Global Context-enhanced Graph Convolutional Networks for Document-level Relation Extraction

1 code implementation • COLING 2020 • Huiwei Zhou, Yibin Xu, Weihong Yao, Zhe Liu, Chengkun Lang, Haibin Jiang

In this paper, we propose Global Context-enhanced Graph Convolutional Networks (GCGCN), a novel model which is composed of entities as nodes and context of entity pairs as edges between nodes to capture rich global context information of entities in a document.

Document-level Relation Extraction Relation