enriched_web_nlg

منابع:

en

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:enriched_web_nlg/en')
  • شرح :
WebNLG is a valuable resource and benchmark for the Natural Language Generation (NLG) community. However, as other NLG benchmarks, it only consists of a collection of parallel raw representations and their corresponding textual realizations. This work aimed to provide intermediate representations of the data for the development and evaluation of popular tasks in the NLG pipeline architecture (Reiter and Dale, 2000), such as Discourse Ordering, Lexicalization, Aggregation and Referring Expression Generation.
  • مجوز : CC Attribution-NonCommercial-Share Alike 4.0 International
  • نسخه : 0.0.0
  • تقسیم ها :
شکاف مثال ها
'dev' 872
'test' 1862
'train' 6940
  • امکانات :
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    "lex": {
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                "_type": "Value"
            },
            "lid": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "template": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sorted_triple_sets": {
                "feature": {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "lexicalization": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

de

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:enriched_web_nlg/de')
  • شرح :
WebNLG is a valuable resource and benchmark for the Natural Language Generation (NLG) community. However, as other NLG benchmarks, it only consists of a collection of parallel raw representations and their corresponding textual realizations. This work aimed to provide intermediate representations of the data for the development and evaluation of popular tasks in the NLG pipeline architecture (Reiter and Dale, 2000), such as Discourse Ordering, Lexicalization, Aggregation and Referring Expression Generation.
  • مجوز : CC Attribution-NonCommercial-Share Alike 4.0 International
  • نسخه : 0.0.0
  • تقسیم ها :
شکاف مثال ها
'dev' 872
'train' 6940
  • امکانات :
{
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        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "size": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "eid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "original_triple_sets": {
        "feature": {
            "otriple_set": {
                "feature": {
                    "dtype": "string",
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                },
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                "id": null,
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        },
        "length": -1,
        "id": null,
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    },
    "modified_triple_sets": {
        "feature": {
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        },
        "length": -1,
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    },
    "shape": {
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        "id": null,
        "_type": "Value"
    },
    "shape_type": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "lex": {
        "feature": {
            "comment": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "lid": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "template": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sorted_triple_sets": {
                "feature": {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                },
                "length": -1,
                "id": null,
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            }
        },
        "length": -1,
        "id": null,
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    }
}