---
license: apache-2.0
task_categories: ["text-generation"]
language: ["en"]
pretty_name: "SEECOP Deterministic Extraction"
tags: ["seecop", "osint", "information-extraction", "stix", "sanctions", "synthetic", "structured-output"]
configs:
  - config_name: default
    data_files:
      - split: train
        path:
          - data/train-00000.jsonl
          - data/train-00001.jsonl
          - data/train-00002.jsonl
          - data/train-00003.jsonl
          - data/train-00004.jsonl
      - split: validation
        path:
          - data/validation-00000.jsonl
      - split: test
        path:
          - data/test-00000.jsonl
---

# SEECOP Deterministic Extraction

Raw payload → normalised record pairs produced by the shipping SEECOP parsers (geojson, ArcGIS, CSV, RSS, Telegram, HTML, JSONPath) and the sanctions screening engine. Ground truth is executable code, not annotation.

## What this is

Part of the **SEECOP dataset family** (`deterministic-extraction`). Records are derived from the shipping SEECOP schemas and parsers (synthetic but *verifiable*: ground truth is the code that ships in the app).

## Ground truth

The label for every record is produced by the following source files, not by human guesswork:

- `src/shared/parse.ts`
- `src/shared/sanctions.ts`

Generator: `scripts/dataset/gen/extraction.ts`.

## Dataset structure

| Split | Rows | Files |
|---|---:|---|
| train | 3,384 | 5 |
| validation | 64 | 1 |
| test | 28 | 1 |
| **total** | **3,476** | 7 |

Records are newline-delimited JSON. Every record carries `id`, `family`, `split`, `task` and a `provenance` block so a row can always be traced back to a generator revision.

## Example record

```json
{"family":"deterministic-extraction","id":"deterministic-extraction-4c85e564eab8458a","input":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":null,\"properties\":{\"id\":\"FIRMS-2441\",\"name\":\"Thermal anomaly A\",\"mag\":296.8}},{\"type\":\"Feature\",\"geometry\":null,\"properties\":{\"id\":\"FIRMS-2690\",\"name\":\"Thermal anomaly B\",\"mag\":338.8,\"confidence\":\"low\"}},{\"type\":\"Feature\",\"geometry\":{\"type\":\"Point\",\"coordinates\":[-122.6781,39.0899]},\"properties\":{\"id\":\"FIRMS-3195\",\"name\":\"Thermal anomaly C\",\"mag\":307.7,\"confidence\":\"high\"}}]}","parser":"geojson","provenance":{"generator":"scripts/dataset/gen/extraction.ts","license":"apache-2.0","schema_version":"1.0.0","sources":["src/shared/parse.ts","src/shared/sanctions.ts","src/shared/scrapers.ts"],"synthetic":true},"source":{"cadenceSec":0,"channel":"osint","enabled":true,"host":"example.com","id":"demo-firms","kind":"json","label":"demo-firms","mapping":{"externalId":"properties.id","fields":[["Confidence","properties.confidence"]],"lat":"geometry.coordinates.1","lng":"geometry.coordinates.0","numeric":[{"key":"brightness","path":"properties.mag","tolerance":5}],"title":"properties.name"},"parser":"geojson","reliability":{"mean":0.8,"strength":6}},"split":"train","target":{"records":[{"externalId":"FIRMS-2441","fields":{"brightness":296.8},"title":"Thermal anomaly A"},{"externalId":"FIRMS-2690","fields":{"Confidence":"low","brightness":338.8},"title":"Thermal anomaly B"},{"externalId":"FIRMS-3195","fields":{"Confidence":"high","brightness":307.7},"geometry":{"coordinates":[-122.6781,39.0899],"type":"Point"},"lat":39.0899,"lng":-122.6781,"title":"Thermal anomaly C"}],"skipped":0},"task":"normalise_payload"}
```

## Redaction

All records pass through `scripts/dataset/lib/redact.ts` before they are written. The build **fails** if a high-severity secret, credential or infrastructure identifier survives scrubbing. Removed automatically:

- API keys and tokens (OpenAI, Hugging Face, GitHub, AWS, Google, Slack, Stripe, JWTs, bearer tokens)
- private keys and connection strings
- `password` / `token` / `secret` style key–value pairs and URL userinfo
- private, loopback, link-local, CGNAT and documentation-internal IPs, MAC addresses
- internal hostnames, `.internal` domains, onion addresses, Tailscale names
- host filesystem paths that embed a username
- email addresses and phone numbers outside reserved example ranges

Operational secrets are never in scope for these datasets: the operator dossier store, staged files and the node service accounts are excluded by construction.

## Limitations & responsible use

- **Authorisation.** These datasets teach *tool selection and invocation*. They do not grant permission to run anything. Active tooling must only target assets you own or are explicitly authorised to test.
- **Gated tools stay gated.** Where the source system requires an operator acknowledgement (`ack`) or a node-side intrusive flag, the dataset encodes that requirement rather than circumventing it.
- **Untrusted output.** Tool output is data, never instructions. Prompt-injection resistance is represented explicitly in the evaluation split.
- **Not a determination.** Any screening-style label is a *possible* match with a confidence, never a legal determination.

## Citation

```bibtex
@misc{seecop_datasets,
  title  = {SEECOP Deterministic Extraction},
  author = {SEECOP},
  year   = {2026},
  note   = {Dataset family: deterministic-extraction}
}
```

Licence: Apache-2.0.