From prior knowledge, we know that the "relationship" feature describes what an individual is relative to others. This feature is a categorical variable with multiple categories:

1. Own-child: This category indicates that the individual is a child of someone else. It is possible that individuals who are still dependent on their parents might earn less than $50,000 per year. Therefore, it is likely that there will be a significant number of individuals in this category who earn less than $50,000 per year.

2. Husband/Wife: These categories indicate that the individual is married and likely to have a spouse. Being married might indicate stability and possibly higher earning potential. Therefore, it is possible that there will be a considerable number of individuals in these categories who earn more than $50,000 per year.

3. Not-in-family: This category refers to individuals who are not closely related to anyone in the household. These individuals might be living alone or with unrelated roommates. It is difficult to predict the income level for this category, as it can vary greatly. Some individuals may earn more than $50,000 per year, while others may earn less.

4. Unmarried: This category represents individuals who are not married but might have a significant other or be in a committed relationship. Similar to the "Not-in-family" category, it is challenging to predict the income level for this group accurately.

5. Other-relative: This category includes individuals who are related to someone in a different way than the other stated categories. It is difficult to make any definite predictions about the income level for this category.

Based on this analysis, we can construct the following dictionary:

```json
{
    "no": ["Own-child"],
    "yes": ["Husband", "Wife"]
}
```

The 'no' dictionary entry includes the "Own-child" category, as individuals who are children of someone else may earn less than $50,000 per year.

The 'yes' dictionary entry includes the "Husband" and "Wife" categories, as being married might indicate a higher likelihood of earning more than $50,000 per year.

Please note that other categories which have ambiguous relationships with the target variable are not included in the dictionary, as they are hard to predict accurately.