--- pretty_name: Causals Graph license: cc-by-4.0 task_categories: - graph-ml tags: - knowledge-graph - news - events - causality - graph configs: - config_name: nodes data_files: - split: snapshot path: v0.1.0-2026-10-09/nodes.jsonl.gz - config_name: edges data_files: - split: snapshot path: v0.1.0-2026-10-09/edges.jsonl.gz --- # Causals Graph A versioned, news-derived graph snapshot from **Causals Lab**. Version `v0.1.0-2026-10-09` contains 369,184 nodes and 1,272,418 directed edges. The graph contains descriptive and contextual relationships as well as extracted causal *claims*. It is **not** a collection of independently verified causal effects; a graph path is not automatically a causal path. This Hugging Face copy mirrors the [canonical GitHub release](https://github.com/causals-lab/community/tree/graph-v0.1.0-2026-10-09/data/v0.1.0-2026-10-09). The [Causals Lab download page](https://causals.org/download/) gives an overview. Use the snapshot version and SHA-256 hashes in `manifest.json` to identify the exact data. The two Viewer configurations, `nodes` and `edges`, are tables from the same graph snapshot; join an edge's `source_id` and `target_id` to node `id`. ## Get started in 10 minutes Try the [runnable notebook](https://github.com/causals-lab/community/blob/main/quickstart/quickstart.ipynb) or [open it in Colab](https://colab.research.google.com/github/causals-lab/community/blob/main/quickstart/quickstart.ipynb). It uses a [small downloadable sample](https://github.com/causals-lab/community/tree/main/quickstart/sample) of 62 nodes and 9 edges selected from this exact release. It checks file hashes, joins edges to nodes, and inspects source-news IDs without requiring private code, a database, or an API key. The selected sample is not representative and does not establish causal effects. ## Files The folder `v0.1.0-2026-10-09/` contains: - `nodes.jsonl.gz` — 369,184 UTF-8 JSONL records, gzip-compressed. - `edges.jsonl.gz` — 1,272,418 UTF-8 JSONL records, gzip-compressed. - `manifest.json` — counts, relation distribution, file sizes and SHA-256 hashes. - `DATA_CARD.md` — schema, provenance, limitations and quality cautions. - `LICENSE_DATA.md` — dataset reuse terms. Read [the complete data card](./v0.1.0-2026-10-09/DATA_CARD.md) before interpreting relations or publishing analysis. In particular, `MENTIONS` is not causal; `OTHER` is unclassified; and `TRIGGERED` or `STATED_CAUSE` are extracted or attributed claims, not independent intervention evidence. The snapshot has no representative whole-graph causal-validity estimate. ## License, attribution and corrections The released dataset is offered under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Attribute **Causals Lab**, identify the version, link to the source and license, and indicate changes. This license applies only to rights the publisher can grant in the released files; it does not license third-party news content, private software, trademarks, or privacy/publicity rights. Suggested citation: > Causals Lab. (2026). *Causals Graph* (v0.1.0-2026-10-09) [Data set]. > https://github.com/causals-lab/community/tree/graph-v0.1.0-2026-10-09/data/v0.1.0-2026-10-09 For data corrections or removal concerns, write privately to **data@causals.org**. Do not post personal or sensitive details in a public issue.