CauseNet

CauseNet is a large-scale causality graph extracted from web and Wikipedia text, mapping cause concepts to effect concepts with supporting evidence for each relation.

from causalatee.graph import load_causenet

# The official CauseNet-precision release; `limit` bounds how many edges load eagerly.
graph = load_causenet(
    "https://groups.uni-paderborn.de/wdqa/causenet/causality-graphs/causenet-precision.jsonl.bz2",
    limit=10_000,
)

rain = graph.get_node("rain")
for edge in rain.outgoing_edges():
    print(edge.target.id, edge.metadata["support"])

Citation

@inproceedings{heindorf:2020,
  title = {{{CauseNet}}: {{Towards}} a {{Causality Graph Extracted}} from the {{Web}}},
  shorttitle = {{{CauseNet}}},
  booktitle = {Proceedings of the 29th {{ACM International Conference}} on {{Information}} \& {{Knowledge Management}}},
  author = {Heindorf, Stefan and Scholten, Yan and Wachsmuth, Henning and Ngonga Ngomo, Axel-Cyrille and Potthast, Martin},
  year = 2020,
  month = oct,
  pages = {3023--3030},
  publisher = {ACM},
  address = {Virtual Event Ireland},
  doi = {10.1145/3340531.3412763},
  url = {https://dl.acm.org/doi/10.1145/3340531.3412763},
  urldate = {2024-07-02},
  isbn = {978-1-4503-6859-9},
  langid = {english}
}