PolitiCause
Intra-sentence No Polarity Signal No Strength Signal
PolitiCause annotates causal relations in political speech transcripts — UN General Debate statements and UK government press conferences — focusing on the domain-specific challenges of political discourse such as attribution, hedging, and complex multi-clause sentences.
Unlike its own paper (which only reports sentence-level classification results), causal-candidate-extraction and causality-identification here are derived from the dataset's underlying multi-annotator span file, reconciled into a single canonical cause/effect pair per sentence — see the conversion script's module docstring for the exact reconciliation policy and its ~9% coverage loss from genuinely incomplete source annotations.
Overview
| Domain | Politics |
| Year | 2024 |
| Sentences | 17,780 |
| Granularity | Intra-sentence |
Tasks & Splits
| Task | Train | Test |
|---|---|---|
| Causality Detection | — | — |
| Causal Event Candidate Extraction | — | — |
| Causality Identification | — | — |
| Causality Extraction | — | — |
Citation
@inproceedings{corral:2024,
title = {{{PolitiCause}}: {{An Annotation Scheme}} and {{Corpus}} for {{Causality}} in {{Political Texts}}},
shorttitle = {{{PolitiCause}}},
booktitle = {Proceedings of the 2024 {{Joint International Conference}} on {{Computational Linguistics}}, {{Language Resources}} and {{Evaluation}}, {{LREC}}/{{COLING}} 2024, 20-25 {{May}}, 2024, {{Torino}}, {{Italy}}},
author = {Corral, Paulina Garcia and B{\'e}chara, Hanna and Zhang, Ran and Jankin, Slava},
editor = {Calzolari, Nicoletta and Kan, Min-Yen and Hoste, V{\'e}ronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen},
year = 2024,
pages = {12836--12845},
publisher = {{ELRA and ICCL}},
url = {https://aclanthology.org/2024.lrec-main.1124},
urldate = {2025-02-08}
}