|
--- |
|
license: odc-by |
|
configs: |
|
- config_name: claim |
|
data_files: |
|
- split: train |
|
path: data/claim_train.jsonl |
|
- split: validation |
|
path: data/claim_dev.jsonl |
|
- split: test |
|
path: data/claim_test.jsonl |
|
- config_name: subclaim |
|
data_files: |
|
- split: train |
|
path: data/subclaim_train.jsonl |
|
- split: validation |
|
path: data/subclaim_dev.jsonl |
|
- split: test |
|
path: data/subclaim_test.jsonl |
|
--- |
|
|
|
# wice |
|
|
|
WiCE: Real-World Entailment for Claims in Wikipedia |
|
|
|
## Dataset Details |
|
|
|
### Dataset Description |
|
|
|
WiCE is a fine-grained textual entailment dataset built on natural claim and evidence pairs extracted from Wikipedia. Given a sentence in Wikipedia and the corresponding article(s) it cites, we annotate the entailment label, a list of sentences in the cited article(s) that support the claim sentence, and tokens in the claim that are unsupported by the article(s). |
|
|
|
This is the `entailment_retrieval` subset that includes the WiCE dataset for entailment and retrieval task. `claim` includes data with the original claims and `subclaim` includes data with the decomposed claims (finegrained annotation by using Claim-Split). |
|
|
|
### Dataset Sources |
|
|
|
<!-- Provide the basic links for the dataset. --> |
|
|
|
- **Repository:** https://github.com/ryokamoi/wice |
|
- **Paper:** Kamoi, Goyal, Rodriguez, and Durett(2023) [WiCE: Real-World Entailment for Claims in Wikipedia |
|
](https://arxiv.org/abs/2303.01432). |
|
|
|
## Citation |
|
|
|
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
|
|
|
```bibtex |
|
@inproceedings{kamoi-etal-2023-wice, |
|
title = "{W}i{CE}: Real-World Entailment for Claims in {W}ikipedia", |
|
author = "Kamoi, Ryo and |
|
Goyal, Tanya and |
|
Rodriguez, Juan and |
|
Durrett, Greg", |
|
editor = "Bouamor, Houda and |
|
Pino, Juan and |
|
Bali, Kalika", |
|
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing", |
|
month = dec, |
|
year = "2023", |
|
address = "Singapore", |
|
publisher = "Association for Computational Linguistics", |
|
url = "https://aclanthology.org/2023.emnlp-main.470", |
|
pages = "7561--7583", |
|
} |
|
``` |
|
|
