Based on prior knowledge, it is likely that gender has some relationship with earning more than 50000 dollars per year. However, it is important to note that gender alone is not a direct indicator of income and there are multiple factors that contribute to a person's income. Nevertheless, we can analyze the relationship between gender and the task at hand.

To analyze this relationship, we can examine the dataset and identify the possible values of the feature gender for each target class.

Here is the dictionary reflecting the possible values of gender for each target class:

```json
{
	"no": ["Male", "Female"],
	"yes": ["Male", "Female"]
}
```

Since the feature gender has only two categories, "Male" and "Female", it is not necessary to exclude any values from the dictionary as requested. However, it is important to note that these results are based on the assumption that the dataset includes all possible values for gender.