Based on prior knowledge, the workclass feature could be related to the person's income. Here is an analysis of the relationship between workclass and the target variable of whether the person earns more than 50000 dollars per year:

- Private: There is a possibility that both high and low earners could be working in private companies, so this category may not provide a strong indication of the target variable.
- Local-gov: Government jobs in the local sector might have a range of salaries, so this category may not be a strong predictor.
- ?: The question mark represents missing values, which can't be used to determine the relationship.
- Self-emp-not-inc: Self-employed individuals who are not incorporated might have varying income levels, so this category may not strongly predict the target variable.
- Federal-gov: Federal government jobs may have more standardized salary structures, providing a better indication of the target variable.
- State-gov: Similar to federal government jobs, state government jobs may have more standardized salary structures, providing a better indication of the target variable.
- Self-emp-inc: Self-employed individuals who are incorporated may have varying income levels, so this category may not be a strong predictor.
- Without-pay: Individuals without pay may not be in the taxable income bracket, so they are unlikely to earn more than 50000 dollars per year. This category could be a strong indicator of the target variable.
- Never-worked: Individuals who have never worked are unlikely to earn more than 50000 dollars per year. This category could be a strong indicator of the target variable.

Based on this analysis, the dictionary representing the relationship between workclass and the target variable is as follows:

```json
{
	"no": ["Without-pay", "Never-worked"],
	"yes": ["Federal-gov", "State-gov"]
}
```