NCA-GENL exam dumps

NCA-GENL practice question 37 of 228

NVIDIA-Certified Associate - Generative AI LLMs. Associate level, NVIDIA. Free question with the correct answer and a full explanation.

NCA-GENL Question 37

Select 2

You are building a generative AI application that requires extracting entities from text and representing them as numerical vectors to perform similarity searches in a vector database. Which combination of Python packages would be most suitable for this task?

  1. A

    spaCy for entity extraction and NumPy for creating numerical vectors

  2. B

    spaCy for entity extraction and a vector database like FAISS for similarity search

  3. C

    NumPy for entity extraction and spaCy for creating numerical vectors

  4. D

    FAISS for entity extraction and NumPy for similarity search

  5. E

    spaCy for entity extraction and FAISS for storing and querying vectors

Show answer and explanation

Correct answers: B, E

Explanation

The correct combination involves using spaCy for entity extraction from text and FAISS as a vector database for similarity search. SpaCy is optimized for natural language processing tasks, such as named entity recognition, while FAISS is designed to efficiently store and query high-dimensional vectors. NumPy is useful for numerical operations but is not specialized for entity extraction or vector database tasks.

  • A. Incorrect.

    While spaCy is suitable for entity extraction, NumPy is not specifically designed for handling similarity searches or serving as a vector database. It focuses on numerical computation and array manipulation.

  • B. Correct.

    This is correct. SpaCy is highly efficient for entity extraction, and FAISS is a specialized library for storing and querying vectors, making it suitable for similarity search tasks.

  • C. Incorrect.

    NumPy is not designed for entity extraction or natural language processing tasks, making this option incorrect. SpaCy, on the other hand, excels at these tasks.

  • D. Incorrect.

    FAISS is not designed for entity extraction, and NumPy is not optimized for similarity searches, so this combination is incorrect.

  • E. Correct.

    This is correct. SpaCy can perform entity extraction from text, and FAISS is a robust vector database for storing and querying numerical representations of text.

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