# DocMIDE

Document images paired with question/answer pairs that require **implicit reasoning** over the document — deriving, cross-referencing, or computing a value — rather than plain OCR transcription. This is the held-out test split used by the [DocMIDE Benchmark](https://github.com/VXRealLimited/DocMIDE-Benchmark) eval harness; the reasoning-annotated training splits (with raw field data and derivation traces, used for SFT/GRPO) live in the [DocMIDE](https://github.com/VXRealLimited/DocMIDE) training repo.

Most document images are real-world documents sourced from the Unikie benchmark (MIT licensed); the `Synthetic` category is procedurally generated and not derived from Unikie. This dataset (questions, answers, and synthetic images) is released under CC-BY-4.0; the `images/real/` subset remains additionally subject to Unikie's MIT license and attribution requirement.

## Dataset structure

`test.jsonl` is a doc-level JSONL file: one line per document image, with a list of `samples` (question/answer pairs) for that document.

```json
{
  "doc_id": "91814768_91814769",
  "image": "images/real/91814768_91814769.png",
  "category": "Administrative",
  "samples": [
    {
      "id": 1,
      "field": "total_to_date_minus_previously_reported",
      "question_type": "derivation",
      "prompt": "This form lists three separate 'Total Expenditures or Disbursements' figures near the bottom: one for This Report, one Previously Reported, and one to Date. By how much does the 'to Date' total exceed the 'Previously Reported' total? Answer with the number only — no currency symbols, commas, or units.",
      "field_present": true,
      "answer": "48085.00"
    }
  ]
}
```

**Fields per sample:**

| Field | Description |
|---|---|
| `id` | Sample index within the document. |
| `field` | Short identifier for the field/value the question targets. |
| `question_type` | `derivation` (compute/combine values) or `spatial` (reason about layout/position/references within the document). |
| `prompt` | The question posed about the document. |
| `field_present` | Whether the queried field actually exists in the document (always `true` in this split). |
| `answer` | The final answer. |

Document-level fields: `doc_id`, `image` (path relative to this directory), `category` (`Administrative`, `Commercial`, `Advertisement`, `Accommodation`, or `Synthetic`).

## Splits

| Split | Documents | Samples |
|---|---:|---:|
| `test.jsonl` | 3,427 | 4,151 |

Images live under `images/` (3,427 total): `images/real/` (427 real-world documents, JPG) and `images/synthetic/` (3,000 procedurally generated documents, PNG).

## Links

Github:
- [DocMIDE](https://github.com/VXRealLimited/DocMIDE) — training code (SFT + GRPO) that consumes this dataset
- [DocMIDE-Benchmark](https://github.com/VXRealLimited/DocMIDE-Benchmark) — serves and scores checkpoints trained on this dataset