Based on prior knowledge, we can analyze how the age feature relates to the target variable of earning more than 50000 dollars per year.

Usually, as individuals gain more experience and progress in their careers, their income tends to increase. Therefore, we can expect that age might be positively correlated with earning more than 50000 dollars per year.

To create the dictionary, we will use the following age ranges:

- Ages 17 to 25: considered as young adults who are typically still studying or starting their careers. They might have lower income levels, so it's likely they earn less than 50000 dollars per year.
- Ages 26 to 35: individuals in this age range may have gained work experience and may have started to earn higher incomes. Therefore, some may earn more than 50000 dollars per year.
- Ages 36 to 45: individuals in this range are typically in their prime working years and may have accumulated enough experience to earn higher salaries. Hence, many from this age group might earn more than 50000 dollars per year.
- Ages 46 to 55: individuals in this range may still hold senior positions in their careers, resulting in higher salaries. It is reasonable to expect that many of them earn more than 50000 dollars per year.
- Ages 56 and above: individuals in this age group are often close to retirement or may have already retired. Their income levels may vary, but it is likely that fewer people in this category earn more than 50000 dollars per year.

Using this analysis, we can generate the dictionary:

```json
{
	"no": [17, 18, 19, 20, 21],
	"yes": [36, 37, 41, 47, 50]
}
```

Please note that the specific values provided here are only examples to demonstrate the format of the dictionary. The actual values will depend on the data you have and the patterns observed in the relationship between age and the target variable.