Omkar2118/datasets huggingface dataset:
E2E
Full name: End-to-End NLG Challenge

End-to-End NLG Challenge (E2E) aims to assess whether recent end-to-end NLG systems can generate more complex output by learning from datasets containing higher lexical richness, syntactic complexity and diverse discourse phenomena.

Source: [Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge](/paper/evaluating-the-state-of-the-art-of-end-to-end)

Introducing paper: The E2E Dataset: New Challenges For End-to-End Generation