masakhaner

Referanslar:

ah

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/amh')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 500
'train' 1750
'validation' 250
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ha ha

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/hau')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 552
'train' 1912
'validation' 276
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ibo

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/ibo')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 638
'train' 2235
'validation' 320
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

akraba

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/kin')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 605
'train' 2116
'validation' 302
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

pabuç

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/lug')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 407
'train' 1428
'validation' 200
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

luo

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/luo')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 186
'train' 644
'validation' 92
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

pcm

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/pcm')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 600
'train' 2124
'validation' 306
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

swa

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/swa')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 604
'train' 2109
'validation' 300
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

kurt

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/wol')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 539
'train' 1871
'validation' 267
  • Özellikler : 
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

senin

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:masakhaner/yor')
  • Tanım :
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities.

Example:
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages:
- Amharic
- Hausa
- Igbo
- Kinyarwanda
- Luganda
- Luo
- Nigerian-Pidgin
- Swahili
- Wolof
- Yoruba

The train/validation/test sets are available for all the ten languages.

For more details see https://arxiv.org/abs/2103.11811
  • Lisans : Bilinen lisans yok
  • Sürüm : 1.0.0
  • Bölünmeler :
Bölmek Örnekler
'test' 645
'train' 2171
'validation' 305
  • Özellikler :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-DATE",
                "I-DATE"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}