VeritasOmega/veritas-claim-verification-dataset

--- language: - en license: apache-2.0 task_categories: - text-classification task_ids: - fact-checking pretty_name: VERITAS Claim Verification Dataset size_categories: - 100K<n<1M --- # VERITAS Claim Verification Dataset **775,294 labeled verification calls** (770,000 synthetic + 5,294 adversarial) Multi-model consensus verdicts from the VERITAS Oracle across 8 domains. ## Paper [VERITAS: Independence-Weighted Multi-Model Consensus for AI Output Verification](https://doi.org/10.5281/zenodo.19187611) ## Adversarial Robustness Findings (NEW) 5,294 adversarial variants generated via deterministic transforms: | Transform | N | Accuracy | |---|---|---| | negation | 2,379 | **99.7%** | | jurisdiction | 114 | 100.0% | | quantifier | 337 | 98.8% | | number_perturb | 85 | 98.8% | | temporal | 2,379 | 79.8% | | **Overall adversarial** | **5,294** | **90.7%** | | Baseline | | 98.4% | | Delta | | -7.7pp | VERITAS is highly robust to negation attacks (99.7%) — a category where single-model verifiers typically drop 10-15pp. Temporal hedging (79.8%) is the documented weakness: no time-indexed knowledge retrieval. ## Datasets - eritas_oracle.synthetic_dataset — 770k synthetic claims - eritas_oracle.synthetic_dataset_adversarial — 5,294 adversarial variants with transform labels ## Schema claim_hash, claim_text, domain, ground_truth, source, confidence, consensus, flags, model_votes, trace_id, latency_ms, correct, ingested_at ## Citation ` @misc{lopez2026veritas, title={VERITAS: Independence-Weighted Multi-Model Consensus for AI Output Verification}, author={RJ Lopez}, year={2026}, doi={10.5281/zenodo.19187611} } `