senti_lex

Referensi:

af

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/af')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2299
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

sebuah

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/an')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 97
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ar

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ar')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2794
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

az

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/az')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1979
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

menjadi

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/be')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1526
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

bg

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/bg')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2847
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

bn

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/bn')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2393
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

saudara

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/br')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 184
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

bs

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/bs')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2020
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ca

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ca')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3204
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

cs

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/cs')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2599
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

cy

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/cy')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1647
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ya

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/da')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3340
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

de

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/de')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3974
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

el

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/el')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2703
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

eo

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/eo')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2604
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

yaitu

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/es')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 4275
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

et

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/et')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2105
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

uni eropa

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/eu')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1979
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

fa

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/fa')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2477
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

fi

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/fi')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3295
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

fo

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/fo')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 123
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

NS

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/fr')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 4653
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

f.y

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/fy')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 224
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ga

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ga')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1073
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

gd

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/gd')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 345
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

jam

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/gl')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2714
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

gu

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/gu')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2145
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

Dia

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/he')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2533
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

Hai

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/hi')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3640
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

jam

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/hr')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2208
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ht

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ht')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 472
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

huh

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/hu')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3522
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

hy

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/hy')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1657
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ia

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ia')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 326
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

pengenal

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/id')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2900
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

io

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/io')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 183
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

adalah

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/is')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1770
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

dia

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/it')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 4491
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ya

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ja')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1017
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ka

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ka')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2202
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

km

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/km')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 956
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

buku

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/kn')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2173
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ko

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ko')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2118
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ku

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ku')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 145
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

oke

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ky')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 246
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

la

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/la')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2033
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

pon

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/lb')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 224
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

lt

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/lt')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2190
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

lv

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/lv')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1938
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

mk

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/mk')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2965
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

Tn.

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/mr')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1825
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

MS

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ms')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2934
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

mt

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/mt')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 863
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

tidak

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/nl')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3976
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

nn

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/nn')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1894
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

TIDAK

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/no')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3089
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

hal

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/pl')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3533
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

pt

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/pt')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3953
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

rm

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/rm')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 116
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ro

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ro')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3329
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ru

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ru')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2914
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

sk

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/sk')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2428
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

sl

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/sl')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2244
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

persegi

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/sq')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2076
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

sr

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/sr')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2034
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

St

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/sv')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3722
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

sw

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/sw')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1314
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ta

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ta')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2057
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

te

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/te')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2523
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

th

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/th')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1279
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

tk

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/tk')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 78
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

tl

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/tl')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1858
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

tr

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/tr')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2500
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

inggris

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/uk')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 2827
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

kamu

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/ur')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1347
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

kamus

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/uz')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 111
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

vi

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/vi')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1016
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

kamu

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/vo')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 43
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

wa

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/wa')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 193
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

ya

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/yi')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 395
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

zh

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/zh')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 1879
  • Fitur : 
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

zhw

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:senti_lex/zhw')
  • Keterangan :
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them.
  • Lisensi : Lisensi Publik Umum GNU v3
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'train' 3828
  • Fitur :
{
    "word": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentiment": {
        "num_classes": 2,
        "names": [
            "negative",
            "positive"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}