a_part,a_part

Références:

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:has_part')
  • Descriptif :
This dataset is a new knowledge-base (KB) of hasPart relationships, extracted from a large corpus of generic statements. Complementary to other resources available, it is the first which is all three of: accurate (90% precision), salient (covers relationships a person may mention), and has high coverage of common terms (approximated as within a 10 year old’s vocabulary), as well as having several times more hasPart entries than in the popular ontologies ConceptNet and WordNet. In addition, it contains information about quantifiers, argument modifiers, and links the entities to appropriate concepts in Wikipedia and WordNet.
  • Licence : Aucune licence connue
  • Version : 0.0.0
  • Fractionnements :
Diviser Exemples
'train' 49848
  • Caractéristiques :
{
    "arg1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "arg2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "score": {
        "dtype": "float64",
        "id": null,
        "_type": "Value"
    },
    "wikipedia_primary_page": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "synset": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}
,

Références:

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:has_part')
  • Descriptif :
This dataset is a new knowledge-base (KB) of hasPart relationships, extracted from a large corpus of generic statements. Complementary to other resources available, it is the first which is all three of: accurate (90% precision), salient (covers relationships a person may mention), and has high coverage of common terms (approximated as within a 10 year old’s vocabulary), as well as having several times more hasPart entries than in the popular ontologies ConceptNet and WordNet. In addition, it contains information about quantifiers, argument modifiers, and links the entities to appropriate concepts in Wikipedia and WordNet.
  • Licence : Aucune licence connue
  • Version : 0.0.0
  • Fractionnements :
Diviser Exemples
'train' 49848
  • Caractéristiques :
{
    "arg1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "arg2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "score": {
        "dtype": "float64",
        "id": null,
        "_type": "Value"
    },
    "wikipedia_primary_page": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "synset": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}