of algorithms for semi-supervised so they did us uh if you see in here um uh they've used in a supervised method wherein they used all the 50 000 examples that were labeled so they needed labels for 50 000 items or entities and they had to train based on that but with the mix match coming in they reduced the number of training set or labeled set to 250. if you know what i mean so so let me go back and i'll explain a bit of a semi-supervised learning space so semi-supervised learning space needs both a bit of a label