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RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation

Published in INLG, 2020

Semi-structured text generation is a non-trivial problem. Although last years have brought lots of improvements in natural language generation, thanks to the development of neural models trained on large scale datasets, these approaches still struggle with producing structured, context- and commonsense-aware texts. Moreover, it is not clear how to evaluate the quality of generated texts. To address these problems, we introduce RecipeNLG – a novel dataset of cooking recipes. We discuss the data collection process and the relation between the semi-structured texts and cooking recipes. We use the dataset to approach the problem of generating recipes. Finally, we make use of multiple metrics to evaluate the generated recipes.

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In 2019, together with Bartłomiej Borzyszkowski, we had opportunity to present our research at ML in PL - the biggest conference in Poland devoted to artificial intelligence. The recording is available on youtube