Building a Test Suite: The Graph Benchmark

A test suite of "What is Sudeep's name?" is useless. You need questions that Break your system. To truly evaluate a Graph RAG implementation, you need as "Stress Test" that pushes the boundaries of multi-hop paths, conflicting dates, and ambiguous entities.

In this lesson, we will look at how to build a Comprehensive Graph Test Suite. We will categorize questions by the "Complexity Level" and learn how to use the "Gold Standard Answer" pattern (where a human provides the perfect answer to compare against). We will see why a good test suite is the only way to safely iterate on your Graph Schema or your Retrieval Chain.

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1. The 4 Levels of Graph Questions

Level 1: Point Retrieval (Precision)

• "What is the budget of Project Titan?"
• Test: Does it find the correct single attribute?

Level 2: Direct Relationship (Connectivity)

• "Who is the manager of the person who leads Project Titan?"
• Test: Can it handle exactly 2 hops correctly?

Level 3: Global Aggregation (Summarization)

• "How many active projects do we have in the Tokyo office?"
• Test: Can it count and filter across a whole community?

Level 4: Hidden Influence (Inference/Logic)

• "If Project A is delayed, which customer-facing services will be affected?"
• Test: Can it navigate a deep (4+ hop) chain of dependencies?

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2. The "Gold Standard" Dataset

For every question in your suite, you should have:

1. Question: The user input.
2. Logic Path: The Cypher query that should be run.
3. Gold Result: The raw data from the DB.
4. Gold Answer: A human-written ideal response.

Why? When you update your LLM to a new version, you run the whole suite. If the "Pass Rate" drops from 95% to 80%, you know exactly which type of logic the new model is struggling with.

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3. Synthetic Question Generation

Can you use an AI to write the tests? Yes.

• Give an LLM your Graph Schema.
• Ask: "Generate 5 complex multi-hop questions that involve the 'WORKS_AT' and 'CONTRASTS_WITH' relationships."

This is a great way to "Flood" your testing environment with thousands of cases that you wouldn't have thought of manually.

graph TD
    S[Schema] --> G[Synthetic Quest Gen]
    G --> Q[Test Suite]
    H[Human Expert] --> Q
    Q --> B[Benchmark Engine]
    B -->|ScoreCard| D[Developer]
    
    style Q fill:#f4b400,color:#fff

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4. Implementation: A JSON Test Suite Structure

[
  {
    "id": "T-001",
    "level": "Multi-Hop",
    "question": "What is the security clearance of Project Titan's lead?",
    "target_nodes": ["Project", "Person", "Clearance"],
    "expected_cypher": "MATCH (p:Project {id:'Titan'})<-[:LEADS]-(pers)-[:HAS_CLEARANCE]->(c) RETURN c.level"
  }
]

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5. Summary and Exercises

A test suite is the "Gym" where your AI gets stronger.

• Categorization by complexity identifies specific failure points.
• Multi-hop questions are the true test of "Graph Thinking."
• Synthetic generation provides scale for testing.
• Gold Standard answers provide the ground truth for judgment.

Exercises

1. Test Writing: Write a "Level 4" question for a graph about "Global Supply Chains." What kind of "Hidden Influence" could occur? (e.g., A factory fire in Taiwan affecting a car dealership in Germany).
2. Level Check: Is the question "Who works in the London office?" a Level 1 or Level 2 question? Why?
3. Visualization: Draw a 5-hop relationship chain. Now, write a question whose answer requires the AI to find every node in that chain.

In the next lesson, we will look at specifically measuring the "Lie": Measuring Hallucination in Multi-Hop Reasoning.