DBLP QuAD 2.0: Scholarly Natural Questions from SPARQL
Abstract: We present DBLP-QuAD 2.0, designed to evaluate Scholarly Knowledge Graph Question Answering (KGQA) over DBLP. Recent updates in the underlying DBLP KG, including new entities and relationships such as venues, research streams, and citation links, have necessitated a corresponding update to existing KG QA benchmarking resources. While the DBLP-QuAD dataset focused on author and publication-centered queries, DBLP-QuAD 2.0 broadens the coverage to reflect the enriched structure of the updated KG. Specifically, the questions in our dataset are formulated from SPARQL query logs that cover a wide range of entities involving authors, publications, venues, research streams, and citation relationships. DBLP-QuAD 2.0 thus provides a more comprehensive benchmark for evaluating KGQA systems with a baseline.
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@inproceedings{DBLP:conf/kcap/TaffaNOWABU25,
author = {Tilahun Abedissa Taffa and
Patrick Neises and
Stefan Ollinger and
Patrick Westphal and
Marcel R. Ackermann and
Debayan Banerjee and
Ricardo Usbeck},
editor = {Cogan Shimizu and
Sebasti{\'{a}}n Ferrada and
Lalana Kagal},
title = {{DBLP} QuAD 2.0: Scholarly Natural Questions from {SPARQL}},
booktitle = {Proceedings of the 13th Knowledge Capture Conference 2025, {K-CAP}
2025, Dayton, Ohio, USA, December 10-12, 2025},
pages = {236--240},
publisher = {{ACM}},
year = {2025},
url = {https://doi.org/10.1145/3731443.3771376},
doi = {10.1145/3731443.3771376},
timestamp = {Fri, 26 Dec 2025 20:53:21 +0100},
biburl = {https://dblp.org/rec/conf/kcap/TaffaNOWABU25.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}