eScience Center Blog

blog.esciencecenter.nl · Company blog · on HN since 2017

The Netherlands eScience Center's engineers write about research software, covering Rust, FPGAs, Python, C++, GraphQL, and word embeddings.

What HN saysHN commenters cite its post on king minus man plus woman to show the word2vec analogy result is partly an artifact of how it was computed.
19HN people shared it
5linked it in comments
27stories submitted
403story points
9 months agolast shared
2017people per year2026

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What HN people wrote when they linked it

spindump8930 · 2025-05-14
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!) that a lot of these vector arithmetic things need some tricks to really shine. For example, excluding the words already present in the query[1]. Others in this thread seem surprised at some of the biases present - there's also a long history of work on that [2,3]. [1] https://blog.esciencecenter.nl/king-man-woman-king-9a7fd2935a85 [2] https://arxiv.org/abs/1905.09866 [3] https://arxiv.org/abs/1903.03862
smallerize · 2025-11-02
That never exactly worked for word2vec either. https://blog.esciencecenter.nl/king-man-woman-king-9a7fd2935a85
liampulles · 2025-10-13
Thank you for the comment! This led me to do a bit more research, and I see indeed the queen result is in itself infact "cheating" a bit: https://blog.esciencecenter.nl/king-man-woman-king-9a7fd2935a85 #TheMoreYouKnow
flo_hu · 2019-07-22
I removed my blog post from medium's distribution. So it should now be freely accessible! https://blog.esciencecenter.nl/king-man-woman-king-9a7fd2935a85

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