Our proposed sentence content task is a paragraph-level analogue to the word content task of Adi et al.
(2017): given embeddings 2 p, s of a paragraph p and a candidate sentence s, respectively, we train a classifier to predict whether or not s occurs in p. we construct a binary classification task in which the input is [p; s], the concatenation of p and s. This task is balanced: for each paragraph p in our corpus, we create one positive instance by sampling a sentence s + from p and one negative instance by randomly sampling a sentence s − from another paragraph p .