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.
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 span-prediction (SP) problem, similar to Question answering (QA) . We present a span-prediction based system for RC and evaluate its performance compared to the embedding based system . We demonstrate that the supervised SP objective works significantly better then the standard classification based objective . We achieve state-of-the-art results on the TACRED and SemEval task 8 datasets.
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span-prediction (SP) problem, similar to
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like span prediction problem
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. We demonstrate that the supervised SP objective works significantly better then the standard classification based objective