Based on prior knowledge, the feature "capital-loss" represents the financial loss incurred by an individual in the previous year. To analyze the relationship between this feature and the task of earning more than $50,000 per year, we can assume the following:

1. People with higher capital losses may earn less than $50,000 per year, as these losses can impact their overall financial situation negatively.
2. People with lower or no capital losses may have a higher chance of earning more than $50,000 per year, as they might not have experienced significant financial setbacks.

To create the dictionary with the required format, we can first divide the dataset into two groups based on the task outcome ('no' or 'yes'). Then, we can extract five typical values of "capital-loss" for each group.

```json
{
	"no": [449, 1590, 1876, 1504, 1741],
	"yes": [0, 1902, 1977, 2415, 2559]
}
```

Note that the specific values provided are arbitrary and may vary depending on the dataset being analyzed. The chosen values should be representative of the relationship between the "capital-loss" feature and the target task.