Based on prior knowledge, it is generally expected that individuals with higher levels of education tend to earn higher incomes. With this in mind, we can analyze the relationship between the education feature and the task of whether a person earns more than $50,000 per year.

To create the dictionary, we need to identify the possible values of the education feature for each target class ('yes' or 'no'). 

Here is the generated dictionary:

```json
{
	"no": ["11th", "HS-grad", "10th", "7th-8th", "9th", "12th", "1st-4th", "Preschool"],
	"yes": ["Assoc-acdm", "Some-college", "Prof-school", "Bachelors", "Masters", "Doctorate", "5th-6th", "Assoc-voc"]
}
```

In this dictionary, we include the education values that are more commonly associated with each target class. This allows us to identify trends where individuals with particular levels of education are more likely to have an income above or below $50,000 per year.