融合实体和上下文信息的篇章关系抽取研究

Document-level relation extraction aims to identify the relations among entities from the document. Compared with traditional sentence-level relation extraction, document-level relation extraction is more realistic and poses new challenges of cross-sentence inference and context information understanding. In this paper, we propose a novel method for document-level relation extraction by fusing entity and context information (FECI), which contains two modules: Entity information extraction module and context information extraction module. Entity information extraction module automatically extracts crucial relation features about entity pair. Context information extraction module extracts different context relation features from the document according to mentions'position information of entity pair. We have conducted experiments on three document-level relation extraction datasets, and the effect has been significantly improved.