From the given feature "occupation" and the task "Does this person earn more than 50000 dollars per year?", we can analyze the relationship between the feature and the target variable based on our prior knowledge.

Certain occupations are typically associated with higher income levels, such as "Exec-managerial" and "Prof-specialty," while others may be associated with lower income levels, such as "Other-service" and "Priv-house-serv." It is reasonable to assume that individuals in the "Armed-Forces" occupation would earn less than 50000 dollars per year. However, it is difficult to predict the income level for certain occupations like "Machine-op-inspct," "Farming-fishing," "Protective-serv," and "Transport-moving" without further information.

Based on this analysis, the following dictionary can be generated:

```json
{
    "no": ["Other-service", "Priv-house-serv", "Armed-Forces"], 
    "yes": ["Exec-managerial", "Prof-specialty"]
}
```