I just started using a part-of-speech tagger, and I am facing many problems.
I started POS tagging with the following:
import nltk
text=nltk.word_to
When you type nltk.download()
in Python, an NLTK Downloader interface gets displayed automatically.
Click on Models and choose maxent_treebank_pos_. It gets installed automatically.
import nltk
text=nltk.word_tokenize("We are going out.Just you and me.")
print nltk.pos_tag(text)
[('We', 'PRP'), ('are', 'VBP'), ('going', 'VBG'), ('out.Just', 'JJ'),
('you', 'PRP'), ('and', 'CC'), ('me', 'PRP'), ('.', '.')]
nltk.download()
Click on Models and choose maxent_treebank_pos_. It gets installed automatically.
import nltk
text=nltk.word_tokenize("We are going out.Just you and me.")
print nltk.pos_tag(text)
[('We', 'PRP'), ('are', 'VBP'), ('going', 'VBG'), ('out.Just', 'JJ'),
('you', 'PRP'), ('and', 'CC'), ('me', 'PRP'), ('.', '.')]
From the shell/terminal, you can use:
python -m nltk.downloader maxent_treebank_pos_tagger
(might need to be sudo on Linux)
It will install maxent_treebank_pos_tagger
(i.e. the standard treebank POS tagger in NLTK) and fix your issue.
If nltk version is 3.4.5, do the below:
import nltk
nltk.download('averaged_perceptron_tagger')
To check you nltk version, do the below:
print (nltk.__version__)
From NLTK
versions higher than v3.2, please use:
>>> import nltk
>>> nltk.__version__
'3.2.1'
>>> nltk.download('averaged_perceptron_tagger')
[nltk_data] Downloading package averaged_perceptron_tagger to
[nltk_data] /home/alvas/nltk_data...
[nltk_data] Package averaged_perceptron_tagger is already up-to-date!
True
For NLTK
versions using the old MaxEnt model, i.e. v3.1 and below, please use:
>>> import nltk
>>> nltk.download('maxent_treebank_pos_tagger')
[nltk_data] Downloading package maxent_treebank_pos_tagger to
[nltk_data] /home/alvas/nltk_data...
[nltk_data] Package maxent_treebank_pos_tagger is already up-to-date!
True
For more details on the change in the default pos_tag
, please see https://github.com/nltk/nltk/pull/1143
import nltk
text = "Obama delivers his first speech."
sent = nltk.sent_tokenize(text)
loftags = []
for s in sent:
d = nltk.word_tokenize(s)
print nltk.pos_tag(d)
Result :
akshayy@ubuntu:~/summ$ python nn1.py [('Obama', 'NNP'), ('delivers', 'NNS'), ('his', 'PRP$'), ('first', 'JJ'), ('speech', 'NN'), ('.', '.')]
( I just asked another question where used this code )