카탈로니아_독립

참고자료:

카탈로니아 사람

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:catalonia_independence/catalan')
  • 설명 :
This dataset contains two corpora in Spanish and Catalan that consist of annotated Twitter messages for automatic stance detection. The data was collected over 12 days during February and March of 2019 from tweets posted in Barcelona, and during September of 2018 from tweets posted in the town of Terrassa, Catalonia.

Each corpus is annotated with three classes: AGAINST, FAVOR and NEUTRAL, which express the stance towards the target - independence of Catalonia.
  • 라이센스 : CC BY-NC-SA 4.0
  • 버전 : 1.1.0
  • 분할 :
나뉘다
'test' 2010년
'train' 6028
'validation' 2010년
  • 특징 :
{
    "id_str": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "TWEET": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "LABEL": {
        "num_classes": 3,
        "names": [
            "AGAINST",
            "FAVOR",
            "NEUTRAL"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

스페인 사람

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:catalonia_independence/spanish')
  • 설명 :
This dataset contains two corpora in Spanish and Catalan that consist of annotated Twitter messages for automatic stance detection. The data was collected over 12 days during February and March of 2019 from tweets posted in Barcelona, and during September of 2018 from tweets posted in the town of Terrassa, Catalonia.

Each corpus is annotated with three classes: AGAINST, FAVOR and NEUTRAL, which express the stance towards the target - independence of Catalonia.
  • 라이센스 : CC BY-NC-SA 4.0
  • 버전 : 1.1.0
  • 분할 :
나뉘다
'test' 2016년
'train' 6046
'validation' 2015년
  • 특징 :
{
    "id_str": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "TWEET": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "LABEL": {
        "num_classes": 3,
        "names": [
            "AGAINST",
            "FAVOR",
            "NEUTRAL"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}