---
pretty_name: Glyph Datasets
license: apache-2.0
language:
  - en
task_categories:
  - image-to-text
size_categories:
  - 100K<n<1M
tags:
  - chemistry
  - cheminformatics
  - ocsr
  - markush
  - chemical-structure-recognition
  - smiles
  - cxsmiles
configs:
  - config_name: markush-train
    data_files:
      - split: train
        path: markush/train.jsonl
---

# glyph-datasets

Data artifacts for **Glyph** — chemical-structure transcription with two models:
**OCSRGlyph** (molecule image → SMILES) and **MarkushGlyph** (patent Markush
image → CXSMILES + R-group table). This repository holds the training indices,
training metadata, and the frozen self-contained evaluation benchmarks that the
`glyph` package auto-downloads.

- **Code:** `EdisonScientific/glyph` (GitHub)
- **Weights:** `EdisonScientific/OCSRGlyph`, `EdisonScientific/MarkushGlyph`
- **License:** Apache-2.0. See [License](#license).
- **Citation:** TBD — the BibTeX entry and arXiv identifier will be added on
  release. See [Citation](#citation).

## Redistribution classes

Artifacts fall into three classes; every subdirectory `README.md` /
`*.provenance.json` sidecar records the class per file.

- **(a) Referenced upstream** — pulled from the pinned public source at load
  time and not re-hosted here (the raw OCSR training images, the MolNexTR CSVs,
  the raw Markush source images).
- **(b) Transformed metadata** — derived label / index / subset files (SMILES +
  relative paths, the mined `adjacent_ring` subset, the flat Markush training
  index). These carry no upstream image bytes.
- **(c) Embedded copies** — the frozen self-contained eval parquets, which *do*
  embed the benchmark images and labels so `glyph … eval` runs with no local
  reconstruction: the **5,719** OCSR benchmark images
  (`ocsr/uspto_ocsr_benchmark.parquet`) and the **1,055** Markush eval images
  (878 + 103 + 74 across the three `markush-eval/*` parquets). These images are
  public-domain USPTO patent depictions / the pinned public MarkushGrapher-2
  benchmark; they are re-hosted only inside these frozen benchmark copies.

## Artifact map

| Path | Rows | Class | Purpose |
|---|---|---|---|
| `ocsr/uspto_ocsr_5719_complete.csv` | 5,719 | (b) | USPTO-OCSR-5719 complete labels (label sidecar). |
| `ocsr/uspto_ocsr_benchmark.parquet` | 5,719 | (c) | Frozen self-contained OCSR benchmark (images + labels embedded); the file `glyph ocsr eval` downloads. |
| `ocsr/adjacent_ring.csv` | 64,752 | (b) | This work: pure-logic mined subset of PubChem-1M (OCSR enrichment). |
| `ocsr/stereo_200k/{train,val}.csv` | 200,000 / 2,000 | (b) | Stereo-200K SMILES + relative image paths (images re-fetched). |
| `ocsr/stereo_200k_white/{train,val}.csv` | 200,000 / 2,000 | (b) | White-cropped Stereo-200K variant (this work's preprocessing). |
| `ocsr/ocsrglyph-recipe.json` | — | — | OCSRGlyph training recipe (hyperparameters). |
| `markush/train.jsonl` | 263,158 | (b) | Frozen flat MarkushGlyph training index (exact order, repeats intact). |
| `markush/manifest.json` | — | — | Flat-index metadata (schema, counts, source revisions, integrity). |
| `markush-eval/ip5m/ip5m_benchmark.parquet` | 878 | (c) | Frozen self-contained IP5-M eval benchmark (images embedded). |
| `markush-eval/ip5m/ds4sd_mg2_predictions_878.jsonl` | 878 | (b) | DS4SD MarkushGrapher-2's own IP5-M eval output: ground truth + MG2 baseline. |
| `markush-eval/m2s/m2s_benchmark.parquet` | 103 | (c) | Frozen self-contained M2S eval benchmark (images embedded). |
| `markush-eval/m2s/ds4sd_mg2_gt_103.jsonl` | 103 | (b) | Derived M2S ground truth for the official DS4SD scorer. |
| `markush-eval/uspto_markush/uspto_markush_benchmark.parquet` | 74 | (c) | Frozen self-contained USPTO-Markush eval benchmark (images embedded). |
| `markush-eval/uspto_markush/ds4sd_mg2_gt_74.jsonl` | 74 | (b) | Derived USPTO-Markush ground truth for the official DS4SD scorer. |

Every data artifact has a companion `*.provenance.json` (source repo + pinned
revision, transformation, counts, integrity hash). Row counts are data rows;
each CSV also carries a 1-line header.

