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If I try this :
import nltk
text = nltk.word_tokenize("And now for something completely different")
nltk.pos_tag(text)
Output:
Traceback (most recent call last):
File "C:/Python27/pos.py", line 3, in <module>
nltk.pos_tag(text)
File "C:\Python27\lib\site-packages\nltk-2.0.4-py2.7.egg\nltk\tag\__init__.py" ipos_tag
tagger = load(_POS_TAGGER)
File "C:\Python27\lib\site-packages\nltk-2.0.4-py2.7.egg\nltk\data.py", line 605,in
resource_val = pickle.load(_open(resource_url))
ImportError: No module named numpy.core.multiarray
467
with the word_tokenize() function. Then the tokens are POS tagged with the function pos_tag() .
In simple words, we can say that POS tagging is a task of labelling each word in a sentence with its appropriate part of speech. We already know that parts of speech include nouns, verb, adverbs, adjectives, pronouns, conjunction and their sub-categories.
To obtain fine-grained POS tags, we could use the tag_ attribute.
It seems that the saved word tokenizer requires numpy. You'll need to install it.
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