CODEWITHSUNDEEP
pythonnlpnltkpos-tagger
SSBakh
SSBakh

Reputation: 1532

How to use pos_tag in NLTK?

So I was trying to tag a bunch of words in a list (POS tagging to be exact) like so:

pos = [nltk.pos_tag(i,tagset='universal') for i in lw]

where lw is a list of words (it's really long or I would have posted it but it's like [['hello'],['world']] (aka a list of lists which each list containing one word) but when I try and run it I get:

Traceback (most recent call last):
  File "<pyshell#183>", line 1, in <module>
    pos = [nltk.pos_tag(i,tagset='universal') for i in lw]
  File "<pyshell#183>", line 1, in <listcomp>
    pos = [nltk.pos_tag(i,tagset='universal') for i in lw]
  File "C:\Users\my system\AppData\Local\Programs\Python\Python35\lib\site-packages\nltk\tag\__init__.py", line 134, in pos_tag
    return _pos_tag(tokens, tagset, tagger)
  File "C:\Users\my system\AppData\Local\Programs\Python\Python35\lib\site-packages\nltk\tag\__init__.py", line 102, in _pos_tag
    tagged_tokens = tagger.tag(tokens)
  File "C:\Users\my system\AppData\Local\Programs\Python\Python35\lib\site-packages\nltk\tag\perceptron.py", line 152, in tag
    context = self.START + [self.normalize(w) for w in tokens] + self.END
  File "C:\Users\my system\AppData\Local\Programs\Python\Python35\lib\site-packages\nltk\tag\perceptron.py", line 152, in <listcomp>
    context = self.START + [self.normalize(w) for w in tokens] + self.END
  File "C:\Users\my system\AppData\Local\Programs\Python\Python35\lib\site-packages\nltk\tag\perceptron.py", line 240, in normalize
    elif word[0].isdigit():
IndexError: string index out of range

Can someone tell me why and how I get this error and how to fix it? Many thanks.

Upvotes: 8

Views: 35962

Answers (3)

MOHA OUSAID SAAID
MOHA OUSAID SAAID

Reputation: 21

if you have the input as raw strings, you can use word_tokenize before pos_tag:

import nltk

is_noun = lambda pos: pos[:2] == 'NN'

lines = 'You can never plan the future by the past'

lines = lines.lower()
tokenized = nltk.word_tokenize(lines)
nouns = [word for (word, pos) in nltk.pos_tag(tokenized) if is_noun(pos)]

print(nouns) # ['future', 'past']

Upvotes: 2

Wickkiey
Wickkiey

Reputation: 4632

A common function to parse a document with pos tags, 

def get_pos(string):
    string = nltk.word_tokenize(string)
    pos_string = nltk.pos_tag(string)
    return pos_string

get_post(sentence)

Hope this helps !

Upvotes: 1

alvas
alvas

Reputation: 121992

Firstly, use human-readable variable names, it helps =)

Next, pos_tag input is a list of string. So it's

>>> from nltk import pos_tag
>>> sentences = [ ['hello', 'world'], ['good', 'morning'] ]
>>> [pos_tag(sent) for sent in sentences]
[[('hello', 'NN'), ('world', 'NN')], [('good', 'JJ'), ('morning', 'NN')]]

Also, if you have the input as raw strings, you can use word_tokenize before pos_tag:

>>> from nltk import pos_tag, word_tokenize
>>> a_sentence = 'hello world'
>>> word_tokenize(a_sentence)
['hello', 'world']
>>> pos_tag(word_tokenize(a_sentence))
[('hello', 'NN'), ('world', 'NN')]

>>> two_sentences = ['hello world', 'good morning']
>>> [word_tokenize(sent) for sent in two_sentences]
[['hello', 'world'], ['good', 'morning']]
>>> [pos_tag(word_tokenize(sent)) for sent in two_sentences]
[[('hello', 'NN'), ('world', 'NN')], [('good', 'JJ'), ('morning', 'NN')]]

And you have the sentences in a paragraph, you can use sent_tokenize to split the sentence up.

>>> from nltk import sent_tokenize, word_tokenize, pos_tag
>>> text = "Hello world. Good morning."
>>> sent_tokenize(text)
['Hello world.', 'Good morning.']
>>> [word_tokenize(sent) for sent in sent_tokenize(text)]
[['Hello', 'world', '.'], ['Good', 'morning', '.']]
>>> [pos_tag(word_tokenize(sent)) for sent in sent_tokenize(text)]
[[('Hello', 'NNP'), ('world', 'NN'), ('.', '.')], [('Good', 'JJ'), ('morning', 'NN'), ('.', '.')]]

See also: How to do POS tagging using the NLTK POS tagger in Python?

Upvotes: 16

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