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Can someone give a qualitative explanation of what the vector of a word with 2 unrelated meanings would look like compared to the vector of a synonym of each of those meanings?



If you think about it like a point on a graph, and the vectors as just 2D points (x,y), then the synonyms would be close and the unrelated meanings would be further away.


I'm guessing 2 dimensions isn't for this.

Here's a concrete example: "bow" would need to be close to "ribbon" (as in a bow on a present) and also close to "gun" (as a weapon that shoots a projectile), but "ribbon" and "gun" would seem to need be far from each other. How does something like word2vec resolve this? Any transitive relationship would seem to fall afoul of this.


Yes, only more sophisticated embeddings can capture that and it's over 300+ dimensions.


But we still need a measure of "closeness" that is non-transitive.




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