FCDS: Fusing Constituency and Dependency Syntax into Document-Level
  Relation Extraction
Xudong Zhu Zhao Kang Bei Hui
Document-level Relation Extraction (DocRE) aims to identify relation labels
between entities within a single document. It requires handling several
sentences and reasoning over them. State-of-the-art DocRE methods use a graph
structure to connect entities across the document to capture dependency syntax
information. However, this is insufficient to fully exploit the rich syntax
information in the document. In this work, we propose to fuse constituency and
dependency syntax into DocRE. It uses constituency syntax to aggregate the
whole sentence information and select the instructive sentences for the pairs
of targets. It exploits the dependency syntax in a graph structure with
constituency syntax enhancement and chooses the path between entity pairs based
on the dependency graph. The experimental results on datasets from various
domains demonstrate the effectiveness of the proposed method. The code is
publicly available at this url.