In watsonx.governance, which text quality metric measures n-gram overlap between generated text and reference texts with an emphasis on recall?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Think of it this way: in real-world AI governance, rouge is exactly what teams reach for when they need to handle this scenario. ROUGE (Recall-Oriented Understudy for Gisting Evaluation) is the recall-focused n-gram metric used for summarization. On the exam, remember that this falls squarely under the 4.0 Configure Evaluation and Monitoring domain.
Full explanation below image
Full Explanation
ROUGE (Recall-Oriented Understudy for Gisting Evaluation) is the recall-focused n-gram metric used for summarization. BLEU focuses on precision. METEOR balances both. SARI compares against both reference and original source input, making it specific to text simplification. The correct answer, "ROUGE", directly addresses the scenario described because it aligns with the specific governance requirement in question. The incorrect options ("BLEU", "METEOR", "SARI") may seem plausible but do not satisfy the core requirement. Understanding the distinction between these concepts is critical for IBM watsonx.governance implementations and is frequently tested in the 4.0 Configure Evaluation and Monitoring section of the certification exam.