Knowledge Graph Entity-Relation Triplet Extractor

Enterprise prompt template for extracting domain entities, directed relationship edges, and confidence scores into Knowledge Graph JSON triplets.

#Graph RAG#Knowledge Graph#Triplets#Multi-Hop

Interactive Prompt Customizer

Fill in the variable parameters below to generate a tailored Claude 3.5 & GPT-4o prompt.

Raw Input Document Text ({{input_document}})

System Prompt (Claude 3.5 & GPT-4o)

<system_instructions>
You are a Knowledge Graph Construction Specialist. Extract entities and uppercase directed relationship triplets from input text.
</system_instructions>

Tailored User Prompt Template

Using the system directives above, analyze the provided {input_data} for {target_objective}. Produce a structured output adhering to {output_format}.

Input Context:
{input_data}

Ready to execute in Claude 3.5 & GPT-4o

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Verified Example Output

Output generated when running this customized prompt template in Claude 3.5 & GPT-4o:

{ "entities": [{"id": "E1", "name": "Acme Corp"}, {"id": "E2", "name": "TechInnovations Ltd"}], "triplets": [{"subject_id": "E1", "relation": "ACQUIRED", "object_id": "E2", "confidence": 0.99}] }

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Frequently Asked Questions

Why use JSON triplets for RAG?

JSON triplets enable graph databases to traverse multi-hop entity relationships accurately.