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http://purl.org/dc/terms/title
ENHANCING SUPPLY CHAIN VISIBILITY WITH KNOWLEDGE GRAPHS AND LARGE LANGUAGE MODELS
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This framework proposes a novel zero-shot, LLM-driven approach to construct knowledge graphs from public data. It specifically leverages LLMs (e.g., GPT-4) with carefully crafted prompts for Named Entity Recognition (NER), Relation Extraction (RE), and Entity Disambiguation. The extracted and structured information is then used to build a comprehensive knowledge graph to enhance supply chain visibility.
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