Burr: A Benchmark for Ontology Learning from Relational Databases
Summary: Burr: a benchmark and mapping-based evaluation metric for ontology learning from relational databases, with 54 scenarios of real-world DB–ontology mappings (including industry datasets) and a micro-benchmark. Evaluation shows rule-based methods currently beat LLMs, but LLMs hold significant promise. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Lukas Laskowski
- 2. Michael Hladik
- 3. Jan Portisch
- 4. Fabian Panse
- 5. Felix Naumann
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| 514 | TURL: Table Understanding through Representation Learning | 2021 | VLDB | 0.00021280726 |
| 8,851 | Hitting Set Enumeration with Partial Information for Unique Column Combination Discovery | 2020 | VLDB | 4.4322123e-05 |
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