Hi @spearsheep,
The truth is that the UI was not really designed to handle this many labels. But there's a reason to it as it is, likely, not the best idea to try to annotate this many labels at the same time.
This would be really taxing for the annotators, as they need to think about big data model with every annotation task and not the easiest task for the model ether.
This thread by @ines explains very well why you might consider splitting your annotation in steps.
In your case it looks like you could have sever high level classes such as EXPERIENCE and DIVISION and once your model is capable to distinguish between these high level classes, you could set up follow-up annotations to reannotate EXPERIENCE and DIVISION into their fine-grained classes.
If you're interested in some more NER annotation good practice tips, this thread has plenty of relevant references on the topic of dealing with a high number of labels.