Methods › Natural Language Processing › Relation Extraction Models › CubeRE
CubeRE
Introduced by Yew Ken Chia et al. in A Dataset for Hyper-Relational Extraction and a Cube-Filling Approach
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Our model known as CubeRE first encodes each input sentence using a language model encoder to obtain the contextualized sequence representation. We then capture the interaction between each possible head and tail entity as a pair representation for predicting the entity-relation label scores. To reduce the computational cost, each sentence is pruned to retain only words that have higher entity scores. Finally, we capture the interaction between each possible relation triplet and qualifier to predict the qualifier label scores and decode the outputs.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
A Dataset for Hyper-Relational Extraction and a Cube-Filling Approach 18 Nov 2022 · 1 repository · arXiv:2211.10018
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Hyper-Relational Extraction | 1 |
| Relation | 1 |
| Relation Extraction | 1 |
| Triplet | 1 |
| graph construction | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections