NCA-GENM Question 126
Select 2A developer is building a multimodal generative AI application that processes text input and generates contextually relevant content. They need to perform named entity recognition (NER), compute vector representations for text, and store these vectors for efficient similarity searches. Which combination of Python tools is best suited for this workflow?
- A
spaCy for named entity recognition, NumPy for vector storage, and a vector database for similarity searches
- B
spaCy for named entity recognition, a vector database for storing and searching vectors, and NumPy for vector computations
- C
NumPy for named entity recognition, spaCy for vector computation, and a vector database for storing and searching vectors
- D
spaCy for named entity recognition, NumPy for basic vector computations, and a vector database for storing and searching vectors
- E
A vector database for named entity recognition, NumPy for similarity searches, and spaCy for vector storage
Show answer and explanation
Correct answers: B, D
Explanation
The correct answers involve using spaCy for named entity recognition, as it is a widely used NLP library for tasks like NER. NumPy is ideal for numerical computations, including basic vector operations. A vector database is specifically optimized for storing and performing similarity searches on vectorized data, making it a critical component for such workflows. Combining these tools ensures an efficient and scalable implementation of the described multimodal generative AI application.
- A. Incorrect.
Incorrect: While spaCy is excellent for named entity recognition, NumPy is not designed for efficient vector storage. A vector database is better suited for similarity searches.
- B. Correct.
Correct: This option correctly assigns spaCy for NER, uses a vector database for storing and searching vectors, and utilizes NumPy for vector computations, which is a common and efficient workflow.
- C. Incorrect.
Incorrect: NumPy is not used for named entity recognition, and spaCy is not typically used for vector computation. This workflow is impractical.
- D. Correct.
Correct: spaCy is used for NER, NumPy for basic vector computations, and a vector database for efficient storage and similarity searches. This is a practical and valid approach.
- E. Incorrect.
Incorrect: A vector database is not used for named entity recognition, and NumPy is not optimized for similarity searches. This combination is incorrect.