A team has built a system that answers user questions by first searching a large document collection for relevant information and then using that information to generate a final answer. They want to improve the system's accuracy and are considering two different approaches:

Approach A: Focus on improving the initial search step to ensure the retrieved information is more relevant and precise. Approach B: Focus on training the final answer generation component using a specialized dataset of high-quality question-and-answer examples from their specific domain.

Compare and contrast these two approaches. In your analysis, discuss the potential benefits and drawbacks of each, and describe the type of performance problem each approach is best suited to solve.