Datasets:
				
			
			
	
			
	
		
			
	
		Tasks:
	
	
	
	
	Text Classification
	
	
	Modalities:
	
	
	
		
	
	Text
	
	
	Formats:
	
	
	
		
	
	parquet
	
	
	Sub-tasks:
	
	
	
	
	natural-language-inference
	
	
	Languages:
	
	
	
		
	
	Catalan
	
	
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	< 1K
	
	
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								---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- extended|glue
task_categories:
- text-classification
task_ids:
- natural-language-inference
pretty_name: wnli-ca
dataset_info:
  features:
  - name: index
    dtype: int64
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': not_entailment
          '1': entailment
  splits:
  - name: train
    num_bytes: 122242
    num_examples: 635
  - name: validation
    num_bytes: 13655
    num_examples: 71
  - name: test
    num_bytes: 43986
    num_examples: 146
  download_size: 69444
  dataset_size: 179883
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---
# WNLI-ca
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)
## Dataset Description
- **Website:** https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html
- **Point of Contact:** [Language Technologies Unit]([email protected])
### Dataset Summary
"A Winograd schema is a pair of sentences that differ in only one or two words and that contain an ambiguity that is resolved in opposite ways in the two sentences and requires the use of world knowledge and reasoning for its resolution. The schema takes its name from Terry Winograd." Source: [The Winograd Schema Challenge](https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html).
The [Winograd NLI dataset](https://dl.fbaipublicfiles.com/glue/data/WNLI.zip) presents 855 sentence pairs, in which the first sentence contains an ambiguity and the second one a possible interpretation of it. The label indicates if the interpretation is correct (1) or not (0).
This dataset is a professional translation into Catalan of [Winograd NLI dataset](https://dl.fbaipublicfiles.com/glue/data/WNLI.zip) as published in [GLUE Benchmark](https://gluebenchmark.com/tasks).
Both the original dataset and this translation are licenced under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/). 
### Supported Tasks and Leaderboards
Textual entailment, Text classification, Language Model.
### Languages
The dataset is in Catalan (`ca-ES`)
## Dataset Structure
### Data Instances
Three tsv files.
### Data Fields
- index
- sentence 1: first sentence of the pair
- sentence 2: second sentence of the pair
- label: relation between the two sentences:
    * 0: the second sentence does not entail a correct interpretation of the first one (neutral)
    * 1: the second sentence entails a correct interpretation of the first one (entailment)
### Example
|  index  |   sentence 1  |  sentence 2  |  label  | 
| ------- |----------- | --------- | ----- | 
| 0 | Vaig clavar una agulla en una pastanaga. Quan la vaig treure, tenia un forat. | La pastanaga tenia un forat. | 1 |
| 1 | En Joan no podia veure l’escenari amb en Guillem davant seu perquè és molt baix. | En Joan és molt baix. | 1 |
| 2 | Els policies van arrestar tots els membres de la banda. Volien aturar el tràfic de drogues del barri. | Els policies volien aturar el tràfic de drogues del barri. | 1 |
| 3 | L’Esteve segueix els passos d’en Frederic en tot. L’influencia moltíssim. | L’Esteve l’influencia moltíssim. | 0 |
  
### Data Splits
- wnli-train-ca.csv: 636
- wnli-dev-ca.csv: 72
- wnli-test-shuffled-ca.csv: 146 
## Dataset Creation
### Curation Rationale
We translated this dataset to contribute to the development of language models in Catalan, a low-resource language, and to allow inter-lingual comparisons. 
### Source Data
- [GLUE Benchmark site](https://gluebenchmark.com)
#### Initial Data Collection and Normalization
This is a professional translation of [WNLI dataset](https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html) into Catalan, commissioned by BSC TeMU within the [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina/).
For more information on how the Winograd NLI dataset was created, visit the webpage [The Winograd Schema Challenge](https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html).
#### Who are the source language producers?
For more information on how the Winograd NLI dataset was created, visit the webpage [The Winograd Schema Challenge](https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html).
### Annotations
#### Annotation process
We comissioned a professional translation of [WNLI dataset](https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html) into Catalan.
#### Who are the annotators?
Translation was commisioned to a professional translator.
### Personal and Sensitive Information
No personal or sensitive information included.
## Considerations for Using the Data
### Social Impact of Dataset
This dataset contributes to the development of language models in Catalan, a low-resource language.
### Discussion of Biases
[N/A]
### Other Known Limitations
[N/A]
## Additional Information
### Dataset Curators
Text Mining Unit (TeMU) at the Barcelona Supercomputing Center ([email protected]).
This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
### Licensing Information
This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by/4.0/">CC Attribution 4.0 International License</a>.
### Citation Information
```
@inproceedings{gonzalez-agirre-etal-2024-building-data,
    title = "Building a Data Infrastructure for a Mid-Resource Language: The Case of {C}atalan",
    author = "Gonzalez-Agirre, Aitor  and
      Marimon, Montserrat  and
      Rodriguez-Penagos, Carlos  and
      Aula-Blasco, Javier  and
      Baucells, Irene  and
      Armentano-Oller, Carme  and
      Palomar-Giner, Jorge  and
      Kulebi, Baybars  and
      Villegas, Marta",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.231",
    pages = "2556--2566",
}
```
### Contributions
[N/A]
 |