- A
Use a larger retrieval chunk size
Why wrong: More context may help, but doesn't directly enforce factual grounding.
- B
Increase the temperature
Why wrong: Higher temperature increases randomness, worsening hallucinations.
- C
Use prompt engineering to instruct the model to stick to the provided context
Explicitly instructing the model to base answers only on the given context reduces hallucination.
- D
Decrease the maximum token length
Why wrong: Shorter outputs may still hallucinate.
Quick Answer
The correct answer is to use prompt engineering to instruct the model to stick to the provided context. This works because retrieval-augmented generation (RAG) systems can hallucinate when the generative model over-relies on its parametric knowledge instead of the retrieved documents; a well-crafted system prompt explicitly constrains the model’s reasoning to the supplied context, effectively reducing hallucination in RAG with prompt engineering. On the Oracle Cloud Infrastructure Generative AI Professional 1Z0-1127 exam, this question tests your understanding of how to combine OCI Generative AI with a custom OCI OpenSearch vector store, and the common trap is assuming that better retrieval alone fixes the issue—without prompt constraints, the model may still invent facts. A useful memory tip is “Context is king, prompt the thing,” reminding you that a clear instruction to use only the provided context is the most direct mitigation.
1Z0-1127 Practice Question: Building LLM Applications with RAG and Vector Search
This 1Z0-1127 practice question tests your understanding of building llm applications with rag and vector search. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A developer uses OCI Generative AI with a custom OCI OpenSearch vector store. The text generation model sometimes hallucinates facts not in the retrieved documents. What is the most effective mitigation?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use prompt engineering to instruct the model to stick to the provided context
Prompt engineering with clear instructions to use only the provided context is a direct and effective way to reduce hallucination.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a larger retrieval chunk size
Why it's wrong here
More context may help, but doesn't directly enforce factual grounding.
- ✗
Increase the temperature
Why it's wrong here
Higher temperature increases randomness, worsening hallucinations.
- ✓
Use prompt engineering to instruct the model to stick to the provided context
Why this is correct
Explicitly instructing the model to base answers only on the given context reduces hallucination.
Related concept
Static NAT maps one inside address to one outside address.
- ✗
Decrease the maximum token length
Why it's wrong here
Shorter outputs may still hallucinate.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Trap categories for this question
Command / output trap
Shorter outputs may still hallucinate.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related 1Z0-1127 NAT questions on configuration and troubleshooting.
- →
Building LLM Applications with RAG and Vector Search — study guide chapter
Learn the concepts, then practise the questions
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Building LLM Applications with RAG and Vector Search practice questions
Targeted practice on this topic area only
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FAQ
Questions learners often ask
What does this 1Z0-1127 question test?
Building LLM Applications with RAG and Vector Search — This question tests Building LLM Applications with RAG and Vector Search — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Use prompt engineering to instruct the model to stick to the provided context — Prompt engineering with clear instructions to use only the provided context is a direct and effective way to reduce hallucination.
What should I do if I get this 1Z0-1127 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related 1Z0-1127 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 23, 2026
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