Prior Relational Schema Assists Effective Contrastive Learning for Inductive Knowledge Graph Completion
Ruilin Luo, Jiayi Li, Jianghangfan Zhang, Jing Xiao, Yujiu Yang
Abstract
Knowledge Graph Completion (KGC) is a task aimed at uncovering the inherent relationships among known knowledge triplets in a Knowledge Graph (KG) and subsequently predicting missing links. Presently, there is a rising interest in inductive knowledge graph completion, where missing links may pertain to previously unobserved entities. Previous inductive KGC methods mainly rely on descriptive information of entities to improve the representation of unseen entities, neglecting to provide effective prior knowledge for relation modeling. To tackle this challenge, we capture prior schema-level interactions related to relations by leveraging entity type information, thereby furnishing effective prior constraints when reasoning with newly introduced entities. Moreover, We employ normal in-batch negatives and introduce schema-guided negatives to bolster the efficiency of normal contrastive representation learning. Experimental results demonstrate that our approach consistently achieves state-of-the-art performance on various established metrics across multiple benchmark datasets for link prediction. Notably, our method achieves a 20.5% relative increase in Hits@1 on the HumanWiki-Ind dataset.- Anthology ID:
- 2024.lrec-main.1139
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 13014–13025
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.1139
- DOI:
- Cite (ACL):
- Ruilin Luo, Jiayi Li, Jianghangfan Zhang, Jing Xiao, and Yujiu Yang. 2024. Prior Relational Schema Assists Effective Contrastive Learning for Inductive Knowledge Graph Completion. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 13014–13025, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Prior Relational Schema Assists Effective Contrastive Learning for Inductive Knowledge Graph Completion (Luo et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.lrec-main.1139.pdf