Based on prior knowledge and judgement, I will analyze how the feature "age" relates to the task of determining whether a person earns more than 50000 dollars per year. Typically, it can be assumed that people who are older and more experienced in the workforce tend to earn higher incomes. However, it is important to note that there can be exceptions and individual circumstances that influence income levels.

Here is the analysis of the relationship between "age" and the task:

- For individuals aged below 16, they are not typically employed adults and therefore their income is likely to be below $50000 per year. So, the feature values below 16 can be classified as 'no' for the target class.

- As age increases from 16 to around the mid-20s, individuals tend to still be in the early stages of their careers and are more likely to have lower incomes. However, there could be some exceptions where they earn more than $50000 per year due to specialized skills or advanced education. So, there can be instances of both 'yes' and 'no' target classes in this age range.

- From around the mid-20s to the early 60s, individuals generally have a higher possibility of earning more than $50000 per year. This age range can be considered as more likely to have the 'yes' target class.

- For individuals aged above the early 60s, some may have retired from full-time employment or have reduced their work hours, which could result in lower incomes. Therefore, there might be instances of the 'no' target class for this age range as well.

Based on this analysis, let's create the dictionary with specific details:

```json
{
	"no": [16, 17, 18, 19, 20],  
	"yes": [30, 35, 40, 45, 50]
}
```

In this dictionary:
- "no" represents the target class where the individual earns less than or equal to $50000 per year.
- "yes" represents the target class where the individual earns more than $50000 per year.
- The listed values represent typical ages, selected based on the earlier analysis for each target class.