cdsc

Riferimenti:

cdsc-e

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:cdsc/cdsc-e')
  • Descrizione : 
Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness and entailment. The dataset may be used for the evaluation of compositional distributional semantics models of Polish. The dataset was presented at ACL 2017. Please refer to the Wróblewska and Krasnowska-Kieraś (2017) for a detailed description of the resource.
  • Licenza : CC BY-NC-SA 4.0
  • Versione : 1.1.0
  • Divide :
Diviso Esempi
'test' 1000
'train' 8000
'validation' 1000
  • Caratteristiche : 
{
    "pair_ID": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "sentence_A": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence_B": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "entailment_judgment": {
        "num_classes": 3,
        "names": [
            "NEUTRAL",
            "CONTRADICTION",
            "ENTAILMENT"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

cdsc-r

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:cdsc/cdsc-r')
  • Descrizione : 
Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness and entailment. The dataset may be used for the evaluation of compositional distributional semantics models of Polish. The dataset was presented at ACL 2017. Please refer to the Wróblewska and Krasnowska-Kieraś (2017) for a detailed description of the resource.
  • Licenza : CC BY-NC-SA 4.0
  • Versione : 1.1.0
  • Divide :
Diviso Esempi
'test' 1000
'train' 8000
'validation' 1000
  • Caratteristiche : 
{
    "pair_ID": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "sentence_A": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence_B": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "relatedness_score": {
        "dtype": "float32",
        "id": null,
        "_type": "Value"
    }
}