Document-level Relationship Extraction by Bidirectional Constraints of Beta Rules

Abstract

Document-level Relation Extraction (DocRE) intends to extract relationships from documents. Some works introduce logic constraints into DocRE, addressing the issues of opacity and weak logic in original DocRE models. However, they only focus on forward logic constraints and the rules mined in these works often suffer from pseudo rules with high standard-confidence but low support. In this paper, we proposes Bidirectional Constraints of Beta Rules(BCBR), a novel logic constraint framework. BCBR first introduces a new rule miner which model rules by beta contribtion. Then forward and reverse logic constraints are constructed based on beta rules. Finally, BCBR reconstruct rule consistency loss by bidirectional constraints to regulate the output of the DocRE model. Experiments show that BCBR outperforms original DocRE models on relation extraction performance (∼2.7 F1) and logic consistency(∼3.1 Logic). Furthermore, BCBR consistently outperforms two other logic constraint frameworks. Our code is available at https://github.com/Louisliu1999/BCBR.