DBScholar

Back to papers

KBPearl: A Knowledge Base Population System Supported by Joint Entity and Relation Linking

Summary: KBPearl is an end-to-end KBP system that ingests an incomplete KB and a corpus to canonicalize noisy Open IE extractions. Entity and relation linking with contextual and source-side cues enables efficient KB population, beating SOTA on real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12213
Venue
VLDB
Year
2020
Pagerank
6.4866871e-05
Overall Rank
4,834 | 66.84%
DOI
10.14778/3384345.3384352

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{lin_vldb20,
        title = {{KBPearl: A Knowledge Base Population System Supported by Joint Entity and Relation Linking}},
        author = {Lin, Xueling and Li, Haoyang and Xin, Hao and Li, Zijian and Chen, Lei},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {7},
        pages = {1035--1049},
        doi = {10.14778/3384345.3384352},
        url = {https://doi.org/10.14778/3384345.3384352},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Previous Page 1 / 1 Next

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
579 Incremental Knowledge Base Construction Using DeepDive 2015 VLDB 0.00016217563
2,917 Query-Driven On-The-Fly Knowledge Base Construction 2018 VLDB 7.9661816e-05
Previous Page 1 / 1 Next

Semantically Similar Papers