1 code implementation • 8 Oct 2023 • Haoran Luo, Haihong E, Yuhao Yang, Tianyu Yao, Yikai Guo, Zichen Tang, Wentai Zhang, Kaiyang Wan, Shiyao Peng, Meina Song, Wei Lin
To address these restrictions, we propose Text2NKG, a novel fine-grained n-ary relation extraction framework for n-ary relational knowledge graph construction.
Event-based N-ary Relaiton Extraction Hypergraph-based N-ary Relaiton Extraction +3
1 code implementation • ACL 2023 • Haoran Luo, Haihong E, Yuhao Yang, Yikai Guo, Mingzhi Sun, Tianyu Yao, Zichen Tang, Kaiyang Wan, Meina Song, Wei Lin
The global-level attention can model the graphical structure of HKG using hypergraph dual-attention layers, while the local-level attention can learn the sequential structure inside H-Facts via heterogeneous self-attention layers.
Ranked #1 on Link Prediction on Wikipeople
1 code implementation • AAAI 2023 • Haoran Luo, Haihong E, Yuhao Yang, Gengxian Zhou, Yikai Guo, Tianyu Yao, Zichen Tang, Xueyuan Lin, Kaiyang Wan
Complex query answering (CQA) is an essential task for multi-hop and logical reasoning on knowledge graphs (KGs).
Ranked #1 on Complex Query Answering on WD50K-QE
1 code implementation • AAAI 2023 • Haoran Luo, Haihong E, Ling Tan, Gengxian Zhou, Tianyu Yao, Kaiyang Wan
To overcome this limitation, we propose a dual-view hyper-relational KG structure (DH-KG) that contains a hyper-relational instance view for entities and a hyper-relational ontology view for concepts that are abstracted hierarchically from the entities.
Ranked #1 on Link prediction on DH-KGs on JW44K-6K