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ecthr_cases

参考:

alleged-violation-prediction

使用以下命令在 TFDS 中加载此数据集:

ds = tfds.load('huggingface:ecthr_cases/alleged-violation-prediction')
  • 说明
The ECtHR Cases dataset is designed for experimentation of neural judgment prediction and rationale extraction considering ECtHR cases.
  • 许可:CC BY-NC-SA (Creative Commons / Attribution-NonCommercial-ShareAlike)
  • 版本:1.0.0
  • 拆分
拆分 样本
'test' 1000
'train' 9000
'validation' 1000
  • 特征
{
    "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"
    },
    "gold_rationales": {
        "feature": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

violation-prediction

使用以下命令在 TFDS 中加载此数据集:

ds = tfds.load('huggingface:ecthr_cases/violation-prediction')
  • 说明
The ECtHR Cases dataset is designed for experimentation of neural judgment prediction and rationale extraction considering ECtHR cases.
  • 许可:CC BY-NC-SA (Creative Commons / Attribution-NonCommercial-ShareAlike)
  • 版本:1.0.0
  • 拆分
拆分 样本
'test' 1000
'train' 9000
'validation' 1000
  • 特征
{
    "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"
    }
}