Relation Extraction as Two-way Span-Prediction

The current supervised relation classification (RC) task uses a single embedding to represent the relation between a pair of entities. We argue that a better approach is to treat the RC task as a Question answering (QA) like span prediction problem. We present a span-prediction based system for RC and evaluate its performance compared to the embedding based system. We achieve state-of-the-art results on the TACRED and SemEval task 8 datasets.