I need to list all the forms (verb , noun, comparative, superlative, adjective, and adverb) of a word using NLTK library in python . For example if I have the word "write" the result should be: wrote writing writer written etc..., also if the word can be written in comparative and superlative form e.g; cold then colder, coldest. And quick : quickly etc. Is there a way to do that?
POS Tagging in NLTK is a process to mark up the words in text format for a particular part of a speech based on its definition and context. Some NLTK POS tagging examples are: CC, CD, EX, JJ, MD, NNP, PDT, PRP$, TO, etc. POS tagger is used to assign grammatical information of each word of the sentence.
if (val = = 'NN' or val = = 'NNS' or val = = 'NNPS' or val = = 'NNP' ): print (text, " is a noun." ) else : print (text, " is not a noun." )
Hi this is my late answer. Hope this still help. I just improve it a little and some small debugging to fit new nltk version. The original code can be found in George-Bogdan Ivanov's answer here Convert words between verb/noun/adjective forms
from nltk.corpus import wordnet as wn
def morphify(word,org_pos,target_pos):
""" morph a word """
synsets = wn.synsets(word, pos=org_pos)
# Word not found
if not synsets:
return []
# Get all lemmas of the word
lemmas = [l for s in synsets \
for l in s.lemmas() if s.name().split('.')[1] == org_pos]
# Get related forms
derivationally_related_forms = [(l, l.derivationally_related_forms()) \
for l in lemmas]
# filter only the targeted pos
related_lemmas = [l for drf in derivationally_related_forms \
for l in drf[1] if l.synset().name().split('.')[1] == target_pos]
# Extract the words from the lemmas
words = [l.name() for l in related_lemmas]
len_words = len(words)
# Build the result in the form of a list containing tuples (word, probability)
result = [(w, float(words.count(w))/len_words) for w in set(words)]
result.sort(key=lambda w: -w[1])
# return all the possibilities sorted by probability
return result
print morphify('sadness','n','v')
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With