All datasets / michaeltheologitis
michaeltheologitis/claimdb
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Citation text from the card
@inproceedings{theologitis-etal-2026-claimdb,
title = "{C}laim{DB}: A Fact Verification Benchmark over Large Structured Data",
author = "Theologitis, Michael and
Dammu, Preetam Prabhu Srikar and
Shah, Chirag and
Suciu, Dan",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.acl-long.1589/",
doi = "10.18653/v1/2026.acl-long.1589",
pages = "34428--34451",
ISBN = "979-8-89176-390-6",
abstract = "Real-world fact-checking often involves verifying claims grounded in structured data at scale. Despite substantial progress in fact-verification benchmarks, this setting remains largely underexplored. In this work, we introduce ClaimDB, a fact-verification benchmark where the evidence for claims is derived from compositions of millions of records and multiple tables. ClaimDB consists of 80 unique real-life databases covering a wide range of domains, from governance and healthcare to media, education and the natural sciences. At this scale, verification approaches that rely on ``reading'' the evidence break down, forcing a timely shift toward reasoning in exec
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dataset_licence({ "id": "michaeltheologitis/claimdb" })
signal: "permissive"
stated_licence: "cc-by-sa-4.0"
sources: 0