Unverified50% confidenceOpinionExact time
In the era of large models, knowledge graph and ontology technologies are playing an increasingly important role in scenarios such as retrieval-augmented generation (RAG), intelligent question answering, and enterprise knowledge management.
1
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50%
Confidence
Medium-term (~90 days)
Relevance
11/3/2026
First Seen
Valid until: 2/1/2027
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Related Claims
UnverifiedThere are three main technical approaches to injecting external knowledge into large language models: fine-tuning, retrieval-augmented generation (RAG), and structured semantic layer/ontology injection.78% similarUnverifiedThe industry best practice is to combine fine-tuning with RAG—first fine-tuning to give the model domain understanding capability, then supplementing the latest dynamic knowledge through RAG.78% similarUnverifiedWhen needed, persistent knowledge is recalled by semantic relevance through RAG (Retrieval-Augmented Generation) technology and then injected into the Prompt.77% similarVerified检索增强生成（RAG）通过基于真实知识库内容回答来解决大模型的幻觉问题76% similar
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