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Cleaning Inconsistencies in Information Extraction via Prioritized Repairs

Summary: Declarative framework for cleaning inconsistent IE outputs by integrating prioritized repairs into document spanners, enabling user-declared conflict-resolution policies that capture industrial cleaning operations and POSIX regex semantics. Analyzes unambiguity and expressive power of such policies, with both positive and negative (decidability/complexity) results. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1615
Venue
PODS
Year
2014
Pagerank
6.6608401e-05
Overall Rank
4,499 | 69.14%
DOI
10.1145/2595438.2594540

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{fagin_pods14,
        address = {New York, NY, USA},
        series = {{PODS} '14},
        title = {{Cleaning Inconsistencies in Information Extraction via Prioritized Repairs}},
        url = {https://dl.acm.org/doi/10.1145/2595438.2594540},
        doi = {10.1145/2595438.2594540},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Fagin, Ronald and Kimelfeld, Benny and Reiss, Frederick and Vansummeren, Stijn},
        year = {2014}
}

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