generics_kb

ds = tfds.load('huggingface:generics_kb/generics_kb_best')

The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as "Dogs bark," and "Trees remove carbon dioxide from the atmosphere." Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.

{
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "term": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "quantifier_frequency": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "quantifier_number": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "generic_sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "score": {
        "dtype": "float64",
        "id": null,
        "_type": "Value"
    }
}

ds = tfds.load('huggingface:generics_kb/generics_kb')

The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as "Dogs bark," and "Trees remove carbon dioxide from the atmosphere." Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.

{
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "term": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "quantifier_frequency": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "quantifier_number": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "generic_sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "score": {
        "dtype": "float64",
        "id": null,
        "_type": "Value"
    }
}

ds = tfds.load('huggingface:generics_kb/generics_kb_simplewiki')

The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as "Dogs bark," and "Trees remove carbon dioxide from the atmosphere." Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.

{
    "source_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentences_before": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "sentences_after": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "concept_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "quantifiers": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "bert_score": {
        "dtype": "float64",
        "id": null,
        "_type": "Value"
    },
    "headings": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "categories": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ds = tfds.load('huggingface:generics_kb/generics_kb_waterloo')

The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as "Dogs bark," and "Trees remove carbon dioxide from the atmosphere." Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.

{
    "source_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentences_before": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "sentences_after": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "concept_name": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "quantifiers": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "bert_score": {
        "dtype": "float64",
        "id": null,
        "_type": "Value"
    }
}