Graph-Based Seed Set Expansion for Relation Extraction Using Random Walk Hitting Times

Joel Lang and James Henderson

Iterative bootstrapping methods are widely employed for relation extraction, especially because they require only a small amount of human supervision Unfortunately, a phenomenon known as semantic drift can affect the accuracy of iterative bootstrapping and lead to poor extractions. This paper proposes an alternative bootstrapping method, which ranks relation tuples by measuring their distance to the seed tuples in a bipartite tuple-pattern graph. In contrast to previous bootstrapping methods, our method is not susceptible to semantic drift, and it empirically results in better extractions than iterative methods.