UniCausal
Intra-sentence
UniCausal is a unified benchmark that harmonises twelve existing causal NLP datasets into a single repository with consistent annotation schema, enabling cross-dataset training and fair multi-corpus evaluation.
Overview
| Domain | Multiple |
| Year | 2023 |
| Sentences | 14,903 |
| Granularity | Intra-sentence |
Tasks & Splits
| Task | Train | Test |
|---|---|---|
| Causality Detection | — | — |
| Causal Event Candidate Extraction | — | — |
| Causality Identification | — | — |
| Causality Extraction | — | — |
Citation
@inproceedings{tan:2023a,
title = {{{UniCausal}}: {{Unified Benchmark}} and {{Repository}} for {{Causal Text Mining}}},
shorttitle = {{{UniCausal}}},
booktitle = {Big {{Data Analytics}} and {{Knowledge Discovery}} - 25th {{International Conference}}, {{DaWaK}} 2023, {{Penang}}, {{Malaysia}}, {{August}} 28-30, 2023, {{Proceedings}}},
author = {Tan, Fiona Anting and Zuo, Xinyu and Ng, See-Kiong},
editor = {Wrembel, Robert and Gamper, Johann and Kotsis, Gabriele and Tjoa, A. Min and Khalil, Ismail},
year = 2023,
series = {Lecture {{Notes}} in {{Computer Science}}},
volume = {14148},
pages = {248--262},
publisher = {Springer},
doi = {10.1007/978-3-031-39831-5_23},
urldate = {2024-09-10}
}