- A
Increase the presence penalty to a positive value, e.g., 0.3
Why wrong: Presence penalty encourages new topics but is less effective at reducing word-level repetition.
- B
Decrease the top-p value to 0.5
Why wrong: Lower top-p makes output more focused but may not reduce repetition.
- C
Increase the temperature to 1.5
Why wrong: Higher temperature may increase randomness but does not specifically target repetition.
- D
Increase the frequency penalty to a positive value, e.g., 0.3
Frequency penalty reduces the likelihood of repeated tokens.
Question 893 of 991
1Z0-1127 Prompt Engineering Practice Question
This 1Z0-1127 practice question tests your understanding of prompt engineering. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 prompt engineer notices that the model's responses are frequently repetitive and contain redundant phrases. Which parameter adjustment is MOST likely to reduce this repetition?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
✓
Increase the frequency penalty to a positive value, e.g., 0.3
Option D is correct because increasing the frequency penalty (e.g., to 0.3) directly penalizes tokens that have already appeared in the generated text, reducing the likelihood of the model repeating the same phrases. This parameter is specifically designed to discourage repetition by subtracting a fixed amount from the log-probability of each token each time it has been generated, making it the most targeted adjustment for this issue.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the presence penalty to a positive value, e.g., 0.3
Why it's wrong here
Presence penalty encourages new topics but is less effective at reducing word-level repetition.
- ✗
Decrease the top-p value to 0.5
Why it's wrong here
Lower top-p makes output more focused but may not reduce repetition.
- ✗
Increase the temperature to 1.5
Why it's wrong here
Higher temperature may increase randomness but does not specifically target repetition.
- ✓
Increase the frequency penalty to a positive value, e.g., 0.3
Why this is correct
Frequency penalty reduces the likelihood of repeated tokens.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between frequency penalty and presence penalty, where candidates mistakenly choose presence penalty (Option A) because they confuse 'penalizing repetition' with 'penalizing topic presence,' not realizing that frequency penalty is the precise parameter for reducing redundant phrases.
Trap categories for this question
Command / output trap
Lower top-p makes output more focused but may not reduce repetition.
Detailed technical explanation
How to think about this question
Under the hood, the frequency penalty works by adding a fixed negative offset (e.g., -0.3) to the logit of each token each time it appears in the generated sequence, effectively lowering its probability of being selected again. This is distinct from the presence penalty, which applies the offset only once per token regardless of frequency. In real-world scenarios, such as generating long-form documentation or code comments, a frequency penalty of 0.2–0.5 is commonly used to maintain lexical diversity without sacrificing coherence.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the 1Z0-1127 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Prompt Engineering — study guide chapter
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FAQ
Questions learners often ask
What does this 1Z0-1127 question test?
Prompt Engineering — This question tests Prompt Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the frequency penalty to a positive value, e.g., 0.3 — Option D is correct because increasing the frequency penalty (e.g., to 0.3) directly penalizes tokens that have already appeared in the generated text, reducing the likelihood of the model repeating the same phrases. This parameter is specifically designed to discourage repetition by subtracting a fixed amount from the log-probability of each token each time it has been generated, making it the most targeted adjustment for this issue.
What should I do if I get this 1Z0-1127 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This 1Z0-1127 practice question is part of Courseiva's free Oracle certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 1Z0-1127 exam.
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