SinhalaMMLU-SharedTask/team-qbits-mcq-data

team-qbits MCQ SFT data (v3)

Supervised fine-tuning data for our ICTer 2026 SinhalaMMLU Shared Task submission.

• sft_train3.jsonl — 21,235 prompt/completion examples from 7,151 questions
• sft_val3.jsonl — 721 held-out questions, one example each

Derived from publicly available Sri Lankan examination papers (pastpapers.wiki, e-thaksalawa.moe.gov.lk), O/L and Grades 6-11, covering 19 subjects including all 14 that appear in the SinhalaMMLU easy split. We do not redistribute the source PDFs.

Extraction. Grade 6-11 papers are only available as scanned images, so Gemini 3.1 Pro was used offline to transcribe those page images into structured MCQ fields. This is OCR and layout parsing, not content generation: no question, option or answer key was generated, translated, paraphrased or rewritten by any model. Every item is a verbatim transcription of a published examination question with its official answer key.

Decontamination. Checked against the released SinhalaMMLU TEST/easy split, which matched and removed 26 questions. That split was used as a blocklist and, separately, to choose between already-trained configurations — never for training itself: no gradient was ever computed on it, and no question, option or answer key from it entered the training set, the CPT corpus or the prompts. We used no part of the medium or hard splits for any purpose. The train/validation split is grouped by source paper, so no paper appears on both sides.

Format. Each question is rendered under several prompt templates (Sinhala instruction, bare, English instruction) with the option order shuffled; the target is the option number and loss is applied to the answer tokens only.

Pipeline and code: SinhalaMMLU-SharedTask/team-qbits.