Based on my prior knowledge and analysis, the relationship between the feature 'age' and the task of determining whether a person earns more than 50000 dollars per year can be as follows:

- Typically, younger individuals (age < 25) are less likely to earn more than 50000 dollars per year, as they are likely to be in the early stages of their careers.
- As individuals progress in their careers, their income tends to increase. Therefore, the likelihood of earning more than 50000 dollars per year generally increases with age.
- However, there may be a point where income starts to decline for older individuals due to retirement or other factors. Therefore, there might be a range of ages where the likelihood of earning more than 50000 dollars per year decreases.

Based on these observations, the dictionary for the relationship between the feature 'age' and the target variable can be constructed as follows:

```json
{
	"no": [18, 22, 24, 28, 30],  
	"yes": [32, 35, 40, 45, 50]  
}
```

Please note that the specific age values provided in the dictionary are just examples and may not be accurate representations of the actual data. They are presented here to demonstrate the expected format of the dictionary, including five typical values for each target class.