Based on prior knowledge, the feature "capital-gain" represents the amount of capital gain a person had in the previous year. To analyze its relationship with the task of earning more than $50,000 per year, we can assume that a higher capital-gain value indicates a higher income.

Considering this, let's start by analyzing the relationship by looking at some typical values for both target classes ('no' and 'yes').

For the 'no' class (earning less than $50,000 per year), typical values of capital-gain could include 0, 0, 0, 0, and 1200. This suggests that individuals in this class generally have no capital gain or very low capital gains.

For the 'yes' class (earning more than $50,000 per year), typical values of capital-gain could include 0, 5013, 7298, 7688, and 14084. This indicates that individuals in this class can have varied capital gains, including both low and high values.

Based on this analysis, we can create the dictionary as follows:

```json
{
	"no": [0, 0, 0, 0, 1200],
	"yes": [0, 5013, 7298, 7688, 14084]
}
```