--- pretty_name: QIMMA-oriented Arabic MCQ Dataset Preview language: - ar license: other task_categories: - question-answering tags: - arabic - multiple-choice - reinforcement-learning - synthetic configs: - config_name: default data_files: - split: train path: training_ready.jsonl --- # QIMMA-oriented Arabic MCQ dataset v1.0 This frozen release contains **477 training-ready Arabic multiple-choice questions**: 81 from the reviewed v2 pilot and 396 newly accepted questions generated with `openai/gpt-oss-120b`. ## Use Use `training_ready.jsonl` as the canonical merged training pool. Each record contains the question, four choices, answer, explanation, source attribution, difficulty, quality adjudication, and release origin. `batch_training_ready.jsonl` contains only the newly added 396 questions. ## Quality and isolation - 500 new candidates were generated. - 396 passed strict final adjudication. - 0 crossed the conservative QIMMA-overlap thresholds. - 0 were flagged as duplicates against the prior pool or batch. - QIMMA prompt text is not included in this release. - Answer positions were deterministically balanced after all filtering. The audit scanned 44,441 benchmark rows using normalized exact matching, fuzzy matching, and multilingual semantic similarity. See `release_manifest.json` for thresholds, distributions, model lineage, and costs. ## Files - `training_ready.jsonl`: canonical 477-item merged dataset. - `batch_training_ready.jsonl`: 396 newly accepted items. - `release_manifest.json`: release counts, distributions, audits, models, and cost. - `review_adjudicated.csv`: final decisions for all 500 new candidates. - `held_out_or_rejected.jsonl`: new candidates excluded by quality review. - `overlap_excluded.jsonl`: items excluded by overlap/duplicate audits, if any. - `contamination_*`: QIMMA similarity audit without benchmark prompt text. - `dataset_duplicate_*`: prior-pool and within-batch duplicate audit. - `pipeline/`: reproducible collection, generation, adjudication, and audit scripts. Reported OpenRouter cost for the new batch was `$1.2916`. Modal compute is not included. Source licensing is recorded per item; preserve attribution.