swedish_medical_ner

Références:

wiki

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

ds = tfds.load('huggingface:swedish_medical_ner/wiki')
  • Descriptif :
SwedMedNER is a dataset for training and evaluating Named Entity Recognition systems on medical texts in Swedish.
It is derived from medical articles on the Swedish Wikipedia, Läkartidningen, and 1177 Vårdguiden.
Diviser Exemples
'train' 48720
  • Caractéristiques :
{
    "sid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "entities": {
        "feature": {
            "start": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "end": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "type": {
                "num_classes": 3,
                "names": [
                    "Disorder and Finding",
                    "Pharmaceutical Drug",
                    "Body Structure"
                ],
                "names_file": null,
                "id": null,
                "_type": "ClassLabel"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ça

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

ds = tfds.load('huggingface:swedish_medical_ner/lt')
  • Descriptif :
SwedMedNER is a dataset for training and evaluating Named Entity Recognition systems on medical texts in Swedish.
It is derived from medical articles on the Swedish Wikipedia, Läkartidningen, and 1177 Vårdguiden.
Diviser Exemples
'train' 745753
  • Caractéristiques :
{
    "sid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "entities": {
        "feature": {
            "start": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "end": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "type": {
                "num_classes": 3,
                "names": [
                    "Disorder and Finding",
                    "Pharmaceutical Drug",
                    "Body Structure"
                ],
                "names_file": null,
                "id": null,
                "_type": "ClassLabel"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

1177

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

ds = tfds.load('huggingface:swedish_medical_ner/1177')
  • Descriptif :
SwedMedNER is a dataset for training and evaluating Named Entity Recognition systems on medical texts in Swedish.
It is derived from medical articles on the Swedish Wikipedia, Läkartidningen, and 1177 Vårdguiden.
Diviser Exemples
'train' 927
  • Caractéristiques :
{
    "sid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "entities": {
        "feature": {
            "start": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "end": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "type": {
                "num_classes": 3,
                "names": [
                    "Disorder and Finding",
                    "Pharmaceutical Drug",
                    "Body Structure"
                ],
                "names_file": null,
                "id": null,
                "_type": "ClassLabel"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}