Based on prior knowledge, the relationship feature describes what this individual is relative to others. It is a categorical variable with the following possible categories: ['Own-child', 'Husband', 'Not-in-family', 'Unmarried', 'Wife', 'Other-relative'].

To analyze the relationship between this feature and the task of determining whether the person earns more than 50000 dollars per year, we can examine the potential associations between different relationship categories and income levels.

A potential hypothesis could be that individuals who are married (Husband or Wife category) might have a higher likelihood of earning more than 50000 dollars per year compared to those who are not married (Unmarried) or have other types of relationships (Own-child, Not-in-family, Other-relative). However, it is important to note that these are just hypotheses and the observed data might have different patterns.

To create the dictionary, we can examine the relationship categories for each target class (yes and no) and include the relevant values in the dictionary:

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

Based on the analysis, we include the categories that are more likely to be associated with each target class. However, it is possible that other relationship categories could also be relevant, but they were not captured in this analysis.