Yes, I was disappointed.

The original paper https://arxiv.org/abs/2410.22046 did look at chord progressions. They also trained a machine learning model to predict the next chord. Some of the chord progression data is in graph form at https://github.com/spyroskantarelis/chordonomicon.

The raw chord data is at https://huggingface.co/datasets/ailsntua/Chordonomicon/tree/.... It consists of one row per song containing a list of chord names in song order (no timing information) and Spotify ids for track and artist. It seems like Spotify has a different id for every released version, so it's really hard to search for particular songs in the data.

To normalise across key signatures you need to know what key the song is in (at each point), and the data doesn't contain that. For many genres it could be guessed reasonably accurately from the chords.