poliglot_ner

Referensi:

ca

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/ca')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 372665
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

de

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/de')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 547578
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

yaitu

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/es')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 386699
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

fi

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/fi')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 387465
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

Hai

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/hi')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 401648
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

pengenal

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/id')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 463862
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ko

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/ko')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 560105
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

MS

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/ms')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 528181
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

hal

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/pl')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 623267
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ru

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/ru')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 551770
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

sr

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/sr')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 559423
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

tl

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/tl')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 160750
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

vi

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/vi')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 351643
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ar

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/ar')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 339109
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

cs

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/cs')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 564462
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

el

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/el')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 446052
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

et

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/et')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 87023
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

NS

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/fr')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 418411
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

jam

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/hr')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 629667
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

dia

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/it')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 378325
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

lt

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/lt')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 848018
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

tidak

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/nl')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 520664
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

pt

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/pt')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 396773
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

sk

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/sk')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 500135
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

St

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/sv')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 634881
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

tr

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/tr')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 607324
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

zh

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/zh')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 1570853
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

bg

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/bg')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 559694
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ya

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/da')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 546440
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

en

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/en')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 423982
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

fa

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/fa')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 492903
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

Dia

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/he')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 459933
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

huh

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/hu')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 590218
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ya

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/ja')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 1691018
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

lv

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/lv')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 331568
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

TIDAK

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/no')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 552176
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ro

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/ro')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 285985
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

sl

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/sl')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 521251
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

th

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/th')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 217631
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

inggris

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/uk')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 561373
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

digabungkan

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:polyglot_ner/combined')
  • Keterangan :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'train' 21070925
  • Fitur :
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lang": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}