Relation Extraction (RE) has been extended to cross-document scenarios
because many relations are not simply described in a single document. This
inevitably brings the challenge of efficient open-space evidence retrieval to
support the inference of cross-document relations, along with the challenge of
multi-hop reasoning on top of entities and evidence scattered in an open set of
documents. To combat these challenges, we propose Mr.CoD, a multi-hop evidence
retrieval method based on evidence path mining and ranking with adapted dense
retrievers. We explore multiple variants of retrievers to show evidence
retrieval is an essential part in cross-document RE. Experiments on CodRED show
that evidence retrieval with Mr.Cod effectively acquires cross-document
evidence that essentially supports open-setting cross-document RE.
Additionally, we show that Mr.CoD facilitates evidence retrieval and boosts
end-to-end RE performance with effective multi-hop reasoning in both closed and
open settings of RE.

本研究提出了一种基于证据路径挖掘和排序的多跳证据检索方法 Mr.CoD，通过多种检索变量探究跨文献关系抽取中的跨文献证据检索和多跳推理挑战。该方法在 CodRED 数据集上的实验结果表明，通过 Mr.CoD 实现的证据检索有效地获得了跨文献证据，并且在封闭和开放设置下提高了关系抽取性能。