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Maestro: Automatic Generation of Comprehensive Benchmarks for Question Answering Over Knowledge Graphs

Summary: Maestro automates generation of QA benchmarks for any knowledge graph (with optional text corpus). It guarantees coverage of NL question and query properties documented in the literature and emits high-quality natural-language questions, enabling reusable, evolving benchmarks across KGs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6742
Venue
SIGMOD
Year
2023
Pagerank
6.0247307e-05
Overall Rank
5,969 | 59.05%
DOI
10.1145/3589322

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{orogat_sigmod23,
        title = {{Maestro: Automatic Generation of Comprehensive Benchmarks for Question Answering Over Knowledge Graphs}},
        author = {Orogat, Abdelghny and El-Roby, Ahmed},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589322},
        url = {https://dl.acm.org/doi/10.1145/3589322},
        year = {2023}
}

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