what do you mean by “automatically know”?
I guess you already know that ##xx tokens are continuation tokens.
I don’t think it is possible to detect from (‘Er’, 17)  that it has a continuation.
If you feed the data into an untrained  Bert model, [I think] the embedding layer will create an embedding vector for (‘Er’,17) that does not depend on the continuation tokens.
If you feed the data into a trained Bert model, the embedding layer might create different embedding vectors for different instances of (‘Er’, 17), depending on their context, which includes depending on any continuation tokens.
There is a nice tutorial by Chris McCormick here https://mccormickml.com/2019/05/14/BERT-word-embeddings-tutorial/ 25 that discusses embeddings in more detail.
If you were asking about something else, please clarify.
[I am not an expert, and I could be wrong]