Relation guided and attention enhanced multi-head selection for relational facts extraction

Multi-head selection is a reasonable way of extracting relational facts. Though effective, it ignores the interdependencies of relations and disregards the contextual information. In this paper, we propose a relation guided and attention enhanced approach to address the above challenges. Specifically, we predict the relations existing in the input sentence to guide multi-head selection. This strategy helps to model dependencies of relations. Moreover, we use an attention mechanism to leverage the sentential context. The experimental results demonstrate that our approach significantly outperforms the baselines.