Verified claim · AI-ML · 92% confidence
TruthfulQA benchmark introduced in paper: TruthfulQA: Measuring How Models Mimic Human Falsehoods (Lin et al., 2021).
Last verified 2026-05-31 · Methodology veritas-v0.1 · 824f830889daf33e
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Structured fields
- Subject
- TruthfulQA benchmark
- Predicate
introduced_in_paper- Object
- TruthfulQA: Measuring How Models Mimic Human Falsehoods (Lin et al., 2021)
- Confidence
- 92%
- Tags
- truthfulqa · benchmark · evaluation · truthfulness · hallucination · lin · 2021
Sources (3)
[1] preprint · arXiv (Lin, Hilton, Evans — University of Oxford + OpenAI) · 2021-09-08
TruthfulQA: Measuring How Models Mimic Human Falsehoods“The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics.”
[2] github release · Stephanie Lin (sylinrl) · 2021-09-08
TruthfulQA benchmark repository[3] docs · Hugging Face
TruthfulQA (Hugging Face Papers)Hugging Face is rated by SourceScore — see its reliability →
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curl https://sourcescore.org/api/v1/claims/824f830889daf33e.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/824f830889daf33e.json");
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// "TruthfulQA benchmark introduced in paper: TruthfulQA: Measuring How Models Mimic Human Falsehoods (Lin et al., 2021)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/824f830889daf33e.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "TruthfulQA benchmark introduced in paper: TruthfulQA: Measuring How Models Mimic Human Falsehoods (Lin et al., 2021)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_truthfulqa_benchmark_fact() -> dict:
"""Fetch the verified SourceScore claim for TruthfulQA benchmark."""
r = httpx.get("https://sourcescore.org/api/v1/claims/824f830889daf33e.json")
return r.json()