Knowledge Graph + AI: Building Structured Knowledge Systems with LLMs

Knowledge Graph Value

Knowledge graphs store entities and relationships in a graph structure, supporting multi-hop reasoning and complex queries. Combined with AI: first use the graph to retrieve relationship paths, then use AI to generate natural language answers.

Entity Extraction

Use LLMs to extract entities and relationships from text to build knowledge graphs.

{"model":"qwen3.6-plus","messages":[{"role":"system","content":"Extract entities and relationships from the following text in JSON format: {"entities": [{"name": "", "type": ""}], "relations": [{"from": "", "to": "", "type": ""}]}"},{"role":"user","content":"{text}"}]}

Q&A Enhancement

When a user asks a question, first find related entities and paths in the knowledge graph, then pass the graph results along with the original question to AI for answer generation — significantly improving answer accuracy.