The question might be not so clear. However, my confusion comes from the following approach: Suppose I use training, testing and validation sets. First, I split my data into training and testing. To tune my parameters (e.g., for pruning a classification tree), I then split my training set into validation and XX. I cannot use the term training set again but how is this set (training-valiation) called?
I agree that the employed terminology is not so great. Here is one way to make it unambiguous, which is used in the AMI Corpus documentation:
First, you can split the data into seen and unseen data. You then split your seen data into validation set and training set. The unseen test is also called test set. The validation set is also called development set, or hold-out data.