Using WordNet with nltk to find synonyms that make sense

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I want to input a sentence, and output a sentence with hard words made simpler.

I'm using Nltk to tokenize sentences and tag words, but I'm having trouble using WordNet to find a synonym for the specific meaning of a word that I want.

For example:

Input: "I refuse to pick up the refuse"

Maybe refuse #1 is the easiest word for rejecting, but the refuse #2 means garbage, and there are simpler words that could go there.

Nltk might be able to tag refuse #2 as a noun, but then how do I get synonyms for refuse (trash) from WordNet?

wordnet nltk python
1 Answers

Sounds like you want word synonyms based upon the part of speech of the word (i.e. noun, verb, etc.)

Follows creates synonyms for each word in a sentence based upon part of speech. References:

  1. Extract Word from Synset using Wordnet in NLTK 3.0
  2. Printing the part of speech along with the synonyms of the word

Code

import nltk; nltk.download('popular') 
from nltk.corpus import wordnet as wn

def get_synonyms(word, pos):
  ' Gets word synonyms for part of speech '
  for synset in wn.synsets(word, pos=pos_to_wordnet_pos(pos)):
    for lemma in synset.lemmas():
        yield lemma.name()

def pos_to_wordnet_pos(penntag, returnNone=False):
   ' Mapping from POS tag word wordnet pos tag '
    morphy_tag = {'NN':wn.NOUN, 'JJ':wn.ADJ,
                  'VB':wn.VERB, 'RB':wn.ADV}
    try:
        return morphy_tag[penntag[:2]]
    except:
        return None if returnNone else ''

Example Usage

# Tokenize text
text = nltk.word_tokenize("I refuse to pick up the refuse")

for word, tag in nltk.pos_tag(text):
  print(f'word is {word}, POS is {tag}')

  # Filter for unique synonyms not equal to word and sort.
  unique = sorted(set(synonym for synonym in get_synonyms(word, tag) if synonym != word))

  for synonym in unique:
    print('\t', synonym)

Output

Note the different sets of synonyms for refuse based upon POS.

word is I, POS is PRP
word is refuse, POS is VBP
     decline
     defy
     deny
     pass_up
     reject
     resist
     turn_away
     turn_down
word is to, POS is TO
word is pick, POS is VB
     beak
     blame
     break_up
     clean
     cull
     find_fault
     foot
     nibble
     peck
     piece
     pluck
     plunk
word is up, POS is RP
word is the, POS is DT
word is refuse, POS is NN
     food_waste
     garbage
     scraps
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