ecthr_cases

References:

• Code
• Huggingface

alleged-violation-prediction

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:ecthr_cases/alleged-violation-prediction')

• Description:

The ECtHR Cases dataset is designed for experimentation of neural judgment prediction and rationale extraction considering ECtHR cases.

• License: CC BY-NC-SA (Creative Commons / Attribution-NonCommercial-ShareAlike)
• Version: 1.1.0
• Splits:

• Features:

{
    "facts": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
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        "_type": "Sequence"
    },
    "labels": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "silver_rationales": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "gold_rationales": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

violation-prediction

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:ecthr_cases/violation-prediction')

• Description:

The ECtHR Cases dataset is designed for experimentation of neural judgment prediction and rationale extraction considering ECtHR cases.

• License: CC BY-NC-SA (Creative Commons / Attribution-NonCommercial-ShareAlike)
• Version: 1.1.0
• Splits:

• Features:

{
    "facts": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "labels": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "silver_rationales": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}