I remember thinking about this when the semantic web was first being discussed. If you think of it from the perceptive of a child, your first 'foundational' words are learned though direct experience. Then while you continue to learn words this way, we can also use those words we 'know' to define secondary or tertiary terms that we have no direct experience of. I'd like to see a graph like this with someones take on the minimum number of necessary foundational words and how that graph would look.

It's a common problem to get excited about networks, build a large one, and then by stuck with an unapproachable hairball. If you want to explore network structure, consider using tools like quadrilateral simmelian backones which can provide an opinionated look at what matters in the network.

If you like this, you would probably enjoy Princeton Wordnet. They have unfortunately stopped developing it.

You can still browse it a bit online with some 3rd party sites: https://en-word.net/

Nice! Reminds me a bit of "WordWeb" which is still around:

https://wordweb.info/free/

which also uses WordNet:

https://en.wikipedia.org/wiki/WordNet

(which this is also using)

which was developed by Princeton w/ DARPA money as an early investigation into AI and so forth.

This reminds me of the classic "Growing a Language" talk by Guy Steele: https://www.youtube.com/watch?v=_ahvzDzKdB0

There are some surprises like the word 'r'

It seems broken. The word "knows" only connects to the word "operator"

It's an interesting visualization for sure, but I don't really know what I can take away from it. Is it useful for something?

Beautiful! Thank you!

Very neat. What software is being used to construct/display the graph?

Is, be, and the don't show up in search box.

What am I missing?