Exam NCA-GENL Topic 6 Question 43 Discussion

Actual exam question for NVIDIA's NCA-GENL exam
Question #: 43
Topic #: 6

In Exploratory Data Analysis (EDA) for Natural Language Understanding (NLU), which method is essential for understanding the contextual relationship between words in textual data?

A. Computing the frequency of individual words to identify the most common terms in a text. B. Applying sentiment analysis to gauge the overall sentiment expressed in a text. C. Generating word clouds to visually represent word frequency and highlight key terms. D. Creating n-gram models to analyze patterns of word sequences like bigrams and trigrams.

Suggested Answer: D Vote an answer

In Exploratory Data Analysis (EDA) for Natural Language Understanding (NLU), creating n-gram models is essential for understanding the contextual relationships between words, as highlighted in NVIDIA's Generative AI and LLMs course. N-grams (e.g., bigrams, trigrams) capture sequences of words, revealing patterns and dependencies in text, such as common phrases or syntactic structures, which are critical for NLU tasks like text generation or classification. Unlike single-word frequency analysis, n-grams provide insight into how words relate to each other in context. Option A is incorrect, as computing word frequencies focuses on individual terms, missing contextual relationships. Option B is wrong, as sentiment analysis targets overall text sentiment, not word relationships. Option C is inaccurate, as word clouds visualize frequency, not contextual patterns. The course notes: "N-gram models are used in EDA for NLU to analyze word sequence patterns, such as bigrams and trigrams, to understand contextual relationships in textual data." References: NVIDIA Building Transformer-Based Natural Language Processing Applications course; NVIDIA Introduction to Transformer-Based Natural Language Processing.

by Dean at Sep 26, 2025, 12:54 AM

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