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README.md

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+---
+license: mit
+---
+
+# ArteFact JSON Dataset
+
+A structured metadata collection containing comprehensive information about artworks, creators, topics, and sentence-level annotations from the ArteFact art historical corpus.
+
+## Dataset Overview
+
+This dataset provides the foundational metadata and structured information that powers the ArteFact AI research platform. It contains 5 essential JSON files that enable cross-referencing between visual artworks, scholarly texts, and semantic embeddings.
+
+## 🏗️ Data Structure
+
+```markdown
+artefact-json/
+├── creators.json      # Artist and creator information
+├── sentences.json     # Sentence-level annotations and metadata
+├── topic_names.json   # Human-readable topic labels
+├── topics.json        # Topic categorization and relationships
+└── works.json         # Artwork metadata and descriptions
+```
+
+##  Dataset Statistics
+
+- **Total Files**: 5 JSON files
+- **Total Size**: ~1.2 GB
+- **Data Coverage**: 7,200+ artworks and associated metadata
+
+### File Details
+
+| File | Size | Description | Records |
+|------|------|-------------|---------|
+| `creators.json` | 850 KB | Artist and creator information | Creator profiles |
+| `sentences.json` | 1.18 GB | Sentence-level annotations | Sentence metadata |
+| `topic_names.json` | 549 B | Human-readable topic labels | Topic mappings |
+| `topics.json` | 1.85 MB | Topic categorization | Topic relationships |
+| `works.json` | 8.5 MB | Artwork metadata | Work descriptions |
+
+##  Data Schema
+
+### `creators.json`
+Contains biographical and professional information about artists, architects, and other creators referenced in the corpus.
+
+### `sentences.json`
+The largest file containing sentence-level metadata, annotations, and cross-references between textual content and visual artworks.
+
+### `topic_names.json`
+Human-readable labels for topic categories, enabling semantic search and filtering across the corpus.
+
+### `topics.json`
+Hierarchical topic relationships and categorization data for organizing and filtering art historical content.
+
+### `works.json`
+Comprehensive metadata about individual artworks, including titles, dates, materials, dimensions, and provenance information.
+
+## 🚀 Usage
+
+This dataset is designed to work in conjunction with:
+- **`samwaugh/artefact-embeddings`** - Vector embeddings for semantic search
+- **`samwaugh/artefact-markdown`** - Source scholarly texts and images
+
+### Example Use Cases
+- **Metadata-driven search** and filtering
+- **Cross-referencing** between artworks and scholarly texts
+- **Topic modeling** and categorization analysis
+- **Creator relationship** mapping and analysis
+- **Art historical research** and data mining
+- **AI training** for art understanding models
+
+##  Data Relationships
+
+The JSON files are interconnected through shared identifiers:
+- **Work IDs** (e.g., `W1009740230`) link works to their metadata
+- **Creator IDs** connect artists to their works and biographical data
+- **Topic IDs** enable categorization and semantic organization
+- **Sentence IDs** provide granular access to textual content
+
+## 📖 Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@dataset{artefact_json_2024,
+  title={ArteFact JSON Dataset},
+  author={Waugh, Samuel},
+  year={2024},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/samwaugh/artefact-json}
+}
+```
+
+## 🔗 Related Resources
+
+- **ArteFact Platform**: [samwaugh/artefact](https://huggingface.co/spaces/samwaugh/artefact)
+- **Embeddings Dataset**: [samwaugh/artefact-embeddings](https://huggingface.co/datasets/samwaugh/artefact-embeddings)
+- **Markdown Dataset**: [samwaugh/artefact-markdown](https://huggingface.co/datasets/samwaugh/artefact-markdown)
+
+## 📄 License
+
+This dataset is released under the MIT License. See the [LICENSE](LICENSE) file for details.
+
+## Contributing
+
+This dataset is part of the larger ArteFact project. For questions, issues, or contributions, please refer to the main ArteFact repository.
+
+---
+
+*Part of the ArteFact AI Research Platform - Bridging Visual Art and Textual Scholarship*