Использованная литература:
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:has_part')
- Описание :
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.
- Лицензия : Лицензия неизвестна
- Версия : 0.0.0
- Сплиты :
| Расколоть | Примеры |
|---|---|
'train' | 49848 |
- Особенности :
{
"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"
}
}
Использованная литература:
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:has_part')
- Описание :
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.
- Лицензия : Лицензия неизвестна
- Версия : 0.0.0
- Сплиты :
| Расколоть | Примеры |
|---|---|
'train' | 49848 |
- Особенности :
{
"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"
}
}