Two Training Strategies for Improving Relation Extraction over Universal Graph

12 Feb 2021 Qin Dai Naoya Inoue Ryo Takahashi Kentaro Inui

This paper explores how the Distantly Supervised Relation Extraction (DS-RE) can benefit from the use of a Universal Graph (UG), the combination of a Knowledge Graph (KG) and a large-scale text collection. A straightforward extension of a current state-of-the-art neural model for DS-RE with a UG may lead to degradation in performance... (read more)

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