FinCausal 2020 (FinCausal-20)

Inter-sentence (whole document/section) No Polarity Signal No Strength Signal

FinCausal annotates causal relations in financial disclosures and news, targeting quantified facts where a cause leads to a measurable financial effect. Converted directly from the FNP 2020 shared task organizers' own repository, using only the "practice" (train) and "trial" (test) splits — the "evaluation" split is an unlabeled blind test set that was never republished with gold labels.

Each row is a whole text section (see the granularity pill above), not a single sentence: causal relations can genuinely span multiple sentences within one section, so a per-sentence schema would risk dropping or corrupting them — the same reasoning already applied to BioCause and TCR.

Overview

Domain	Finance
Year	2020
Sentences	22,058
Granularity	Inter-sentence (whole document/section)

Tasks & Splits

Task	Train	Test
Causality Detection	—	—
Causal Event Candidate Extraction	—	—
Causality Identification	—	—
Causality Extraction	—	—

Citation

@inproceedings{mariko:2020,
  title = {The Financial Document Causality Detection Shared Task ({{FinCausal}} 2020)},
  booktitle = {Proceedings of the 1st Joint Workshop on Financial Narrative Processing and {{MultiLing}} Financial Summarisation},
  author = {Mariko, Dominique and {Abi-Akl}, Hanna and Labidurie, Estelle and Durfort, Stephane and De Mazancourt, Hugues and {El-Haj}, Mahmoud},
  editor = {{El-Haj}, Dr Mahmoud and Athanasakou, Dr Vasiliki and Ferradans, Dr Sira and Salzedo, Dr Catherine and Elhag, Dr Ans and Bouamor, Dr Houda and Litvak, Dr Marina and Rayson, Dr Paul and Giannakopoulos, Dr George and Pittaras, Nikiforos},
  year = 2020,
  month = dec,
  pages = {23--32},
  publisher = {COLING},
  address = {Barcelona, Spain (Online)},
  url = {https://aclanthology.org/2020.fnp-1.3/}
}