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Found 4 papers, 4 papers with code
Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction
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
HAHE: Hierarchical Attention for Hyper-Relational Knowledge Graphs in Global and Local Level
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
NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphs
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
DHGE: Dual-View Hyper-Relational Knowledge Graph Embedding for Link Prediction and Entity Typing
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
