Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- eu
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- extended|glue
task_categories:
- text-classification
task_ids:
- natural-language-inference
pretty_name: WNLI-eu
config_names:
- wnli
language_details: eu-ES
configs:
- config_name: wnli
data_files:
- split: validation
path: wnli_validation.jsonl
- split: test
path: wnli_test.jsonl
default: true
dataset_info:
config_name: wnli
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: label
dtype:
class_label:
names:
'0': not_entailment
'1': entailment
- name: idx
dtype: int32
splits:
- name: validation
num_bytes: 12960
num_examples: 71
- name: test
num_bytes: 41450
num_examples: 146
download_size: 60587
dataset_size: 54410
Dataset Card for WNLI-eu
- Point of Contact: [email protected]
Dataset Description
Dataset Summary
WNLI-eu is the professional translation to Basque of the WNLI dataset. WNLI is part of the GLUE benchmark for English (Wang et al., 2018) and is based on the Winograd Schema Challenge (WSC) dataset (Levesque et al., 2011):
A Winograd schema is a pair of sentences differing in only one or two words and containing an ambiguity that is resolved in opposite ways in the two sentences and that requires the use of world knowledge and reasoning for its resolution.
Specifically, WNLI instances consist of Winograd schemas converted into NLI sentence-pair classification problems.
Languages
- eu-ES
Dataset Structure
Data Instances
WNLI-eu examples look like this:
{
"sentence1": "Isurbidea ilearekin buxatuta dago. Garbitu egin behar da.",
"sentence2": "Ilea garbitu behar da.",
"label": 0,
"idx": 0
}
Data Fields
sentence1
(str): the premise.sentence2
(str): second sentence.label
(int):1
or0
, whethersentence1
entailssentence2
or not, respectively.idx
(int): index of the example.
Data Splits
name | validation | test |
---|---|---|
default | 71 | 146 |
Dataset Creation
This dataset is a professional translation of the English WNLI dataset into Basque, commissioned by HiTZ (UPV/EHU) within the ILENIA project. For more information on how WNLI and the Winograd Schema Challenge dataset were created, please refer to their articles (see above).
Additional Information
This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215335.
Licensing Information
Creative Commons Attribution 4.0 International (CC BY 4.0)
Citation Information
@inproceedings{baucells-etal-2025-iberobench,
title = "{I}bero{B}ench: A Benchmark for {LLM} Evaluation in {I}berian Languages",
author = "Baucells, Irene and
Aula-Blasco, Javier and
de-Dios-Flores, Iria and
Paniagua Su{\'a}rez, Silvia and
Perez, Naiara and
Salles, Anna and
Sotelo Docio, Susana and
Falc{\~a}o, J{\'u}lia and
Saiz, Jose Javier and
Sepulveda Torres, Robiert and
Barnes, Jeremy and
Gamallo, Pablo and
Gonzalez-Agirre, Aitor and
Rigau, German and
Villegas, Marta",
editor = "Rambow, Owen and
Wanner, Leo and
Apidianaki, Marianna and
Al-Khalifa, Hend and
Eugenio, Barbara Di and
Schockaert, Steven",
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.coling-main.699/",
pages = "10491--10519",
}