Based on my prior knowledge, the feature "capital-loss" represents the capital loss incurred by an individual in the previous year. A capital loss occurs when the selling price of an asset is lower than its original purchase price.

Since the task is to determine whether a person earns more than $50,000 per year, we can analyze the relationship between the feature "capital-loss" and the target variable to identify typical capital loss values for each target class.

Analysis:

- "capital-loss" for target class "no" (individual does not earn more than $50,000 per year):
    - Typically, people with low or no capital loss may have lower incomes. Therefore, we can expect to see values around 0 or very low.
    - Some common values for people not earning more than $50,000 per year could be 0, 1539, 1902, 1887, and 1977.

- "capital-loss" for target class "yes" (individual earns more than $50,000 per year):
    - People who earn more than $50,000 per year may have higher capital losses due to investments or business activities.
    - Some common values for people earning more than $50,000 per year could be 1876, 1974, 1669, 1485, and 2179.

Based on this analysis, the dictionary representing the relationship between the feature "capital-loss" and the target variable "earning more than $50,000 per year" would be:

```json
{
	"no": [0, 1539, 1902, 1887, 1977],
	"yes": [1876, 1974, 1669, 1485, 2179]
}
```