Mindtagger: A Demonstration of Data Labeling in Knowledge Base Construction
Summary: Mindtagger: a versatile data-labeling tool for KB construction, demonstrated to aid error analysis and end-to-end debugging. Labeling tasks align with error-analysis guidelines; Mindtagger enables labeling across data products to boost KB quality. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jaeho Shin
- 2. Christopher Ré
- 3. Michael Cafarella
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,105 | Extracting Databases from Dark Data with DeepDive | 2016 | SIGMOD | 6.4409563e-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 |
|---|---|---|---|---|
| 488 | Data Curation at Scale: The Data Tamer System | 2013 | CIDR | 0.00022029993 |
| 668 | Incremental Knowledge Base Construction Using DeepDive | 2015 | VLDB | 0.00018428925 |
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