DBLP QuAD 2.0: Scholarly Natural Questions from SPARQL

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

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.
Original languageEnglish
Title of host publicationK-CAP 2025 - Proceedings of the 13th Knowledge Capture Conference 2025
EditorsCogan Shimizu, Sebastian Ferrada, Lalana Kagal
Number of pages5
PublisherAssociation for Computing Machinery, Inc
Publication date09.12.2025
Pages236-240
ISBN (electronic)979-8-4007-1867-0
DOIs
Publication statusPublished - 09.12.2025
EventK-CAP '25: Knowledge Capture Conference 2025 - Dayton, United States
Duration: 10.12.202512.12.2025

Bibliographical note

Publisher Copyright:
© 2025 Copyright held by the owner/author(s).

    Research areas

  • DBLP, Knowledge Graph Question Answering, Question Answering Dataset, SPARQL to Natural Questions

DOI