e2e_nlg

ds = tfds.load('huggingface:e2e_nlg')

The E2E dataset is used for training end-to-end, data-driven natural language generation systems in the restaurant domain, which is ten times bigger than existing, frequently used datasets in this area.
The E2E dataset poses new challenges:
(1) its human reference texts show more lexical richness and syntactic variation, including discourse phenomena;
(2) generating from this set requires content selection. As such, learning from this dataset promises more natural, varied and less template-like system utterances.


E2E is released in the following paper where you can find more details and baseline results:
https://arxiv.org/abs/1706.09254

{
    "meaning_representation": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "human_reference": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}