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

(calc.datova.ai)
176 points nxa | 1 comments | 14 May 25 19:54 UTC | HN request time: 0.203s | source

I've been playing with embeddings and wanted to try out what results the embedding layer will produce based on just word-by-word input and addition / subtraction, beyond what many videos / papers mention (like the obvious king-man+woman=queen). So I built something that doesn't just give the first answer, but ranks the matches based on distance / cosine symmetry. I polished it a bit so that others can try it out, too.

For now, I only have nouns (and some proper nouns) in the dataset, and pick the most common interpretation among the homographs. Also, it's case sensitive.

1. nxa ◴[14 May 25 21:24 UTC] No.43989378[source]▶
This might be helpful: I haven't implemented it in the UI, but from the API response you can see what the word definitions are, both for the input and the output. If the output has homographs, likeliness is split per definition, but the UI only shows the best one.

Also, if it gets buried in comments, proper nouns need to be capitalized (Paris-France+Germany).

I am planning on patching up the UI based on your feedback.