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Datasets:
introspector
/
zkprologml

Tasks:
Other
Modalities:
Tabular
Text
Formats:
parquet
Size:
1M - 10M
Libraries:
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pandas
Polars
License:
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zkprologml / README.md
mike dupont
Add 8M file dataset with Monster Group shards
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metadata 
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 

from datasets import load_dataset

ds = load_dataset("introspector/zkprologml")
print(ds['train'][0])

Links