TENET: Joint Entity and Relation Linking with Coherence Relaxation
Summary: TENET relaxes global coherence in joint entity-relation linking by formulating it as a minimum-cost rooted-tree cover on a knowledge-coherence graph, unsupervised. Efficient approximation with pruning yields SOTA performance on real-world datasets. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Xueling Lin (Hong Kong University of Science and Technology)
- 2. Lei Chen (Hong Kong University of Science and Technology)
- 3. Chaorui Zhang (Huawei)
BibTeX Citation
@inproceedings{lin_sigmod21,
title = {{TENET: Joint Entity and Relation Linking with Coherence Relaxation}},
author = {Lin, Xueling and Chen, Lei and Zhang, Chaorui},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457280},
url = {https://dl.acm.org/doi/10.1145/3448016.3457280},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,872 | OpenMEL: Unsupervised Multimodal Entity Linking Using Noise-Free Expanded Queries and Global Coherence | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,917 | Query-Driven On-The-Fly Knowledge Base Construction | 2018 | VLDB | 7.9661816e-05 |
| 4,834 | KBPearl: A Knowledge Base Population System Supported by Joint Entity and Relation Linking | 2020 | VLDB | 6.4866871e-05 |
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