Attend the Women in ML Symposium on December 7 Register now

swedish_medical_ner

References:

wiki

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:swedish_medical_ner/wiki')
  • Description:
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.
Split Examples
'train' 48720
  • Features:
{
    "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"
    }
}

lt

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:swedish_medical_ner/lt')
  • Description:
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.
Split Examples
'train' 745753
  • Features:
{
    "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

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:swedish_medical_ner/1177')
  • Description:
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.
Split Examples
'train' 927
  • Features:
{
    "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"
    }
}