---
license: cc0-1.0
task_categories:
- text-classification
- token-classification
language:
- en
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
tags:
- causality
pretty_name: Causal News Corpus (CNC)
configs:
- config_name: causality detection
  data_files:
  - split: train
    path: causality-detection/train.parquet
  - split: test
    path: causality-detection/test.parquet
  features:
  - name: index
    dtype: string
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': uncausal
          '1': causal
- config_name: causal candidate extraction
  data_files:
  - split: train
    path: causal-candidate-extraction/train.parquet
  - split: test
    path: causal-candidate-extraction/test.parquet
  features:
    - name: index
      dtype: string
    - name: text
      dtype: string
    - name: entity
      sequence:
        sequence: int32
- config_name: causality identification
  data_files:
  - split: train
    path: causality-identification/train.parquet
  - split: test
    path: causality-identification/test.parquet
  features:
  - name: index
    dtype: string
  - name: text
    dtype: string
  - name: relations
    list:
    - name: relationship
      dtype:
        class_label:
          names:
            '0': no-rel
            '1': causal
    - name: first
      dtype: string
    - name: second
      dtype: string
train-eval-index:
- config: causality detection
  task: text-classification
  task_id: text_classification
  splits:
    train_split: train
    eval_split: test
  col_mapping:
    text: text
    label: label
  metrics:
  - type: accuracy
  - type: precision
  - type: recall
  - type: f1
- config: causal candidate extraction
  task: token-classification
  task_id: token_classification
  splits:
    train_split: train
    eval_split: test
  metrics:
  - type: accuracy
  - type: precision
  - type: recall
  - type: f1
- config: causality identification
  task: text-classification
  task_id: text_classification
  splits:
    train_split: train
    eval_split: test
  metrics:
  - type: accuracy
  - type: precision
  - type: recall
  - type: f1
---

> [!NOTE]  
> This repository integrates the original 2022 "V1" release of the Causal News Corpus (CNC) into hf datasets.
> Please find the original dataset [here](https://github.com/tanfiona/CausalNewsCorpus). This is the OLDER,
> much more sparsely span-annotated release (183 causal relations, vs. 2257 in [CNCv2](../CNCv2), the
> "V2"/RECESS release the maintainers now recommend using) — kept as its own separate dataset rather than
> silently overwritten, so both remain available for comparison. Please see the [citations](#citations) at
> the end of this README.

## Dataset Description

- **Repository:** https://github.com/tanfiona/CausalNewsCorpus
- **Paper:** [The Causal News Corpus: Annotating Causal Relations in Event Sentences](https://aclanthology.org/2022.lrec-1.246)

# Usage
## Causality Detection
```py
from datasets import load_dataset
dataset = load_dataset("thagen/CausalNewsCorpus", "causality detection")
```

## Causal Candidate Extraction
```py
from datasets import load_dataset
dataset = load_dataset("thagen/CausalNewsCorpus", "causal candidate extraction")
```

## Causality Identification
```py
from datasets import load_dataset
dataset = load_dataset("thagen/CausalNewsCorpus", "causality identification")
```

# Citations

The Causal News Corpus paper by [Tan et al., 2022](https://aclanthology.org/2022.lrec-1.246):
```bib
@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}
}
```