CRWB: A Multilingual Ontology and Knowledge Graph for Recipes

In recent years, the fusion of artificial intelligence and semantic web technologies has paved the way for innovative approaches to managing and utilizing information. With the growing demand for structured gastronomical data, there is a need for well-defined ontologies that facilitate recipe organization, ingredient classification, nutritional insights, and personalized diet recommendations. The dataset presents a multilingual recipe ontology and knowledge graph, capturing critical relationships between ingredients, nutrition, cooking actions, and recipe planning. Our ontology supports interoperability across different languages (English, Hindi, and Japanese), facilitating AI applications such as ingredient substitution and personalized recommendations. The proposed knowledge graph leverages semantic web technologies to enhance structured data accessibility and machine-readable representations, ultimately contributing to computational gastronomy and food informatics.