Based on prior knowledge, the workclass feature can give some insight into whether a person earns more than $50,000 per year or not. Here is an analysis of the relationship between the workclass feature and the target variable:

1. Private: This category represents individuals working in the private sector. It is common for people in this category to earn both below and above $50,000 per year. Therefore, this category could have examples for both the "yes" and "no" target classes.

2. Local-gov: This category represents individuals working for local government. People in this category may have various income levels, so it is possible to find examples for both the "yes" and "no" target classes.

3. ?: This category represents missing or unknown workclass values. Since the workclass is unknown, it is hard to predict whether a person earns more than $50,000 per year. Therefore, it is not necessary to include this category in the dictionary.

4. Self-emp-not-inc: This category represents self-employed individuals who are not incorporated. Self-employment can have different income levels, so it is possible to find examples for both the "yes" and "no" target classes.

5. Federal-gov: This category represents individuals working for the federal government. People working in the federal government can have various income levels, so it is possible to find examples for both the "yes" and "no" target classes.

6. State-gov: This category represents individuals working for state government. People working in the state government can have various income levels, so it is possible to find examples for both the "yes" and "no" target classes.

7. Self-emp-inc: This category represents self-employed individuals who are incorporated. Self-employment can have different income levels, so it is possible to find examples for both the "yes" and "no" target classes.

8. Without-pay: This category represents individuals without pay, such as unpaid interns or volunteers. It is unlikely that individuals in this category would earn more than $50,000 per year. Therefore, this category may have examples for the "no" target class.

9. Never-worked: This category represents individuals who have never worked. It is unlikely that individuals in this category would earn more than $50,000 per year. Therefore, this category may have examples for the "no" target class.

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

```json
{
	"no": ["Without-pay", "Never-worked"],
	"yes": ["Private", "Local-gov", "Self-emp-not-inc", "Federal-gov", "State-gov", "Self-emp-inc"]
}
```

Please note that this analysis is based on statistical inferences and assumptions. The actual relationship between the workclass feature and the target variable can vary depending on the specific dataset and context.