Based on prior knowledge, marital status can be a relevant feature for predicting income. Generally, individuals who are married or in a civil partnership tend to have higher incomes compared to those who are single, widowed, divorced, or separated.

Based on this analysis, the dictionary for the relationship between marital-status feature and the task of whether a person earns more than 50000 dollars per year can be created as follows:

```json
{
	"no": ["Never-married", "Divorced", "Separated", "Widowed"], 
	"yes": ["Married-civ-spouse", "Married-spouse-absent", "Married-AF-spouse"]
}
```

In this case, the marital-status values "Never-married", "Divorced", "Separated", and "Widowed" are more likely to be associated with individuals who earn less than 50000 dollars per year. On the other hand, the marital-status values "Married-civ-spouse", "Married-spouse-absent", and "Married-AF-spouse" are more likely to be associated with individuals who earn more than 50000 dollars per year.

Note that the values "Never-married", "Divorced", "Separated", "Widowed" have been identified as relevant for the "no" class (earning less than 50000 dollars per year), and the values "Married-civ-spouse", "Married-spouse-absent", "Married-AF-spouse" have been identified as relevant for the "yes" class (earning more than 50000 dollars per year). Other categories of marital status are not included in the dictionary as they might not significantly influence the target variable.