Based on my prior knowledge, the occupation of an individual can be a good indicator of their income level. Certain occupations tend to have higher salaries compared to others. However, it is important to note that there can be individuals with the same occupation but different income levels, so this feature alone may not be sufficient to predict whether a person earns more than $50,000 per year.

Here is the dictionary representing the relationship between the "occupation" feature and the target variable:

```json
{
	"no": ["Machine-op-inspct", "Farming-fishing", "Protective-serv", "?", "Other-service", "Craft-repair", "Adm-clerical", "Handlers-cleaners", "Priv-house-serv", "Armed-Forces"],
	"yes": ["Prof-specialty", "Exec-managerial", "Tech-support", "Sales", "Transport-moving"]
}
```

The possible values of the "occupation" feature for the "no" class (individuals earning less than or equal to $50,000 per year) include: "Machine-op-inspct", "Farming-fishing", "Protective-serv", "?", "Other-service", "Craft-repair", "Adm-clerical", "Handlers-cleaners", "Priv-house-serv", and "Armed-Forces".

The possible values of the "occupation" feature for the "yes" class (individuals earning more than $50,000 per year) include: "Prof-specialty", "Exec-managerial", "Tech-support", "Sales", and "Transport-moving".

Note that the value "?" is included in the "no" class since it is hard to predict the income level for individuals with unknown occupations.