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README.md
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- provenance
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- graph
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- PROV-DM
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- provenance
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- graph
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- PROV-DM
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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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---
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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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---
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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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## 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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## Citation
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If you use MatPROV, please cite:
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```
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TBD
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```
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