Based on prior knowledge, we can analyze the relationship between the "educational-num" feature and the task of earning more than 50000 dollars per year.

In general, individuals with higher levels of education tend to have higher incomes. Therefore, it is expected that as the "educational-num" value increases, the likelihood of earning more than 50000 dollars per year also increases.

To create the requested dictionary, we need to identify typical values of "educational-num" for each target class.

For individuals earning less than or equal to 50000 dollars per year ('no'), typical values of "educational-num" could be:
- 1 (for "Preschool" or "Nursery school")
- 8 (for "12th grade, no diploma")
- 9 (for "High school graduate")
- 10 (for "Some college, no degree")
- 11 (for "Associate's degree")

For individuals earning more than 50000 dollars per year ('yes'), typical values of "educational-num" could be:
- 13 (for "Bachelor's degree")
- 14 (for "Master's degree")
- 15 (for "Professional school degree")
- 16 (for "Doctorate degree")
- 7 (for "5th or 6th grade")

Based on this analysis, we can generate the dictionary:

```json
{
	"no": [1, 8, 9, 10, 11],
	"yes": [13, 14, 15, 16, 7]
}
```