A framework for recipe data structure with applications for culinary and nutritional insights

食谱数据结构框架及其在烹饪与营养洞察中的应用

Abstract: Cooking is a complex process that transforms raw ingredients into delicious and nutritious dishes, yet the recipes that encode this process remain largely free text; readable by people but not directly computable. Existing recipe collections capture fragments of this information, but no shared representation links a recipe’s structured ingredient composition, its geo-cultural provenance, and its nutritional profile within a single queryable schema.

摘要： 烹饪是一个将原始食材转化为美味且营养丰富的菜肴的复杂过程，然而，编码这一过程的食谱大多仍以自由文本形式存在；它们虽然易于人类阅读，却无法直接进行计算。现有的食谱集合仅捕捉了这些信息的部分片段，尚无一种共享的表示方法能够将食谱的结构化成分组成、地理文化来源及其营养概况整合在一个可查询的单一架构中。

We address this representation gap by formalizing a framework for recipe data structure that decomposes each recipe into typed ingredient entities, grounds those entities in a reference nutritional database, and annotates them with geo-cultural and dietary context. We present RecipeDB2, a structured compilation of 128,942 recipes with 35,474 ingredients from 32 regions and 99 countries.

我们通过规范化一种食谱数据结构框架来解决这一表示鸿沟，该框架将每份食谱分解为类型化的食材实体，将这些实体关联至参考营养数据库，并标注其地理文化和饮食背景。我们推出了 RecipeDB2，这是一个包含来自 32 个地区和 99 个国家的 128,942 份食谱及 35,474 种食材的结构化汇编。

Ingredient phrases are parsed into seven culinary attributes using a transformer-based named-entity model; ingredients are linked to the USDA reference tables through a BERT embedding strategy (F1 = 87.90 on a manually adjudicated set of the 200 most frequent ingredients), yielding 148 nutritional parameters per mapped ingredient; a Random Forest classifier propagates 34 ingredient categories across the full vocabulary; and a deterministic, conservative rule set assigns each recipe a dietary style.

利用基于 Transformer 的命名实体模型，食材短语被解析为七种烹饪属性；通过 BERT 嵌入策略将食材与美国农业部（USDA）参考表进行关联（在 200 种最常见食材的人工裁定集上 F1 分数达到 87.90），为每种映射的食材提供 148 项营养参数；随机森林分类器在整个词汇表中传播 34 种食材类别；此外，一套确定性的保守规则集为每份食谱分配了饮食风格。

Through RecipeDB2, we demonstrate a scalable framework for making recipes computable, turning culinary heritage (long treated as an artistic rather than a quantitative object) into a data-driven analysis.

通过 RecipeDB2，我们展示了一个使食谱可计算的可扩展框架，将烹饪遗产（长期以来被视为艺术而非定量对象）转化为数据驱动的分析。