README.md

metadata

YAML tags: null
annotations_creators:
  - expert-generated
language_creators:
  - found
language:
  - ca
license:
  - cc-by-nc-sa-4.0
multilinguality:
  - monolingual
pretty_name: teca
size_categories:
  - unknown
source_datasets: []
task_categories:
  - >-
    text-classificationThis is a professional translation of the XQuAD corpus
    and its annotations.
task_ids:
  - natural-language-inference

Dataset Card for XNLI-ca

Dataset Description

• Website:

• Paper:

• Point of Contact:

Dataset Summary

Professional translation into Catalan of The Cross-lingual Natural Language Inference XNLI dataset.

XNLI is an evaluation corpus for language transfer and cross-lingual sentence classification in 15 languages. It is a crowd-sourced collection of 5,000 test and 2,500 dev pairs for the MultiNLI corpus. The pairs are annotated with textual entailment and translated into 14 languages: French, Spanish, German, Greek, Bulgarian, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, Hindi, Swahili and Urdu. This results in 112.5k annotated pairs. Each premise can be associated with the corresponding hypothesis in the 15 languages, summing up to more than 1.5M combinations.

XNLI is restricted to only non-commercial research purposes under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

Supported Tasks and Leaderboards

Textual entailment, Text classification, Language Model

Languages

The dataset is in Catalan (ca-CA).

Dataset Structure

Data Instances

Two JSON files, one for each split.

Example:

    
   {
    "label": "contradiction",
    "premise": "Bé, ni tan sols estava pensant en això, però estava molt frustrat i vaig acabar tornant a parlar amb ell.",
    "hypothesis": "No he tornat a parlar amb ell."
  },
  {
    "label": "entailment",
    "premise": "Bé, ni tan sols estava pensant en això, però estava molt frustrat i vaig acabar tornant a parlar amb ell.",
    "hypothesis": "Estava tan molest que vaig començar a parlar amb ell de nou."
  },
  {
    "label": "neutral",
    "premise": "Bé, ni tan sols estava pensant en això, però estava molt frustrat i vaig acabar tornant a parlar amb ell.",
    "hypothesis": "Vam tenir una gran xerrada."
  }
  

Data Fields

• premise: text
• hypothesis: text related to the premise
• label: relation between premise and hypothesis:
  • 0: entailment
  • 1: neutral
  • 2: contradiction

Data Splits

• dev.json: 2490 examples
• test.json: 5010 examples

Dataset Creation

Curation Rationale

We created this dataset to contribute to the development of language models in Catalan, a low-resource language.

Source Data

XNLI.

Initial Data Collection and Normalization

This dataset is a professional translation of XNLI into Catalan, commissioned by BSC LangTech Unit within Projecte AINA.

For more information on how XNLI was created, refer to the paper XNLI: Evaluating Cross-lingual Sentence Representations, or visit the XNLI's webpage.

Who are the source language producers?

For more information on how XNLI was created, refer to the paper XNLI: Evaluating Cross-lingual Sentence Representations, or visit the XNLI's webpage.

Annotations

Annotation process

[N/A]

Who are the annotators?

This is a professional translation of the XNLI corpus and its annotations.

Personal and Sensitive Information

No personal or sensitive information included.

Considerations for Using the Data

Social Impact of Dataset

We hope 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

Language Technologies Unit 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 within the framework of Projecte AINA.

Licensing Information

XNLI is restricted to only non-commercial research purposes under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

Citation Information