| --- |
| 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) — 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} |
| } |
| ``` |
| |