Document-to-Database: Extraction Meets Relational Semantics
Summary: DataMosaic bridges LLM document extraction and relational semantics via a constraint-aware orchestrator. Its closed extract–verify–repair–re-extract loop incrementally builds auditable databases, reducing violations and improving database-level accuracy. (summarized by gpt-5.6-luna on Aug 17 2026)
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Authors
- 1. Zhengxuan Zhang (Hong Kong University of Science and Technology)
- 2. Zhuowen Liang (Hong Kong University of Science and Technology)
- 3. Jiazhuo Chen (Hong Kong University of Science and Technology)
- 4. Haixun Wang (EvenUp)
- 5. Nan Tang (Hong Kong University of Science and Technology)
BibTeX Citation
@article{zhang_vldb26,
title = {{Document-to-Database: Extraction Meets Relational Semantics}},
author = {Zhang, Zhengxuan and Liang, Zhuowen and Chen, Jiazhuo and Wang, Haixun and Tang, Nan},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {9},
pages = {2522--2535},
doi = {10.14778/3819518.3819568},
url = {https://doi.org/10.14778/3819518.3819568},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 13,591 | DataMosaic: An Interactive Demonstration of Constraint-Driven Document-to-Database Construction | 2026 | VLDB | - |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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