CafeteriaFCD Corpus: Food Consumption Data Annotated with Regard to Different Food Semantic Resources

Abstract

Besides the numerous studies in the last decade involving food and nutrition data, this domain remains low resourced. Annotated corpuses are very useful tools for researchers and experts of the domain in question, as well as for data scientists for analysis. In this paper, we present the annotation process of food consumption data (recipes) with semantic tags from different semantic resources—Hansard taxonomy, FoodOn ontology, SNOMED CT terminology and the FoodEx2 classification system. FoodBase is an annotated corpus of food entities—recipes—which includes a curated version of 1000 instances, considered a gold standard. In this study, we use the curated version of FoodBase and two different approaches for annotating—the NCBO annotator (for the FoodOn and SNOMED CT annotations) and the semi-automatic StandFood method (for the FoodEx2 annotations). The end result is a new version of the golden standard of the FoodBase corpus, called the CafeteriaFCD (Cafeteria Food Consumption Data) corpus. This corpus contains food consumption data—recipes—annotated with semantic tags from the aforementioned four different external semantic resources. With these annotations, data interoperability is achieved between five semantic resources from different domains. This resource can be further utilized for developing and training different information extraction pipelines using state-of-the-art NLP approaches for tracing knowledge about food safety applications.

Predefined domain specific embeddings of food concepts and recipes: A case study on heterogeneous recipe datasets

“…The two aforementioned goals where both achieved with mapping the ingredients to a food item in the USDA database. We have dealt with this type of mapping in previous studies [35], [40] where we used a lexical similarity approach involving Part of Speech (POS) tagging and probability theory. This method is limited because of its nature to base the matching on intersection of nouns, which the POS tagging method may not capture.…”

CafeteriaSA corpus: scientific abstracts annotated across different food semantic resources

“…A part of the CAFETERIA project also involved the extension of the FoodBase corpus with semantic tags of the annotated mentions of food entities. As a result of this work, the CafeteriaFCD corpus ( 30 ) was produced, which is a version of the FoodBase corpus where the annotated food entities are linked to the Hansard taxonomy and the FoodOn and SNOMED-CT ontologies. The same methodology for automatic linking of the mentions of food entities in the text to the identifiers in the FoodOn and SNOMED-CT ontologies is used for adding the semantic tags to both the CafeteriaFCD corpus and the CafeteriaSA corpus (presented as a part of this work).…”