Dataset Card for "xcopa"

Dataset Summary

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the creation of XCOPA and the implementation of the baselines are available in the paper.

Xcopa language et

Supported Tasks and Leaderboards

More Information Needed

Languages

• et
• ht
• id
• it
• qu
• sw
• ta
• th
• tr
• vi
• zh

Dataset Structure

Data Instances

et

• Size of downloaded dataset files: 0.37 MB
• Size of the generated dataset: 0.07 MB
• Total amount of disk used: 0.44 MB

An example of 'validation' looks as follows.

{
    "changed": false,
    "choice1": "Ta kallas piima kaussi.",
    "choice2": "Ta kaotas oma isu.",
    "idx": 1,
    "label": 1,
    "premise": "Tüdruk leidis oma helveste seest putuka.",
    "question": "effect"
}

ht

• Size of downloaded dataset files: 0.37 MB
• Size of the generated dataset: 0.07 MB
• Total amount of disk used: 0.44 MB

An example of 'validation' looks as follows.

{
    "changed": false,
    "choice1": "Ta kallas piima kaussi.",
    "choice2": "Ta kaotas oma isu.",
    "idx": 1,
    "label": 1,
    "premise": "Tüdruk leidis oma helveste seest putuka.",
    "question": "effect"
}

id

• Size of downloaded dataset files: 0.37 MB
• Size of the generated dataset: 0.07 MB
• Total amount of disk used: 0.45 MB

An example of 'validation' looks as follows.

{
    "changed": false,
    "choice1": "Ta kallas piima kaussi.",
    "choice2": "Ta kaotas oma isu.",
    "idx": 1,
    "label": 1,
    "premise": "Tüdruk leidis oma helveste seest putuka.",
    "question": "effect"
}

it

• Size of downloaded dataset files: 0.37 MB
• Size of the generated dataset: 0.08 MB
• Total amount of disk used: 0.45 MB

An example of 'validation' looks as follows.

{
    "changed": false,
    "choice1": "Ta kallas piima kaussi.",
    "choice2": "Ta kaotas oma isu.",
    "idx": 1,
    "label": 1,
    "premise": "Tüdruk leidis oma helveste seest putuka.",
    "question": "effect"
}

qu

• Size of downloaded dataset files: 0.37 MB
• Size of the generated dataset: 0.08 MB
• Total amount of disk used: 0.45 MB

An example of 'validation' looks as follows.

{
    "changed": false,
    "choice1": "Ta kallas piima kaussi.",
    "choice2": "Ta kaotas oma isu.",
    "idx": 1,
    "label": 1,
    "premise": "Tüdruk leidis oma helveste seest putuka.",
    "question": "effect"
}

Data Fields

The data fields are the same among all splits.

et

• premise : a string feature.
• choice1 : a string feature.
• choice2 : a string feature.
• question : a string feature.
• label : a int32 feature.
• idx : a int32 feature.
• changed : a bool feature.

ht

• premise : a string feature.
• choice1 : a string feature.
• choice2 : a string feature.
• question : a string feature.
• label : a int32 feature.
• idx : a int32 feature.
• changed : a bool feature.

id

• premise : a string feature.
• choice1 : a string feature.
• choice2 : a string feature.
• question : a string feature.
• label : a int32 feature.
• idx : a int32 feature.
• changed : a bool feature.

it

• premise : a string feature.
• choice1 : a string feature.
• choice2 : a string feature.
• question : a string feature.
• label : a int32 feature.
• idx : a int32 feature.
• changed : a bool feature.

qu

• premise : a string feature.
• choice1 : a string feature.
• choice2 : a string feature.
• question : a string feature.
• label : a int32 feature.
• idx : a int32 feature.
• changed : a bool feature.

Data Splits

name	validation	test
et	100	500
ht	100	500
id	100	500
it	100	500
qu	100	500

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

Creative Commons Attribution 4.0 International (CC BY 4.0) .

Citation Information

  @article{ponti2020xcopa,
  title={{XCOPA: A} Multilingual Dataset for Causal Commonsense Reasoning},
  author={Edoardo M. Ponti, Goran Glava
{s}, Olga Majewska, Qianchu Liu, Ivan Vuli'{c} and Anna Korhonen},
  journal={arXiv preprint},
  year={2020},
  url={https://ducdauge.github.io/files/xcopa.pdf}
}

@inproceedings{roemmele2011choice,
  title={Choice of plausible alternatives: An evaluation of commonsense causal reasoning},
  author={Roemmele, Melissa and Bejan, Cosmin Adrian and Gordon, Andrew S},
  booktitle={2011 AAAI Spring Symposium Series},
  year={2011},
  url={https://people.ict.usc.edu/~gordon/publications/AAAI-SPRING11A.PDF},
}

Contributions

Thanks to @patrickvonplaten , @lewtun , @thomwolf for adding this dataset.