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Show HN: Semantic Calculator (king-man+woman=?)

calc.datova.ai

31–40 of 179 posts

Re: Show HN: Semantic Calculator (king-man+woman=?)

#33

I don't get it but I'm not sure I'm supposed to. life + death = mortality life - death = lifestyle drug + time = occasion drug - time = narcotic art + artist + money = creativity art + artist - money = muse happiness + politics = contentment happiness + art = gladness happiness + money = joy happiness + love = joy

Does the system you’re querying ‘get it’? From the answers it doesn’t seem to understand these words or their relations. Once in a while it’ll hit on something that seems to make sense.

Re: Show HN: Semantic Calculator (king-man+woman=?)

#34
post #8

King-man+woman=Navratilova, who is apparently a Czech tennis player. Apparently, it's very case-sensitive. Cool idea!

"King" (capital) probably was interpreted as https://en.wikipedia.org/wiki/Billie_Jean_King , that's why a tennis player showed up.

Heh. This is fun:

Navratilova - woman + man = Lendl

Re: Show HN: Semantic Calculator (king-man+woman=?)

#35

First off, this interface is very nice and a pleasure to use, congrats! Are you using word2vec for these, or embeddings from another model? I also wanted to add some flavor since it looks like many folks in this thread haven't seen something like this - it's been known since 2013 that we can do this (but it's great to remind folks especially with all the "modern" interest in NLP). It's also known (in some circles!) t…

Thank you! I actually had a hard time finding prior work on this, so I appreciate the references.

The dictionary is based on https://wordnet.princeton.edu/, no word2vec. It's just a plain lookup among precomputed embeddings (with mxbai-embed-large). And yes, I'm excluding words that are present in the query because.

It would be interesting to see how other models perform. I tried one (forgot the name) that was focused on coding, and it didn't perform nearly as well (in terms of human joy from the results).

Re: Show HN: Semantic Calculator (king-man+woman=?)

#39

  data + plural = number
  data - plural = research
  king - crown = (didn't work... crown gets circled in red)
  king - princess = emperor
  king - queen = kingdom
  queen - king = worker
  king + queen = queen + king = kingdom
  boy + age = (didn't work... boy gets circled in red)
  man - age = woman
  woman - age = newswoman
  woman + age = adult female body (tied with man)
  girl + age = female child
  girl + old = female child
The other suggestions are pretty similar to the results I got in most cases. But I think this helps illustrate the curse of dimensionality (i.e. distances are ill-defined in high dimensional spaces). This is still quite an unsolved problem and seems a pretty critical one to resolve that doesn't get enough attention.
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