| license: mit | |
| task_categories: | |
| - other | |
| size_categories: | |
| - 1M<n<10M | |
| # zkPrologML Dataset | |
| Complete indexed filesystem analysis with Monster Group shard assignments. | |
| ## Dataset Description | |
| - **Files**: 8,017,192 indexed files | |
| - **Size**: 250MB parquet | |
| - **Columns**: 16 (path, godel, shard, natural_class, eigenvector_sum, etc.) | |
| - **Shards**: 71 (Monster Group partitions) | |
| ## Data Fields | |
| - `path`: File path | |
| - `godel`: Gödel number | |
| - `shard`: Monster Group shard (0-70) | |
| - `natural_class`: Classification (very_low, low, medium, high, very_high) | |
| - `eigenvector_sum`: Sum of eigenvector components | |
| - `meaning`: Semantic meaning | |
| - `usage`: Usage description | |
| - `labels`: Classification labels | |
| ## Natural Classes | |
| - very_low: 25.19% | |
| - low: 25.32% | |
| - medium: 24.65% | |
| - high: 20.40% | |
| - very_high: 4.44% | |
| ## Correlations | |
| - Gödel ↔ Shard: 1.000 (perfect!) | |
| - Eigenvector sum ↔ Gödel: 0.996 | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("introspector/zkprologml") | |
| print(ds['train'][0]) | |
| ``` | |
| ## Links | |
| - Dashboard: https://huggingface.co/spaces/introspector/zkprologml | |
| - GitHub: https://github.com/meta-introspector/zkprologml | |