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hotpot_qa

References:

distractor

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:hotpot_qa/distractor')
  • Description:
HotpotQA is a new dataset with 113k  Wikipedia-based question-answer  pairs with  four  key  features:  (1)  the  questions  require finding and reasoning over multiple supporting  documents  to  answer;  (2)  the  questions  are  diverse  and  not  constrained  to  any pre-existing  knowledge  bases  or  knowledge schemas;  (3)  we  provide  sentence-level  supporting facts required for reasoning, allowingQA systems to reason with strong supervisionand explain the predictions; (4) we offer a new type  of  factoid  comparison  questions  to  testQA  systems’  ability  to  extract  relevant  facts and perform necessary comparison.
  • License: No known license
  • Version: 1.0.0
  • Splits:
Split Examples
'train' 90447
'validation' 7405
  • Features:
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "type": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "level": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "supporting_facts": {
        "feature": {
            "title": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sent_id": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "context": {
        "feature": {
            "title": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sentences": {
                "feature": {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

fullwiki

Use the following command to load this dataset in TFDS:

ds = tfds.load('huggingface:hotpot_qa/fullwiki')
  • Description:
HotpotQA is a new dataset with 113k  Wikipedia-based question-answer  pairs with  four  key  features:  (1)  the  questions  require finding and reasoning over multiple supporting  documents  to  answer;  (2)  the  questions  are  diverse  and  not  constrained  to  any pre-existing  knowledge  bases  or  knowledge schemas;  (3)  we  provide  sentence-level  supporting facts required for reasoning, allowingQA systems to reason with strong supervisionand explain the predictions; (4) we offer a new type  of  factoid  comparison  questions  to  testQA  systems’  ability  to  extract  relevant  facts and perform necessary comparison.
  • License: No known license
  • Version: 1.0.0
  • Splits:
Split Examples
'test' 7405
'train' 90447
'validation' 7405
  • Features:
{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "type": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "level": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "supporting_facts": {
        "feature": {
            "title": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sent_id": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "context": {
        "feature": {
            "title": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sentences": {
                "feature": {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}