Feature idea: track artifacts (co-)dependencies

I think it might be quite useful to track dependencies in such a way that e.g. if I want to deploy a new version of artifact `foo` to `prod` and foo depends on artifacts `bar` and `baz` then GTO will warn me if `bar` and `baz` are not yet in `prod`.

Reasoning:

In a scenario with coupled data and model versions (see [here](https://discord.com/channels/485586884165107732/563406153334128681/1015962755611754577) for my reasons for why that might be a good idea) it would be nice to be able to link them together explicitly.

I can look at the dvc pipeline of my `foo` model in the `foo_training` repository and see that it depends on `foo_data, rev:v0.1.0`. I can even add this info to the annotation of `foo_model` in GTO in the model registry (so that I don't have to keep going back to the model to check). But with this workflow, I would like to make sure I cannot deploy a model to production if it depends on a dataset which is not yet in production (i.e. if it is produced by a data pipeline which does not run in production and consequently, the integration of the model service and data preparation service will fail).

So a cool feature would be if GTO gives me a warning (or prevents me unless I use something like `gto assign --force`) when I am assigning `prod` (or any specified reserved stage name) to the model, unless its dataset dependency is also in `prod`.