Hi all I'm fairly up to date with all the NLP tasks out there (nlpprogress.com, paperswithcode.com) and great tools like (nltk, flair, huggingface etc). I want to take a single word, and predict a similar word, a little like the old "Google Sets" feature except extrapolating from a single example. I'm thinking GPT-3 might be the best bet with some seed text like

here is a list of similar things: banana, 

and ask it to predict the next word.

transformer.huggingface.co is promising enough (though hilariously inadequate in itself) that I'm thinking GPT-3 indeed may well be the answer.

But the alternative is to navigate a treebank, through "type of" relationships… much, much faster and cheaper.

I've tagged this "semantic similarity" but really I don't want the relationship to be "similar", rather "is part of same set of".

thoughts most appreciated from actual practitioners in this space rather than hobbyists like me :)


1 Answer 1


But the alternative is to navigate a treebank, through "type of" relationships… much, much faster and cheaper.

WordNet provides exactly this: it is a lexical database in which words are grouped by synonyms, with several types of relations between groups in particular hypernyms/hyponyms (more general/more specific).

The database can be downloaded and there is a library to use it through nltk.

  • $\begingroup$ OMG thanks Erwan I’ve used WordNet once before s couple of years ago but I’m not an active practitioner in this space so many thanks for the reminder! One question: last time I checked it wasn’t maintained. What do people use if they want a WordNet style capability that’s reflecting vernacular of the 2020s? $\endgroup$
    – Julian H
    Mar 10, 2021 at 11:12
  • 1
    $\begingroup$ @JulianH I think you're right, as far as I know Wordnet covers standard English, I doubt they would even try to cover anything specific of a period of time anyway. But I'm not aware of anything else remotely similar to WordNet which would cover your needs. So as you mentioned in the question, I think that people would just use similarity measures with word embeddings otherwise, with the disadvantage that it's not specific to any particular semantic relationship between words. $\endgroup$
    – Erwan
    Mar 10, 2021 at 14:26

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.