Referensi:
dugaan-pelanggaran-prediksi
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:ecthr_cases/alleged-violation-prediction')
- Keterangan :
The ECtHR Cases dataset is designed for experimentation of neural judgment prediction and rationale extraction considering ECtHR cases.
- Lisensi : CC BY-NC-SA (Creative Commons / Attribution-NonCommercial-ShareAlike)
- Versi : 1.1.0
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 1000 |
'train' | 9000 |
'validation' | 1000 |
- Fitur :
{
"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"
}
}
prediksi pelanggaran
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:ecthr_cases/violation-prediction')
- Keterangan :
The ECtHR Cases dataset is designed for experimentation of neural judgment prediction and rationale extraction considering ECtHR cases.
- Lisensi : CC BY-NC-SA (Creative Commons / Attribution-NonCommercial-ShareAlike)
- Versi : 1.1.0
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 1000 |
'train' | 9000 |
'validation' | 1000 |
- Fitur :
{
"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"
}
}