thagen/CNCv2
[!NOTE] This repository integrates the "V2" release of the Causal News Corpus (CNC) — published as RECESS — into hf datasets. Please find the original dataset here. This is the actively-maintained release the maintainers recommend using ("For 2023 Shared Task, please use V2"), with far richer span annotations (2257 causal relations) than CNC, the original 2022 release (183 causal relations) — kept as its own separate dataset for comparison rather than silently overwritten. Please see the… See the full description on the dataset page: https://huggingface.co/datasets/thagen/CNCv2.
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[!NOTE] This repository integrates the "V2" release of the Causal News Corpus (CNC) — published as RECESS — into hf datasets. Please find the original dataset here. This is the actively-maintained release the maintainers recommend using ("For 2023 Shared Task, please use V2"), with far richer span annotations (2257 causal relations) than CNC, the original 2022 release (183 causal relations) — kept as its own separate dataset for comparison rather than silently overwritten. Please see the citations at the end of this README.
Dataset Description
- Repository: https://github.com/tanfiona/CausalNewsCorpus
- Paper: RECESS: Resource for Extracting Cause, Effect, and Signal Spans
Usage
Causality Detection
from datasets import load_dataset
dataset = load_dataset("thagen/CausalNewsCorpusV2", "causality detection")Causal Candidate Extraction
from datasets import load_dataset
dataset = load_dataset("thagen/CausalNewsCorpusV2", "causal candidate extraction")Causality Identification
from datasets import load_dataset
dataset = load_dataset("thagen/CausalNewsCorpusV2", "causality identification")Citations
This "V2" release is published as RECESS, Tan et al., 2023:
@inproceedings{tan-etal-2023-recess,
title = {{RECESS}: Resource for Extracting Cause, Effect, and Signal Spans},
booktitle = {Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)},
author = {Tan, Fiona Anting and Hettiarachchi, Hansi and H{\"u}rriyeto{\u{g}}lu, Ali and Oostdijk, Nelleke and Caselli, Tommaso and Nomoto, Tadashi and Uca, Onur and Liza, Farhana Ferdousi and Ng, See-Kiong},
year = {2023},
address = {Nusa Dua, Bali},
publisher = {Association for Computational Linguistics},
pages = {66--82}
}The original Causal News Corpus paper by Tan et al., 2022:
@inproceedings{tan:2022,
title = {The Causal News Corpus: Annotating Causal Relations in Event Sentences},
booktitle = {Proceedings of the 13th Language Resources and Evaluation Conference},
author = {Tan, Fiona Anting and Ng, See-Kiong and Ong, Alifia Reina},
year = {2022},
pages = {2298--2310},
publisher = {European Language Resources Association}
}