## Per-artifact schemas

**OCSR**

- `uspto_ocsr_5719_complete.csv` — `image_id, smiles, source_of_label`.
- `uspto_ocsr_benchmark.parquet` — `id, image (struct<bytes, path>), mol,
  smiles, selfies, inchi, source_of_label`; image bytes present for all 5,719
  rows, zero null SMILES.
- `adjacent_ring.csv` — `pubchem_cid, InChI, SMILES, num_atoms`.
- `stereo_200k/*.csv`, `stereo_200k_white/*.csv` — `SMILES, file_path` (relative
  image path; images re-fetched from `Robert-zwr/Stereo-200k`).

**Markush**

- `train.jsonl` — one JSON object per line: `source`, `source_id`, `images`
  (list of `images/<source>/train/<source_id>.png`), `messages` (a `user` +
  `assistant` chat turn). See `manifest.json` for the full contract, per-source
  counts, and source revisions.

**Markush eval**

- `*_benchmark.parquet` — `id, image (struct<bytes, path>), benchmark, record`
  (`record` is the JSON of the prepared eval row); image bytes present for all
  rows.
- `ip5m/ds4sd_mg2_predictions_878.jsonl` — `id, cxsmiles` (MG2 baseline
  prediction), `cxsmiles_opt, gt_cxsmiles` (DS4SD ground truth; 8 unparseable
  rows kept as null), `gt_cxsmiles_opt`.
- `m2s/ds4sd_mg2_gt_103.jsonl`, `uspto_markush/ds4sd_mg2_gt_74.jsonl` — `id,
  gt_cxsmiles, gt_cxsmiles_opt` (derived ground truth; no MG2 baseline column,
  since no DS4SD model run is published for these two benchmarks).

## Usage

The `glyph` package resolves these artifacts automatically — no manual
`huggingface-cli` step.

```bash
# OCSR headline: the benchmark parquet auto-downloads from this repo.
uv run glyph ocsr eval --checkpoint EdisonScientific/OCSRGlyph --output uspto5719.json

# Markush: the self-contained benchmark auto-downloads; STEP 2 auto-pulls the
# matching ground truth from markush-eval/<name>/.
uv run glyph markush eval benchmark --benchmark ip5m \
    --checkpoint EdisonScientific/MarkushGlyph --base-model Qwen/Qwen3.5-2B-Base \
    --output preds.json
tools/mg2_scorer/score_benchmark.sh --benchmark ip5m --input-json preds.json

# Markush training: the flat index auto-downloads with hub:markush/train.jsonl.
uv run python -m glyph.markush.train.sft \
    --config configs/ablations/ocsr-as-markush-fraction/sft_2b_markush_ocsr5pct.yaml \
    --data-path hub:markush/train.jsonl
```

See the code repository's `REPRODUCE.md` for the exact commands, expected
counts, pinned revisions, and both Markush scoring contracts.

## License

Apache-2.0 (same as the code repository). Each referenced upstream source keeps
its own license — see the per-subdirectory
`README.md` and `*.provenance.json` sidecars for attribution (PubChem, MolNexTR,
MolSight/Stereo-200K, MolScribe, `hheiden/USPTO_OCSR_benchmark`,
`docling-project/MarkushGrapher-Datasets` and `-2-Datasets`,
`UniParser/MolParser-7M`). The embedded benchmark images are public-domain USPTO
patent depictions / the pinned public MarkushGrapher-2 benchmark.

## Citation

TBD. This data accompanies the paper *Chemical Structure Transcription Across
Molecules*; the BibTeX entry and arXiv identifier will be added on release.