polyglotte_ner

Les références:

Californie

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/ca')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 372665
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/de')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 547578
  • Caractéristiques :
{
    "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"
    }
}

es

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/es')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 386699
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/fi')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 387465
  • Caractéristiques :
{
    "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"
    }
}

Salut

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/hi')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 401648
  • Caractéristiques :
{
    "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"
    }
}

identifiant

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/id')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 463862
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/ko')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 560105
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/ms')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 528181
  • Caractéristiques :
{
    "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"
    }
}

PL

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/pl')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 623267
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/ru')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 551770
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/sr')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 559423
  • Caractéristiques :
{
    "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"
    }
}

télé

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/tl')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 160750
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/vi')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 351643
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/ar')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 339109
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/cs')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 564462
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/el')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 446052
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/et')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 87023
  • Caractéristiques :
{
    "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"
    }
}

fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/fr')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 418411
  • Caractéristiques :
{
    "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"
    }
}

heure

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/hr')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 629667
  • Caractéristiques :
{
    "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"
    }
}

il

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/it')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 378325
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/lt')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 848018
  • Caractéristiques :
{
    "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"
    }
}

nl

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/nl')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 520664
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/pt')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 396773
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/sk')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 500135
  • Caractéristiques :
{
    "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"
    }
}

sv

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/sv')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 634881
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/tr')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 607324
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/zh')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 1570853
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/bg')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 559694
  • Caractéristiques :
{
    "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"
    }
}

papa

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/da')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 546440
  • Caractéristiques :
{
    "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"
    }
}

fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/en')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 423982
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/fa')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 492903
  • Caractéristiques :
{
    "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"
    }
}

il

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/he')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 459933
  • Caractéristiques :
{
    "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"
    }
}

hein

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/hu')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 590218
  • Caractéristiques :
{
    "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"
    }
}

oui

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/ja')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 1691018
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/lv')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 331568
  • Caractéristiques :
{
    "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"
    }
}

Non

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/no')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 552176
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/ro')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 285985
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/sl')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 521251
  • Caractéristiques :
{
    "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"
    }
}

ème

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/th')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 217631
  • Caractéristiques :
{
    "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"
    }
}

Royaume-Uni

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/uk')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 561373
  • Caractéristiques :
{
    "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"
    }
}

combiné

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:polyglot_ner/combined')
  • Description :
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.
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Divisions :
Diviser Exemples
'train' 21070925
  • Caractéristiques :
{
    "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"
    }
}