Extending FKG.in: Towards a Food Claim Traceability Network

August 22, 2025 Β· Declared Dead Β· πŸ› Proceedings of the 1st International Workshop on Multi-modal Food Computing

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Saransh Kumar Gupta, Rizwan Gulzar Mir, Lipika Dey, Partha Pratim Das, Anirban Sen, Ramesh Jain arXiv ID 2508.16117 Category cs.AI: Artificial Intelligence Cross-listed cs.CL, cs.IR Citations 0 Venue Proceedings of the 1st International Workshop on Multi-modal Food Computing Last Checked 4 months ago
Abstract
The global food landscape is rife with scientific, cultural, and commercial claims about what foods are, what they do, what they should not do, or should not do. These range from rigorously studied health benefits (probiotics improve gut health) and misrepresentations (soaked almonds make one smarter) to vague promises (superfoods boost immunity) and culturally rooted beliefs (cold foods cause coughs). Despite their widespread influence, the infrastructure for tracing, verifying, and contextualizing these claims remains fragmented and underdeveloped. In this paper, we propose a Food Claim-Traceability Network (FCN) as an extension of FKG[.]in, a knowledge graph of Indian food that we have been incrementally building. We also present the ontology design and the semi-automated knowledge curation workflow that we used to develop a proof of concept of FKG[.]in-FCN using Reddit data and Large Language Models. FCN integrates curated data inputs, structured schemas, and provenance-aware pipelines for food-related claim extraction and validation. While directly linked to the Indian food knowledge graph as an application, our methodology remains application-agnostic and adaptable to other geographic, culinary, or regulatory settings. By modeling food claims and their traceability in a structured, verifiable, and explainable way, we aim to contribute to more transparent and accountable food knowledge ecosystems, supporting researchers, policymakers, and most importantly, everyday consumers in navigating a world saturated with dietary assertions.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Artificial Intelligence

Died the same way β€” πŸ‘» Ghosted