Furthermore, rather than considering all pairs of clusters as candidate merges, we use the scores of the pairwise models to reduce the search space, first by providing an ordering over which merges are considered and secondly by discarding merges that are not likely to be good.
our model also achieves the highest CEAF φ 4 F 1 and second highest MUC F 1 scores among the other systems.