Based on prior knowledge, the "relationship" feature can provide valuable insights into a person's earnings. Here is the analysis:

1. Own-child: It is likely that individuals who are "Own-child" earn less than $50,000 per year. This category may indicate younger individuals who are still dependent on their parents.

2. Husband/Wife: Individuals who are categorized as "Husband" or "Wife" might have a higher chance of earning more than $50,000 per year. These categories may represent individuals who are more likely to be the breadwinners in a household.

3. Not-in-family/Unmarried: The "Not-in-family" and "Unmarried" categories can include a wide range of possibilities, making it difficult to predict their earnings. Therefore, it is not possible to make specific assumptions based solely on these categories.

4. Other-relative: Similar to the "Not-in-family" and "Unmarried" categories, the "Other-relative" category is too broad to make reliable predictions about earnings.

Based on this analysis, the dictionary would look like this:

```json
{
	"no": ["Own-child", "Not-in-family", "Unmarried", "Other-relative"],
	"yes": ["Husband", "Wife"]
}
```