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DBLP QuAD 2.0: Scholarly Natural Questions from SPARQL

Year: 2025

Type: conference-paper

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.

Source: ACM International Conference on Knowledge Capture (K-CAP)

DOI: 10.1145/3731443.3771376

Authors: Tilahun Abedissa Taffa, Patrick Neises, Stefan Ollinger, Patrick Westphal, Marcel R. Ackermann, Debayan Banerjee, Ricardo Usbeck

Institutions: Leuphana University of Lüneburg, Universität Hamburg, Schloss Dagstuhl – Leibniz Center for Informatics

Language: English

Topic: Semantic Web and Ontologies

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4417148591

FWCI:

Cites: 8

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