Dataset:



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

More Information Needed

Languages

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Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

et

  • Size of downloaded dataset files: 0.35 MB
  • Size of the generated dataset: 0.07 MB
  • Total amount of disk used: 0.42 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: 0.35 MB
  • Size of the generated dataset: 0.07 MB
  • Total amount of disk used: 0.42 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: 0.35 MB
  • Size of the generated dataset: 0.07 MB
  • Total amount of disk used: 0.43 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: 0.35 MB
  • Size of the generated dataset: 0.08 MB
  • Total amount of disk used: 0.43 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: 0.35 MB
  • Size of the generated dataset: 0.08 MB
  • Total amount of disk used: 0.43 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 Sample Size

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

Dataset Creation

Curation Rationale

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Source Data

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Annotations

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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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.

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