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.

라이센스 : Creative Commons Attribution-ShareAlike 4.0 International Public License(CC BY-SA 4.0) 라이센스 요약은 http://creativecommons.org/licenses/by-sa/4.0/ 을 참조하십시오.
버전 : 1.0.0
분할 :

나뉘다	예
`'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.

라이센스 : Creative Commons Attribution-ShareAlike 4.0 International Public License(CC BY-SA 4.0) 라이센스 요약은 http://creativecommons.org/licenses/by-sa/4.0/ 을 참조하십시오.
버전 : 1.0.0
분할 :

나뉘다	예
`'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.

라이센스 : Creative Commons Attribution-ShareAlike 4.0 International Public License(CC BY-SA 4.0) 라이센스 요약은 http://creativecommons.org/licenses/by-sa/4.0/ 을 참조하십시오.
버전 : 1.0.0
분할 :

나뉘다	예
`'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"
    }
}