Based on prior knowledge, we can analyze the relationship between the age of an individual and their earnings. Usually, as individuals gain more experience and progress in their careers, their earnings tend to increase. Therefore, it is reasonable to assume that older people are more likely to earn above $50,000 per year compared to younger individuals. 

Here is the dictionary generated based on this analysis:

```json
{
  "no": [17, 18, 19, 20, 21],
  "yes": [40, 45, 50, 55, 60]
}
```

In this dictionary, we have provided five typical age values for each target class. The "no" list includes ages ranging from 17 to 21, while the "yes" list includes ages ranging from 40 to 60. These values are just examples and may vary depending on the specific dataset being analyzed.