Using NLTK and WordNet; how do I convert simple tense verb into its present, past or past participle form? Using NLTK and WordNet; how do I convert simple tense verb into its present, past or past participle form? python python

Using NLTK and WordNet; how do I convert simple tense verb into its present, past or past participle form?


With the help of NLTK this can also be done. It can give the base form of the verb. But not the exact tense, but it still can be useful. Try the following code.

from nltk.stem.wordnet import WordNetLemmatizerwords = ['gave','went','going','dating']for word in words:    print word+"-->"+WordNetLemmatizer().lemmatize(word,'v')

The output is:

gave-->givewent-->gogoing-->godating-->date

Have a look at Stack Overflow question NLTK WordNet Lemmatizer: Shouldn't it lemmatize all inflections of a word?.


I think what you're looking for is the NodeBox::Linguistics library. It does exactly that:

print en.verb.present("gave")>>> give


For Python3:

pip install pattern

then

from pattern.en import conjugate, lemma, lexeme, PRESENT, SGprint (lemma('gave'))print (lexeme('gave'))print (conjugate(verb='give',tense=PRESENT,number=SG)) # he / she / it

yields

give ['give', 'gives', 'giving', 'gave', 'given'] gives

thnks to @Agargara for pointing & authors of Pattern for their beautiful work, go support them ;-)

PS. To use most of pattern's functionality in python 3.7+, you might want to use the trick described here