doxa-friend/MolMole_Patent300

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MolMole_Patent300 is a curated benchmark designed to evaluate models that extract chemical information from full-page patent images.
It was introduced in the paper “MolMole: Molecule Mining from Scientific Literature.”

This benchmark enables end-to-end evaluation of chemical information extraction, covering:

• Molecule bounding box detection
• Reaction parsing
• Optical chemical structure recognition (OCSR)

📦 Contents

Folder	Description	Format / Suffix
images_300/	300 full patent pages	.png
json/	Annotations of molecule/text bounding boxes and reactions	patent_300_huggingface.json
mol/	Molfile for each molecule bounding box	.mol

📄 JSON File Structure

dla_bboxes

{
  "id": 0,                          // Unique ID of bbox within the page
  "bbox": [x_min, y_min, w, h],     // Pixel coordinates 
  "category_id": 1                  // 1 = structure, 2 = text
}

reactions

{
  "reactants": [0, 1],   // IDs of reactant bboxes 
  "conditions": [3],     // IDs of condition bboxes 
  "products":  [2]       // IDs of product bboxes
}

🧪 Molfile Naming Rule

Each .mol file is named using the following format:
{PATENT_PAGE_NAME}_bbox_{BBOX_ID}.mol

---

📖 Citation

@misc{research2025molmolemoleculeminingscientific,
    title={MolMole: Molecule Mining from Scientific Literature}, 
    author={LG AI Research and Sehyun Chun and Jiye Kim and Ahra Jo and Yeonsik Jo and Seungyul Oh and Seungjun Lee and Kwangrok Ryoo and Jongmin Lee and Seung Hwan Kim and Byung Jun Kang and Soonyoung Lee and Jun Ha Park and Chanwoo Moon and Jiwon Ham and Haein Lee and Heejae Han and Jaeseung Byun and Soojong Do and Minju Ha and Dongyun Kim and Kyunghoon Bae and Woohyung Lim and Edward Hwayoung Lee and Yongmin Park and Jeongsang Yu and Gerrard Jeongwon Jo and Yeonjung Hong and Kyungjae Yoo and Sehui Han and Jaewan Lee and Changyoung Park and Kijeong Jeon and Sihyuk Yi},
    year={2025},
    eprint={2505.03777},
    archivePrefix={arXiv},
    primaryClass={cs.LG},
    url={https://arxiv.org/abs/2505.03777}, 
  }

📄 License

This dataset is released under the CC-BY-NC-ND-4.0 License.

Disclaimer

Out of 550 total pages used for evaluation in the MolMole paper, only 300 (from patents) are publicly released here.
The remaining 250 pages are excluded from this release due to copyright limitations.