EventCausality / README.md
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---
license: other
task_categories:
- text-classification
- token-classification
language:
- en
multilinguality:
- monolingual
size_categories:
- n<1K
tags:
- causality
pretty_name: EventCausality
configs:
- config_name: causality detection
data_files:
- split: train
path: causality-detection/train.parquet
- split: validation
path: causality-detection/dev.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: validation
path: causal-candidate-extraction/dev.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: validation
path: causality-identification/dev.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 EventCausality corpus into hf datasets. Please find the original dataset
> [here](https://cogcomp.seas.upenn.edu/page/resource_view/27). The data is sourced from the
> [CREST](https://github.com/phosseini/CREST) aggregation. Please see the [citations](#citations) at the end of this README.
## Dataset Description
- **Homepage:** https://cogcomp.seas.upenn.edu/page/resource_view/27
- **Paper:** [Causal Relation Extraction](https://aclanthology.org/D11-1027/)
# Usage
## Causality Detection
```py
from datasets import load_dataset
dataset = load_dataset("thagen/EventCausality", "causality detection")
```
## Causal Candidate Extraction
```py
from datasets import load_dataset
dataset = load_dataset("thagen/EventCausality", "causal candidate extraction")
```
## Causality Identification
```py
from datasets import load_dataset
dataset = load_dataset("thagen/EventCausality", "causality identification")
```
# Citations
The EventCausality paper by [Do et al., 2011](https://aclanthology.org/D11-1040/):
```bib
@inproceedings{do:2011,
title = {Minimally {{Supervised Event Causality Identification}}},
booktitle = {Proceedings of the 2011 {{Conference}} on {{Empirical Methods}} in {{Natural Language Processing}}, {{EMNLP}} 2011, 27-31 {{July}} 2011, {{John McIntyre Conference Centre}}, {{Edinburgh}}, {{UK}}, {{A}} Meeting of {{SIGDAT}}, a {{Special Interest Group}} of the {{ACL}}},
author = {Do, Quang and Chan, Yee Seng and Roth, Dan},
year = {2011},
pages = {294--303},
publisher = {ACL},
urldate = {2026-01-05}
}
```
CREST by [Hosseini et al., 2021](https://arxiv.org/abs/2103.13606) &mdash; whose aggregation we used to source the EventCausality data:
```bib
@article{hosseini:2021,
title = {Predicting {{Directionality}} in {{Causal Relations}} in {{Text}}},
author = {Hosseini, Pedram and Broniatowski, David A. and Diab, Mona T.},
year = {2021},
journal = {CoRR},
volume = {abs/2103.13606},
eprint = {2103.13606},
archiveprefix = {arXiv}
}
```