Suppose that sentences {s en k,l |l ∈ L} contain the same entities in articles of entity e y m, the wrong labelling errors increase because some of them are almost irrelevant to e y m. Knowledge attention aims at filtering out wrong labelled sentences through smaller weights and related sentences with higher weights.
we define it proportional to the similarity between s y k,l and e y m: ψ(e y m , s y k,l ) ∝ sim(e y m , where sim is similarity measurement, and we use cosine similarity in the rest of the paper.