Based on the test results of 10 corpora, we show that a PU learning technique outperformed distributional similarity significantly.
the entity set expansion problem is defined as follows: Given a set S of seed entities of a particular class, and a set D of candidate entities (e.g., extracted from a text corpus), we wish to determine which of the entities in D belong to S. we "expand" the set S based on the given seeds.