Based on prior knowledge, the feature "relationship" can have an impact on the individual's earnings. Let's analyze the relationship between the feature and the task "Does this person earn more than 50000 dollars per year?"

To create the dictionary, we need to determine the possible values of the feature "relationship" for each target class (yes and no).

Let's start by analyzing the relationship values for the target class "no", which represents individuals who earn less than or equal to 50000 dollars per year.

For the target class "no", the possible values of the feature "relationship" are:
- Own-child
- Not-in-family
- Unmarried
- Other-relative

Now, let's analyze the relationship values for the target class "yes", which represents individuals who earn more than 50000 dollars per year.

For the target class "yes", the possible values of the feature "relationship" are:
- Husband
- Wife

Based on this analysis, we can create the dictionary:

```json
{
	"no": ["Own-child", "Not-in-family", "Unmarried", "Other-relative"],
	"yes": ["Husband", "Wife"]
}
```

Note that we only include the values that are present in the dataset for each target class. For the "no" class, we did not include the value "Not-specified" as it was not present in the dataset.