NLTK convert tokenized sentence to synset format

Question

I'm looking to get the similarity between a single word and each word in a sentence using NLTK.

NLTK can get the similarity between two specific words as shown below. This method requires that a specific reference to the word is given, in this case it is 'dog.n.01' where dog is a noun and we want to use the first (01) NLTK definition.

dog = wordnet.synset('dog.n.01')
cat = wordnet.synset('cat.n.01')
print  dog.path_similarity(cat)
>> 0.2

The problem is that I need to get the part of speech information from each word in the sentence. The NLTK package has the ability to get the parts of speech for each word in a sentence as shown below. However, these speech parts ('NN', 'VB', 'PRP'...) don't match up with the format that the synset takes as a parameter.

text = word_tokenize("They refuse to permit us to obtain the refuse permit")
pos_tag(text)
>> [('They', 'PRP'), ('refuse', 'VBP'), ('to', 'TO'), ('permit', 'VB'), ('us', 'PRP'), ('to', 'TO'), ('obtain', 'VB'), ('the', 'DT'), ('refuse', 'NN'), ('permit', 'NN')]

Is is possible to get the synset formatted data from pos_tag() results in NLTK? By synset formatted I mean the format like dog.n.01

Answer 1

You can use a simple conversion function:

from nltk.corpus import wordnet as wn

def penn_to_wn(tag):
    if tag.startswith('J'):
        return wn.ADJ
    elif tag.startswith('N'):
        return wn.NOUN
    elif tag.startswith('R'):
        return wn.ADV
    elif tag.startswith('V'):
        return wn.VERB
    return None

After tagging a sentence you can tie a word inside the sentence with a SYNSET using this function. Here's an example:

from nltk.stem import WordNetLemmatizer
from nltk import pos_tag, word_tokenize

sentence = "I am going to buy some gifts"
tagged = pos_tag(word_tokenize(sentence))

synsets = []
lemmatzr = WordNetLemmatizer()

for token in tagged:
    wn_tag = penn_to_wn(token[1])
    if not wn_tag:
        continue

    lemma = lemmatzr.lemmatize(token[0], pos=wn_tag)
    synsets.append(wn.synsets(lemma, pos=wn_tag)[0])

print synsets

Result: [Synset('be.v.01'), Synset('travel.v.01'), Synset('buy.v.01'), Synset('gift.n.01')]

Answer 2

You can use the alternative form of wordnet.synset:

wordnet.synset('dog', pos=wordnet.NOUN)

You'll still need to translate the tags offered by pos_tag into those supported by wordnet.sysnset -- unfortunately, I don't know of a pre-built dictionary doing that, so (unless I'm missing the existence of such a correspondence table) you'll need to build your own (you can do that once and pickle it for subsequent reloading).

See http://www.nltk.org/book/ch05.html , subchapter 1, on how to get help about a specific tagset -- e.g nltk.help.upenn_tagset('N.*') will confirm that the UPenn tagset (which I believe is the default one used by pos_tag) uses 'N' followed by something to identify variants of what synset will see as a wordnet.NOUN.

I have not tried http://www.nltk.org/_modules/nltk/tag/mapping.html but it might be just what you require -- give it a try!