Hyper-Relational Extraction
2 papers with code • 1 benchmarks • 1 datasets
HyperRED is a dataset for the new task of hyper-relational extraction, which extracts relation triplets together with qualifier information such as time, quantity or location. For example, the relation triplet (Leonard Parker, Educated At, Harvard University) can be factually enriched by including the qualifier (End Time, 1967).
HyperRED
Most implemented papers
A Dataset for Hyper-Relational Extraction and a Cube-Filling Approach
Hence, we propose CubeRE, a cube-filling model inspired by table-filling approaches and explicitly considers the interaction between relation triplets and qualifiers.
Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction
lhrlab/text2nkg
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However, the construction of NKGs remains at a coarse-grained level, which is always in a single schema, ignoring the order and variable arity of entities.
