Based on prior knowledge, we can analyze how the feature "workclass" relates to the task of determining whether a person earns more than 50000 dollars per year.

Analyzing the "workclass" feature, we can make a hypothesis that individuals who work in certain categories may have a higher likelihood of earning more than 50000 dollars per year. For example, individuals who are self-employed or work for the federal government may have higher incomes compared to those working in the private sector or local government.

Based on this hypothesis, we can create a dictionary with the possible values of the "workclass" feature for each target class:

```json
{
	"no": ["Private", "Local-gov", "?", "Self-emp-not-inc", "State-gov"], 
	"yes": ["Self-emp-inc", "Federal-gov"]
}
```

In this dictionary, the "no" key represents individuals who do not earn more than 50000 dollars per year, while the "yes" key represents individuals who do earn more than 50000 dollars per year. The values in the lists correspond to the possible values of the "workclass" feature for each target class.

Note that values such as "?", "Without-pay", and "Never-worked" have been excluded from the list as they are difficult to predict or may represent cases where income is unlikely to be above 50000 dollars per year.