“Pre-trained language models (PLMs) have been widely used in entity and relation extractionmethods in recent years. However, due to the semantic gap between general-domain text usedfor pre-training and domain-specific text, these methods encounter semantic redundancy anddomain semantics insufficiency when it comes to domain-specific tasks. To mitigate this issue,we propose a low-cost and effective knowledge-enhanced method to facilitate domain-specificsemantics modeling in joint entity and relation extraction. Precisely, we use ontology and entitytype descriptions as domain knowledge sources, which are encoded and incorporated into thedownstream entity and relation extraction model to improve its understanding of domain-specificinformation. We construct a dataset called SSUIE-RE for Chinese entity and relation extractionin space science and utilization domain of China Manned Space Engineering, which contains awealth of domain-specific knowledge. The experimental results on SSUIE-RE demonstrate theeffectiveness of our method, achieving a 1.4% absolute improvement in relation F1 score overprevious best approach. Introduction”

“Named entity recognition and relation extraction are core sub-tasks of relational triple extraction. Recent studies have used parameter sharing or joint decoding to create interaction between these two tasks. However, ensuring the specificity of task-specific traits while the two tasks interact properly is a huge difficulty. We propose a multi-gate encoder that models bidirectional task interaction while keeping sufficient feature specificity based on gating mechanism in this paper. Precisely, we design two types of independent gates: task gates to generate task-specific features and interaction gates to generate instructive features to guide the opposite task. Our experiments show that our method increases the state-of-the-art (SOTA) relation F1 scores on ACE04, ACE05 and SciERC datasets to 63.8% (+1.3%), 68.2% (+1.4%), 39.4% (+1.0%), respectively, with higher inference speed over previous SOTA model.”