https://www.oranlooney.com/quotes/
I've did something similar to your 3D viewer once, but for all possible solutions to the Soma cube:
https://www.oranlooney.com/demos/soma-forest/
The way that works is it uses t-SNE to embed the solutions in a 2D manifold based on similarity. This is completely different than John Conway's SOMAP solution.
In theory I could do something similar for quotes, passing each through an embedding model, computing the n^2 semantic distances, and using t-SNE to flatten that to 3D manifold, and using the resulting point to select the row, book, and shelf in a library.
Are you planning to make your 3D library code open source?