Referensi:
lipat1
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:persian_ner/fold1')
- Keterangan :
The dataset includes 250,015 tokens and 7,682 Persian sentences in total. It is available in 3 folds to be used in turn as training and test sets. The NER tags are in IOB format.
- Lisensi : Lisensi Internasional Creative Commons Attribution 4.0
- Versi : 1.1.0
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 2560 |
'train' | 5121 |
- Fitur :
{
"tokens": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner_tags": {
"feature": {
"num_classes": 13,
"names": [
"O",
"I-event",
"I-fac",
"I-loc",
"I-org",
"I-pers",
"I-pro",
"B-event",
"B-fac",
"B-loc",
"B-org",
"B-pers",
"B-pro"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
lipat2
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:persian_ner/fold2')
- Keterangan :
The dataset includes 250,015 tokens and 7,682 Persian sentences in total. It is available in 3 folds to be used in turn as training and test sets. The NER tags are in IOB format.
- Lisensi : Lisensi Internasional Creative Commons Attribution 4.0
- Versi : 1.1.0
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 2561 |
'train' | 5120 |
- Fitur :
{
"tokens": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner_tags": {
"feature": {
"num_classes": 13,
"names": [
"O",
"I-event",
"I-fac",
"I-loc",
"I-org",
"I-pers",
"I-pro",
"B-event",
"B-fac",
"B-loc",
"B-org",
"B-pers",
"B-pro"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
lipat3
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:persian_ner/fold3')
- Keterangan :
The dataset includes 250,015 tokens and 7,682 Persian sentences in total. It is available in 3 folds to be used in turn as training and test sets. The NER tags are in IOB format.
- Lisensi : Lisensi Internasional Creative Commons Attribution 4.0
- Versi : 1.1.0
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 2560 |
'train' | 5121 |
- Fitur :
{
"tokens": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner_tags": {
"feature": {
"num_classes": 13,
"names": [
"O",
"I-event",
"I-fac",
"I-loc",
"I-org",
"I-pers",
"I-pro",
"B-event",
"B-fac",
"B-loc",
"B-org",
"B-pers",
"B-pro"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}