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--- |
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license: cc-by-4.0 |
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language: |
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- en |
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tags: |
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- materials-science |
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- provenance |
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- graph |
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- PROV-DM |
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- information-extraction |
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pretty_name: MatPROV |
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--- |
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# MatPROV |
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**MatPROV** is a dataset of materials synthesis procedures extracted from scientific papers using large language models (LLMs) and represented in [PROV-DM](https://www.w3.org/TR/prov-dm/)–compliant structures. |
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Further details on MatPROV are described in our paper "[MatPROV: A Provenance Graph Dataset of Material Synthesis Extracted from Scientific Literature](https://arxiv.org/abs/2509.01042).” |
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--- |
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## Files |
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``` |
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MatPROV/ |
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├── MatPROV.jsonl # Main dataset (2,367 synthesis procedures) |
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├── ground-truth/ # Expert-annotated ground truth |
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│ └─ <DOI>.json |
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├── few-shot/. # Prompt examples used for synthesis procedure extraction |
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│ └─ <DOI>.txt |
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└── doi_status.csv # Status of each paper DOI across the pipeline |
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``` |
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*Note: In file names under `ground-truth/` and `few-shot/`, forward slashes (`/`) in DOIs are replaced with underscores (`_`).* |
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--- |
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## Data format |
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The main dataset file is `MatPROV.jsonl`, where each line corresponds to one paper’s structured record. |
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Each record contains: |
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- `doi`: DOI of the source paper |
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- `label`: Identifier for the extracted synthesis procedure, encoding the material's chemical composition and key synthesis characteristics (e.g., `CuGaTe2_ball-milling`) |
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- `prov_jsonld`: A PROV-JSONLD structure describing the synthesis procedure |
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### Example |
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```json |
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{ |
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"doi": "10.1002/advs.201600035", |
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"label": "Fe1+xNb0.75Ti0.25Sb_composition variation", |
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"prov_jsonld": { |
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"@context": [ |
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{"xsd": "http://www.w3.org/2001/XMLSchema#", "prov": "http://www.w3.org/ns/prov#"}, |
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"https://openprovenance.org/prov-jsonld/context.jsonld", |
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"URL of MatPROV's context schema omitted for double-blind review" |
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], |
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"@graph": [ |
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{ |
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"@type": "Entity", |
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"@id": "e1", |
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"label": [{"@value": "Fe", "@language": "EN"}], |
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"type": [{"@value": "material"}], |
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"matprov:purity": [{"@value": "99.97%", "@type": "xsd:string"}] |
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} |
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... |
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] |
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} |
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} |
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``` |
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## Visualization |
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You can visualize the PROV-JSONLD data in MatPROV using the online tool at: https://matprov-project.github.io/prov-jsonld-viz/ |
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To do this, copy the value of the `"prov_jsonld"` field from any record in `MatPROV.jsonl` and paste it into the “PROV-JSONLD Editor” panel of the tool. |
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A directed graph of the synthesis procedure will then be generated, as shown in the figure below. |
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## Dataset construction summary |
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- Source papers collected: 1648 |
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- **Relevant Text Extraction** |
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- 32 papers contained no synthesis-related text |
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- → 1616 papers remained |
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- **Synthesis Procedure Extraction** |
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- 48 papers contained no synthesis procedure |
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- → 1568 papers remained (final dataset) |
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The DOIs of these 1568 papers and their extracted data are included in `MatPROV.jsonl`. |
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For details on the filtering status of each DOI, see `doi_status.csv`. |
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## Ground Truth annotations |
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- A subset of papers was manually annotated by a single domain expert. |
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- Files are stored in `ground-truth/` and named as `<DOI>.json`. |
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## Few-shot examples |
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- Prompt examples used for LLM extraction are provided in `few-shot/`. |
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- Files are stored in `few-shot/` and named as `<DOI>.txt`. |
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## Links |
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- Paper: https://arxiv.org/abs/2509.01042 |
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- Code: https://github.com/MatPROV-project/matprov-experiments |
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## Citation |
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If you use MatPROV, please cite: |
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``` |
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@inproceedings{tsuruta2025matprov, |
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title={Mat{PROV}: A Provenance Graph Dataset of Material Synthesis Extracted from Scientific Literature}, |
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author={Hirofumi Tsuruta and Masaya Kumagai}, |
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booktitle={NeurIPS 2025 Workshop on AI for Accelerated Materials Design}, |
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year={2025} |
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} |
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``` |
