1Z0-1127-25 LLM Fundamentals Practice Question
An OCI practitioner is comparing BERTScore with traditional n-gram metrics (ROUGE, BLEU) for evaluating summarization. Which THREE statements about BERTScore are true?
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
✓
BERTScore uses pre-trained contextual embeddings from BERT
BERTScore uses contextual embeddings, captures semantic similarity, and correlates better with human judgment than n-gram metrics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
BERTScore uses pre-trained contextual embeddings from BERT
Why this is correct
It leverages BERT's embeddings to compute semantic similarity.
- ✗
BERTScore does not require a reference text
Why it's wrong here
BERTScore requires a reference for comparison.
- ✗
BERTScore computes similarity based on exact n-gram overlap
Why it's wrong here
BERTScore uses contextual embeddings, not n-gram overlap.
- ✓
BERTScore typically has higher correlation with human judgment than ROUGE
Why this is correct
Studies show BERTScore aligns better with human evaluation.
- ✓
BERTScore is more robust to paraphrasing than ROUGE or BLEU
Why this is correct
Semantic matching captures synonyms and rephrasing.
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