Datasets:
license: other
license_name: mixed-upstream
license_link: https://github.com/OpenBallast/ballast
language:
- en
pretty_name: Ballast eval sets
size_categories:
- 10K<n<100K
tags:
- question-answering
- factuality
- hallucination
- rag
configs:
- config_name: matrix_probes
data_files: matrix_probes.parquet
- config_name: halluc_probes
data_files: halluc_probes.parquet
Ballast eval sets
The probe sets behind the Ballast measurements. Two files:
matrix_probes.parquet— 50,147 factual questions (recall), each with a gold answer, alias set, 7 type-matched distractors, and — where resolvable — a Wikidata subject Q-id linking it to the Ballast T0 corpus (90.5% linked at full corpus). Measured on two model families: Gemma-4 (E2B/E4B/12B) and Qwen3.5 (0.8B/2B/4B/9B), plus a bf16/fp8/nf4 quantization sweep.halluc_probes.parquet— 43,137 hallucination probes (beyond recall), 98.3% entity-linked, run over seven (model, quant) cells.
Recall probes (matrix_probes)
| source | origin | notes |
|---|---|---|
popqa |
PopQA | native subject Q-ids + popularity; the primary instrument |
wikidata |
self-generated from T0 | rank-stratified, uncontaminated by construction, regenerable |
simpleqa |
SimpleQA | typed distractors from answer_type × topic |
nq_open |
Natural Questions (open) | entity-linked via normalized n-gram match |
triviaqa |
TriviaQA (rc.nocontext) | linked via wiki-title hints + spans |
Hallucination probes (halluc_probes)
| family | n | what it tests |
|---|---|---|
hop2 |
24,320 | self-generated 2-hop compositions from T0 ("where was the director of this film born?") — the answer exists only through a join across two evidence lines, so copy-extraction cannot work. Includes a 3,200-probe adversarial subset (adversarial=true) where the competing join path's answer is also present in evidence. |
unanswerable |
12,000 | 9,600 absent_prop (the property was never recorded) + 2,400 false_premise. Every candidate answer is false; any confident pick is a fabrication. |
wikimulti |
6,000 | 2WikiMultiHopQA compositional + inference questions, both hops entity-linked. |
truthfulqa |
817 | TruthfulQA mc1 as a control family: grounding is expected to leave it unmoved. |
What they showed (full analysis in the thesis): grounding collapses multi-hop hallucination in all 21 family×cell readings (3–20×, monotone in corpus level), but on unanswerable probes fabrication rises with corpus coverage in all 7 cells — evidence that mentions the question's entities without containing an answer suppresses exactly the abstentions that were correct. The TruthfulQA control is imperfect: 3 of 7 cells hold within the 2% margin.
Schema
Both files: question_id, source, question, prop, subj, subj_qid,
gold, gold_aliases[], distractors[], s_pop, pop_decile.
halluc_probes adds family, subfamily, adversarial, bridge_qid
(the join entity for 2-hop probes).
Intended use
Logprob choice scoring: score gold + distractors under the same prompt, prediction = argmax length-normalized answer logprob, confidence = softmax mass on argmax, abstain below 0.5. Grounded condition prepends the subject's rendered evidence block from T0 at a chosen level (2-hop probes prepend both hops' blocks). Two passes (no corpus / full corpus) compose exactly to every corpus level via the subject's rank bucket — see the methodology.
Contamination stance
Models have seen the upstream benchmarks' sources in pretraining. The wikidata
recall probes and the hop2 compositions are uncontaminated by construction
(generated from the corpus, not the web). The headline quantity
(grounded − ungrounded delta) is contamination-conservative: pretraining
exposure inflates the ungrounded floor, shrinking the measured gain.
Licenses
Upstream sets keep their upstream licenses (PopQA/TriviaQA/NQ/2WikiMultiHopQA/
TruthfulQA: research-standard open licenses; SimpleQA: MIT). The self-generated
wikidata and hop2 probes are CC0. Check upstream terms before commercial
use of those subsets.