Based on prior knowledge, the feature "capital-gain" represents the capital gain a person had in the previous year. To determine the relationship between this feature and the task of whether someone earns more than $50,000 per year, we can analyze the distribution of capital-gain values for each target class.

Here is the analysis:

For the target class "no" (earning less than or equal to $50,000 per year):
- The feature "capital-gain" tends to have lower values, indicating that individuals earning less money have less capital gain opportunities.
- Typical capital-gain values for this class could include 0, 1000, 2000, 3000, and 4000.

For the target class "yes" (earning more than $50,000 per year):
- The feature "capital-gain" tends to have higher values, indicating that individuals earning more money have more significant capital gains.
- Typical capital-gain values for this class could include 10000, 20000, 30000, 40000, and 50000.

Based on this analysis, we can create the following dictionary:

```json
{
	"no": [0, 1000, 2000, 3000, 4000],
	"yes": [10000, 20000, 30000, 40000, 50000]
}
```