metadata
license: other
task_categories:
- text-classification
- token-classification
language:
- en
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
tags:
- causality
pretty_name: CaTeRS
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
This repository integrates the CaTeRS corpus into hf datasets. Please find the original dataset here. The data is sourced from the CREST aggregation. Please see the citations at the end of this README.
Dataset Description
- Homepage: https://www.cs.rochester.edu/nlp/rocstories/CaTeRS/
- Paper: CaTeRS: Causal and Temporal Relation Scheme for Semantic Annotation of Event Structures
Usage
Causality Detection
from datasets import load_dataset
dataset = load_dataset("thagen/CaTeRS", "causality detection")
Causal Candidate Extraction
from datasets import load_dataset
dataset = load_dataset("thagen/CaTeRS", "causal candidate extraction")
Causality Identification
from datasets import load_dataset
dataset = load_dataset("thagen/CaTeRS", "causality identification")
Citations
The CaTeRS paper by Mostafazadeh et al., 2016:
@inproceedings{mostafazadeh:2016,
title = {{{CaTeRS}}: {{Causal}} and {{Temporal Relation Scheme}} for {{Semantic Annotation}} of {{Event Structures}}},
shorttitle = {{{CaTeRS}}},
booktitle = {Proceedings of the {{Fourth Workshop}} on {{Events}}, {{EVENTS}}@{{HLT-NAACL}} 2016, {{San Diego}}, {{California}}, {{USA}}, {{June}} 17, 2016},
author = {Mostafazadeh, Nasrin and Grealish, Alyson and Chambers, Nathanael and Allen, James F. and Vanderwende, Lucy},
year = {2016},
pages = {51--61},
publisher = {Association for Computational Linguistics},
doi = {10.18653/V1/W16-1007}
}
CREST by Hosseini et al., 2021 — whose aggregation we used to source the CaTeRS data:
@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}
}