Datasets:
gold splits: benchmark 777, val, train_dedhi, seed-7
Browse files- README.md +62 -0
- data/benchmark.jsonl +0 -0
- data/train.jsonl +0 -0
- data/train_seed7.jsonl +0 -0
- data/validation.jsonl +0 -0
README.md
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---
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license: apache-2.0
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task_categories:
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- image-text-to-text
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language:
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- en
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pretty_name: Suture
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tags:
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- insurance
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- document-qc
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- policy-issuance
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- synthetic
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- verifier-as-oracle
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configs:
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- config_name: benchmark
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data_files: data/benchmark.jsonl
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- config_name: validation
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data_files: data/validation.jsonl
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- config_name: train
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data_files: data/train.jsonl
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- config_name: train_seed7
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data_files: data/train_seed7.jsonl
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---
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# Suture
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Gold tasks for **policy-issuance QC**: a structured underwriting binder, a structured issued policy, and the exact discrepancy set. Images are **not** stored. Re-render with `suture_forge.generate.render_doc` from the GitHub repo.
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Paper and adapter: [caiotheodoro/suture](https://github.com/caiotheodoro/suture) · [`caiotheodoro/suture-8b`](https://huggingface.co/caiotheodoro/suture-8b). Predictions on this gold: [`caiotheodoro/suture-evals`](https://huggingface.co/datasets/caiotheodoro/suture-evals).
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## Splits
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| Config | Seed | n | What |
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|---|---:|---:|---|
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| `benchmark` | 777 | 1000 | Contracted held-out set. Never in train. |
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| `validation` | 7 holdout | 80 | Val. Optimistic vs 777; `DEDUCTIBLE_HIGHER` gold n=0. |
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| `train` | 7+11+13+17+19+23 | 5120 | Published SFT mix (`train_dedhi`). |
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| `train_seed7` | 7 | 320 | Official stratified split, no class boost. |
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Leakprobe vs val and vs benchmark is **0**. Signature = SHA-256 over sorted ground-truth fields. Build refuses overlap > 0.
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## Row schema
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Each line is a `Task`: `task_id`, `seed`, `binder`, `policy`, `image_*_sha256`, `expected` (`PASS`/`FLAG` + discrepancies), `signature`, `difficulty`. Taxonomy and weights: repo `CONTRACTS.md` (13 classes).
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## Render
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```python
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from datasets import load_dataset
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from suture_forge.schema import Binder, Policy
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from suture_forge.generate import render_doc
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row = load_dataset("caiotheodoro/suture", "benchmark", split="train")[0]
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png = render_doc(Binder.model_validate(row["binder"]), "BINDER",
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row["difficulty"], row["task_id"])
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```
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Linux vs macOS raster can differ (SHA mismatch). Labels do not. Eval in the project re-renders on the GPU host.
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## License / use
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Apache-2.0. Synthetic ACORD-style pages, not real submissions. Form numbers are public ISO ids. Do not treat this as a carrier document corpus.
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data/benchmark.jsonl
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data/train.jsonl
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data/train_seed7.jsonl
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data/validation.jsonl
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