xcopa

References:

et

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/et')
  • Description:
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
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

ht

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/ht')
  • Description:
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 ht
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

it

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/it')
  • Description:
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 it
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

id

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/id')
  • Description:
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 id
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

qu

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/qu')
  • Description:
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 qu
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

sw

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/sw')
  • Description:
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 sw
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

zh

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/zh')
  • Description:
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 zh
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

ta

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/ta')
  • Description:
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 ta
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

th

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/th')
  • Description:
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 th
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

tr

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/tr')
  • Description:
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 tr
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

vi

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/vi')
  • Description:
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 vi
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-et

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-et')
  • Description:
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 English translation for language et
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-ht

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-ht')
  • Description:
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 English translation for language ht
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-it

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-it')
  • Description:
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 English translation for language it
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-id

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-id')
  • Description:
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 English translation for language id
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-sw

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-sw')
  • Description:
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 English translation for language sw
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-zh

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-zh')
  • Description:
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 English translation for language zh
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-ta

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-ta')
  • Description:
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 English translation for language ta
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-th

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-th')
  • Description:
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 English translation for language th
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-tr

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-tr')
  • Description:
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 English translation for language tr
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}

translation-vi

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:xcopa/translation-vi')
  • Description:
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 English translation for language vi
  • License: No known license
  • Version: 1.1.0
  • Splits:
Split Examples
'test' 500
'validation' 100
  • Features:
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "choice2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "idx": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "changed": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    }
}