FoodSafeSum: Enabling Natural Language Processing Applications for Food Safety Document Summarization and Analysis (2025.findings-emnlp)
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Juli Bakagianni, Korbinian Randl, Guido Rocchietti, Cosimo Rulli, Franco Maria Nardini, Salvatore Trani, Aron Henriksson, Anna Romanova, John Pavlopoulos
| Challenge: | a lack of structured datasets hinders natural language processing research . a new dataset of food safety documents and related metadata is presented . |
| Approach: | They present a dataset of human-written and Large Language Model (LLM)-generated food safety documents . they evaluate their utility on three NLP tasks directly reflecting food safety practices . |
| Outcome: | The proposed dataset performs comparably or better than human summaries on three NLP tasks . it also shows clustering of summary for event tracking and compliance monitoring . |
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