swedish_medical_ner

참고자료:

위키

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:swedish_medical_ner/wiki')
  • 설명 :
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.
나뉘다
'train' 48720
  • 특징 :
{
    "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

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:swedish_medical_ner/lt')
  • 설명 :
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.
나뉘다
'train' 745753
  • 특징 :
{
    "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

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:swedish_medical_ner/1177')
  • 설명 :
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.
나뉘다
'train' 927
  • 특징 :
{
    "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"
    }
}