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Provenance for Natural Language Queries

Summary: End-to-end NL QA system delivering provenance-enabled answers with explanations tied to query provenance. Introduces two NL provenance views—factorization and summarization—turning large provenance into readable NL, with experiments and a user study on quality and scalability. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11741
Venue
VLDB
Year
2017
Pagerank
6.6107638e-05
Overall Rank
4,602 | 68.43%
DOI
10.14778/3055540.3055548

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{deutch_vldb17,
        title = {{Provenance for Natural Language Queries}},
        author = {Deutch, Daniel and Frost, Nave and Gilad, Amir},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {5},
        pages = {577--588},
        doi = {10.14778/3055540.3055548},
        url = {https://doi.org/10.14778/3055540.3055548},
        year = {2017}
}

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