dataset_info:
features:
- name: images
list:
image:
decode: false
- name: image_group_id
dtype: string
- name: qa
list:
- name: inputs
dtype: string
- name: labels
dtype: int64
- name: metadata
dtype: string
- name: choices_list
list: string
splits:
- name: test
num_bytes: 256660459
num_examples: 6186
- name: train
num_bytes: 2286302065
num_examples: 49820
download_size: 2543457015
dataset_size: 2542962524
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: train
path: data/train-*
license: mit
source_datasets:
- OpenMOSS-Team/GameQA-140K
gameqa
GameQA native multiple-choice questions, with original screenshot bytes.
Full native train/test JSON and image archives are joined once. Open-ended questions are omitted; no distractors are generated. Options retain source order, equivalent duplicates collapse, and gold indices are remapped. Embedded option blocks are removed before Jev permutation. Screenshots are grouped across QAs and test images take precedence over training copies. Image groups are shuffled within each native split with seed 0; QA order is retained. Procedural game labels are used; generated rationales are excluded from inputs. Original source declares MIT. No validation split is fabricated.
Original data: OpenMOSS-Team/GameQA-140K. Repackaged as parquet for tasksource by scripts/repackage_dataset/games.py.
Conversion provenance: source revisions, hashes, configuration and exclusions.