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license: mit
task_categories:
- text-classification
- other
language:
- en
tags:
- cold-case
- unsolved-murders
- forensic-analytics
- crime-dataset
- pecd5
size_categories:
- n<1K
---
# PEC5D Cold-Case Grid — dataset
Structured dataset for the PEC5D Photonic Entanglement 5D Cold-Case
Grid: 32 documented unsolved cases (1900s–present) with model-input
scores, plus entity-layer exports (characters, timelines, scenarios).
**Ethics:** hypothesis lattice only. Not legal evidence. No
accusations. Sources are public OSINT classes only.
## Files
| File | Content |
|---|---|
| `cases.json` | 32 cases: year, lat/lon, type, evidence/motive/jurisdiction/body/genetic/severity/status scores, entity tags, descriptions |
| `characters.json` | Named people (victims, suspects, POIs, witnesses) with roles and case bindings |
| `timelines.json` | Per-case dated events |
| `scenarios.json` | Hypothesis-lattice scenario variants with plausibility weights |
## Schema (cases.json)
```json
{
"case_id": "zodiac_1968",
"name": "The Zodiac Killer",
"year": 1968,
"lat": 37.7749,
"lon": -122.4194,
"case_type": "serial",
"evidence": 6, // E_i in [0,10]
"motive": 2, // M_i in [0,10]
"jurisdiction": 7, // J_i in [0,10]
"body": 1, // B_i in {0, 0.5, 1}
"genetic": 0, // G_i in {0, 1}
"severity": 0.95, // public impact
"status": 0, // S_i in {0, 0.5, 1}
"entities": ["cipher", "letters", "..."],
"description": "..."
}
```
## Usage
```python
from datasets import load_dataset
ds = load_dataset("Codexcoder/pec5d-cold-case-grid", split="train")
```
## Credit
Derived from publicly documented events; structured as model inputs for
the PEC5D grid (github.com/onegayunicorn/deepseek-v4-sovereign).
|