Our basic underlying hypothesis is that the salience of an entity e i should be calculated by taking into consideration both its confidence and the confidence of other entities {e j } connected to it, which is inspired by PageRank [13].
for each entity e i , we construct a set of related entities as follows: {n j | n j is a name, n j and e i are coreferential or linked by a relation; and n j is involved in an event mention} Then we compute the salience of e i based on local confidence lc by the baseline single-document event extraction, and select the top-ranked entities as centroid entities: Any extraction errors from the baseline system, especially on name and time arguments, will be compounded in our new cross-document IE task because they are vital to centroid detection and temporal ordering.