The process breaks down to three steps: first, we pair c j with each of the sentences t k ∈ T and compute a sentence-sentence relational vector v j,k which is the sum over all the word-word bi-linear contraction (the bi-linear contraction of two word embeddings Then, we average over the sentencesentence relation vectors to obtain a summary vector p j = average  Since our models' supervision comes in the form of whole scenarios, supervising our iterative insertion clustering model is not completely straightforward.
there may be multiple correct sentences that can be added to the current scenario.