLTK developer community recently fixed this bug in the code. Have a look at this commit made to their code a few days back.

https://github.com/nltk/nltk/commit/d3de14e58215beebdccc7b76c044109f6197d1d9#diff-26b258372e0d13c2543de8dbb1841252

The snippet where the change was made is as follows;

self.tagdict = {}
self.classes = set()
    if load:
        AP_MODEL_LOC = 'file:'+str(find('taggers/averaged_perceptron_tagger/'+PICKLE))
          self.load(AP_MODEL_LOC)
        # Initially it was:AP_MODEL_LOC = str(find('taggers/averaged_perceptron_tagger/'+PICKLE)) 

def tag(self, tokens):

Updating the file to the most recent commit worked for me and was able to use the nltk.pos_tag command. I believe this would resolve your problem as well (assuming you have everything else set up).

Solution 2:

EDITED

This issue has been resolved from NLTK v3.2.1. Please upgrade your NLTK!

First read @MananVyas answer for the why:

https://stackoverflow.com/a/35902494/610569

Here's the how, without downgrading to NLTK v3.1, using NLTK 3.2, you can use this "hack":

>>> from nltk.tag import PerceptronTagger
>>> from nltk.data import find
>>> PICKLE = "averaged_perceptron_tagger.pickle"
>>> AP_MODEL_LOC = 'file:'+str(find('taggers/averaged_perceptron_tagger/'+PICKLE))
>>> tagger = PerceptronTagger(load=False)
>>> tagger.load(AP_MODEL_LOC)
>>> pos_tag = tagger.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')]