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.
for instance, for the example in figure 1, the most readable update can be made by inserting He never exited the consulate but died there to the right of Jamal Khashoggi was murdered.