ending versus what is the probability of the wrong ending and again as we get better language models they should start to learn to exploit context and assign correct like you know the correct probabilities to these different strings and so very early work kind of took the classic supervised learning approach of just throwing you know a you know a model maybe with even word vectors pretty trained at the system and treating it as like a binary classification task but in this case the story close task it's difficult to