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188-mcq
Mask-grounded multiple choice (Set-of-Mark style) for mobile phone screen defect localization — 1196 items,
derived deterministically from the binary segmentation masks of AI4Manufacturing/188.
Exact-match gradable → SFT and RLVR-ready.
Task
One item per eligible defective record. image is a 2×2 grid of views A–D of the same photo,
each overlaying one red candidate region mask. Exactly one view overlays the named defect type accurately — right
location and extent. annot is the correct letter. The three negatives per item are hard by
construction (shift / fliplr / flipud / rot180 / dilate ≥2.5× / erode), each guaranteed
wrong (IoU vs truth < 0.35 except dilate), panels mutually distinct (pairwise IoU < 0.7). Gold
letters: A 310 / B 293 / C 301 / D 292. Coverage: oil 398, scratch 399, stain 399.
Records are skipped (confidence over coverage) when the gold mask is under ~30 visible px after
panel downscale, fewer than 3 sound negatives are constructible, or the mask covers >35% of the frame.
Skipped defects remain fully covered by 188-grounding / 188-region.
| field | meaning |
|---|---|
query |
names the defect type to locate; "answer with the letter only" |
image |
2×2 composite, panels A–D |
annot |
A / B / C / D |
reasoning |
null — deterministic |
cate / task |
B / T-B2 |
metadata |
source, image_sha256, defect_type, gold_letter, panel_tags, area_pct |
Provenance
Built deterministically (no LLM/teacher; reasoning is null) from AI4Manufacturing/188
— MSD mobile-phone-screen inspection — 1,220 photos, 3 defect types (oil, scratch, stain) + good; each anomalous image has a paired binary pixel segmentation mask (binarized from the palette mask at index>0 (the source encodes defect TYPE in the palette index, so LOCATION comes from the mask and TYPE from metadata)).
Generator: annotate/188/build_188_derived.py in forge_model; machine gates
annotate/188/verify_188.py (all green at build: boxes/gold re-derived byte-identical, clean
regions contain zero defect pixels, mcq gold = the true panel, no leaked-artifact vocabulary, image
set sha256-disjoint from all other cached AI4Manufacturing datasets).
Resolution. Images are native 1920×1080 (not downscaled — preserves thin scratches); all coordinates live in that pixel space (see metadata.image_wh).
Query diversity. query is drawn from a fixed pool of surface variants (paraphrases preserving
the task + answer format), selected by an independent per-record hash; a machine gate confirms no
template correlates with the gold.
The repository name is an internal task code (the source dataset's code is
188).
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