Extending FKG.in: Towards a Food Claim Traceability Network

2025-08-22

AI Summary

Global food health claims originate from heterogeneous, unverified sources, lacking a unified, traceable infrastructure. To address this, we propose the Food Claims Traceability Network (FCN), an extension of the Indian Food Knowledge Graph (FKG.in), establishing the first traceability framework specifically designed for food health claims. Methodologically, we design a domain-specific ontology and integrate Reddit-based data mining, large language model–driven information extraction, source-aware knowledge fusion, and knowledge graph construction to enable cross-cultural, multi-source structural modeling and provenance tracking of claims. Our contributions are threefold: (1) a three-tier traceability mechanism linking claims to supporting evidence and original sources; (2) an end-to-end proof-of-concept system—FKG.in-FCN—that automatically extracts claims from unstructured text, assesses their credibility, and anchors them in contextual provenance; and (3) substantial improvements in dietary information transparency and scientific verifiability.

Technology Category

• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Application Domains: Misinformation & Fake News

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Security and Privacy: Data transparency and provenance

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.

Problem

• Tracing fragmented food claims across scientific and cultural contexts
• Verifying health benefits and misrepresentations in dietary assertions
• Building structured ontology for transparent food knowledge ecosystems

Innovation

• Food Claim-Traceability Network extension
• Ontology design with semi-automated curation
• Provenance-aware claim extraction pipelines