Building Structured Databases of Factual Knowledge from Massive Text Corpora
Summary: Minimally-supervised, domain- and language-independent extraction of entities, relations, and attributes to build StructDBs from text corpora. Demonstrates scalable cross-domain StructDB construction across news, social, biomedical, and business data with reduced labeling, enabling exploration and knowledge discovery. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Xiang Ren (University of Illinois Urbana-Champaign)
- 2. Meng Jiang (University of Illinois Urbana-Champaign)
- 3. Jingbo Shang (University of Illinois Urbana-Champaign)
- 4. Jiawei Han (University of Illinois Urbana-Champaign)
BibTeX Citation
@inproceedings{ren_sigmod17,
title = {{Building Structured Databases of Factual Knowledge from Massive Text Corpora}},
author = {Ren, Xiang and Jiang, Meng and Shang, Jingbo and Han, Jiawei},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3054781},
url = {https://dl.acm.org/doi/10.1145/3035918.3054781},
year = {2017}
}
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