Revisiting Named Entity Recognition in Food Computing: Enhancing Performance and Robustness

Abstract

Food computing requires reliable extraction of food-related named entities — ingredients, nutrients, preparation methods, and health signals — from unstructured text. We revisit NER approaches for this domain, diagnosing failure modes and improving performance and robustness across food-specific corpora.