Predicting the Structure of Cooking Recipes

Cooking recipes exist in abundance; but due to their unstructured text format, they are hard to study quantitatively beyond treating them as simple bags of words. In this paper, we propose an ingredient-instruction dependency tree data structure to represent recipes. The proposed rep-resentation allows for more refined com-parison of recipes and recipe-parts, and is a step towards semantic representation of recipes. Furthermore, we build a parser that maps recipes into the proposed rep-resentation. The parser’s edge prediction accuracy of 93.5 % improves over a strong baseline of 85.7 % (54.5 % error reduction). 1