GastroCorp: A Bilingual Gastronomic NER Corpus (Spanish–English)

GastroCorp is a bilingual (Spanish–English) gastronomic corpus for Named Entity Recognition (NER), constructed through human annotation by 71 university students at Universidad Tecnológica de Bolívar (Cartagena, Colombia) using Label Studio. Corpus Statistics 21,385 annotated tasks (16,587 menus · 4,798 recipes) 86,320 clean entities across four types: DISH, BEVERAGE, INGREDIENT, BRAND Split: 70% train / 15% dev / 15% test (stratified by entity type) Inter-annotator agreement: Cohen's κ = 0.9031 (Almost perfect) · Pairwise F1 = 0.9727 (Brandsen et al., 2020) Annotation period: October–December 2025 Entity Types DISH: complete dish names in menus (e.g., "Lomo saltado", "Grilled salmon") BEVERAGE: drinks listed as final products (e.g., "Mojito", "Café americano") INGREDIENT: individual components in menu descriptions and recipes BRAND: commercial names and registered trademarks Each entity is annotated with semantic attributes (cooking method, preparation state, culinary origin, language, beverage type, etc.). Files menu_{train,dev,test}.jsonl — Menu annotations in HuggingFace Datasets format recipe_{train,dev,test}.jsonl — Recipe annotations in HuggingFace Datasets format All files follow the HuggingFace NER JSONL format with aligned token/tag sequences and full entity metadata. Labels use English names (DISH, BEVERAGE, INGREDIENT, BRAND) for international interoperability. Data Sources Menus: provided by CLUVI (Colombia) under academic use agreement Recipes: RecipeNLG (Bień et al., 2020), HumbleIntelligence Food NER 1M (HuggingFace), TASTEset (Wróblewska et al., 2021) Context This corpus was developed as part of a Master's thesis in Engineering at Universidad Tecnológica de Bolívar, investigating the integration of NER with Neural Machine Translation (NMT) to improve translation quality of gastronomic texts between Spanish and English. License and Use Restrictions This corpus is released under CC BY-NC 4.0 (Attribution-NonCommercial). Academic and research use is permitted with proper attribution. Commercial use is not permitted. The menu data component is derived from a source provided under an academic-only agreement; this restriction applies to the full dataset.