DBLP QuAD 2.0: Scholarly Natural Questions from SPARQL
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-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 language | English |
|---|---|
| Title of host publication | K-CAP 2025 - Proceedings of the 13th Knowledge Capture Conference 2025 |
| Editors | Cogan Shimizu, Sebastian Ferrada, Lalana Kagal |
| Number of pages | 5 |
| Publisher | Association for Computing Machinery, Inc |
| Publication date | 09.12.2025 |
| Pages | 236-240 |
| ISBN (electronic) | 979-8-4007-1867-0 |
| DOIs | |
| Publication status | Published - 09.12.2025 |
| Event | K-CAP '25: Knowledge Capture Conference 2025 - Dayton, United States Duration: 10.12.2025 → 12.12.2025 |
Bibliographical note
Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
- Computational Theory and Mathematics
- Computer Science Applications
- Information Systems
- Software
ASJC Scopus Subject Areas
- DBLP, Knowledge Graph Question Answering, Question Answering Dataset, SPARQL to Natural Questions
