Word sense disambiguation in NLTK Python

Question

I am new to NLTK Python and i am looking for some sample application which can do word sense disambiguation. I have got a lot of algorithms in search results but not a sample application. I just want to pass a sentence and want to know the sense of each word by referring to wordnet library. Thanks

I have found a similar module in PERL. http://marimba.d.umn.edu/allwords/allwords.html Is there such module present in NLTK Python?

Answer 1

Recently, part of the pywsd code has been ported into the bleeding edge version of NLTK' in the wsd.py module, try:

>>> from nltk.wsd import lesk >>> sent = 'I went to the bank to deposit my money' >>> ambiguous = 'bank' >>> lesk(sent, ambiguous) Synset('bank.v.04') >>> lesk(sent, ambiguous).definition() u'act as the banker in a game or in gambling' 

For better WSD performance, use the pywsd library instead of the NLTK module. In general, simple_lesk() from pywsd does better than lesk from NLTK. I'll try to update the NLTK module as much as possible when I'm free.

---

In responds to Chris Spencer's comment, please note the limitations of Lesk algorithms. I'm simply giving an accurate implementation of the algorithms. It's not a silver bullet, http://en.wikipedia.org/wiki/Lesk_algorithm

Also please note that, although:

lesk("My cat likes to eat mice.", "cat", "n") 

don't give you the right answer, you can use pywsd implementation of max_similarity():

>>> from pywsd.similarity import max_similiarity >>> max_similarity('my cat likes to eat mice', 'cat', 'wup', pos='n').definition  'feline mammal usually having thick soft fur and no ability to roar: domestic cats; wildcats' >>> max_similarity('my cat likes to eat mice', 'cat', 'lin', pos='n').definition  'feline mammal usually having thick soft fur and no ability to roar: domestic cats; wildcats' 

@Chris, if you want a python setup.py , just do a polite request, i'll write it...