Teaching models to 'Walk' the Path: Chain-of-Topology

In standard RAG, the LLM reads a document. In Graph RAG, the LLM Navigates a Maze. If you give it a 3-hop path: (Sudeep)-[A]-(Project)-[B]-(Deadline)-[C]-(Delayed), the AI must understand that Delayed is attributed to Sudeep because of the chain, not just because they appear in the same paragraph. This is Chain-of-Topology (CoT).

In this lesson, we will look at how to prompt an AI to "Step" through the graph. We will learn how to use Reasoning Benchmarks to guide the model's focus and how to prevent "Short-Circuiting" (where the AI ignores the middle node and makes a faulty direct connection).

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1. The "Short-Circuit" Danger

If you show the AI: Sudeep -> Project Alpha and Project Alpha -> Late, it might say: "Sudeep is late." The Error: Sudeep might have finished his part on time, but the Project is late because of a different person.

The Fix: You must instruct the AI to name every "Edge" in the reasoning. "Trace the path from the person to the delay. State the relationship at each step."

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2. Step-by-Step Prompting (CoT)

We use a specific system instruction to force "Walking" behavior:

INSTRUCTION:
1. Identify the 'Origin Node' from the prompt.
2. Follow the FIRST relationship to the 'Bridge Node'.
3. State the property found at the 'Bridge Node'.
4. Follow the SECOND relationship to the 'Destination Node'.
5. Synthesize the final answer.

By forcing the AI to list the "Hops" internally, you increase logic accuracy by 30-40% for multi-step questions.

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3. The "Edge-First" Philosophy

Teach the AI that Edges are more important than Nouns. A noun (Person) can have many roles. The Edge (:WAS_HIRED_FOR) defines the current role in the context of the question.

graph LR
    P[Sudeep] -- CONTRIBUTED_TO --> R[Repo]
    R -- DEPLOYED_BY --> S[Server]
    S -- STATUS --> C[CRASHED]
    
    subgraph "Reasoning Step 1"
    P --- R
    end
    
    subgraph "Reasoning Step 2"
    R --- S
    end
    
    subgraph "Reasoning Step 3"
    S --- C
    end

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4. Implementation: A CoT Prompt for Graph Paths

QUESTION: Why did the server crash?
GRAPH EVIDENCE:
(Sudeep)-[PUSHED_TO]->(AuthRepo)
(AuthRepo)-[TRIGGERED]->(Build_99)
(Build_99)-[CONTAINS_BUG]->(MemoryLeak)

REASONING:
1. Sudeep pushed code to AuthRepo.
2. This triggered Build_99.
3. Build_99 introduced a MemoryLeak.
ANSWER: The crash was caused by a MemoryLeak from Sudeep's recent push to the AuthRepo.

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5. Summary and Exercises

Walking the path is a Disciplined Activity for the AI.

• Short-circuiting is the most common multi-hop error.
• Edges define the "Why" and "How" of the logic.
• Step-by-step instructions prevent the AI from jumping to "Convenient" conclusions.
• Grounding: If the AI cannot name the bridge node, it shouldn't state the final fact.

Exercises

1. CoT Task: Write the "Reasoning Steps" for the following question: "How is Sudeep connected to the CEO?" Given: (Sudeep)-[:REPORTS_TO]->(Manager) and (Manager)-[:REPORTS_TO]->(CEO).
2. The "Invisible" Hop: If the AI skips the "Manager" and says "Sudeep reports to the CEO," is the answer correct? Is it Traceable?
3. Visualization: Draw a 3-hop path. Label each hop with a number.

In the next lesson, we will look at dynamic retrieval: Recursive Retrieval: The Thinking Agent.