melayang

Referensi:

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:hover')
  • Keterangan :
HoVer is an open-domain, many-hop fact extraction and claim verification dataset built upon the Wikipedia corpus. The original 2-hop claims are adapted from question-answer pairs from HotpotQA. It is collected by a team of NLP researchers at UNC Chapel Hill and Verisk Analytics.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.1.0
  • Perpecahan :
Membelah Contoh
'test' 4000
'train' 18171
'validation' 4000
  • Fitur :
{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "uid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "claim": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "supporting_facts": [
        {
            "key": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "value": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        }
    ],
    "label": {
        "num_classes": 2,
        "names": [
            "NOT_SUPPORTED",
            "SUPPORTED"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "num_hops": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "hpqa_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}