Based on the given feature "native-country" and the task of predicting whether a person earns more than $50,000 per year, the relationship between the feature and the target can be analyzed as follows:

1. It is expected that individuals from some countries may have higher or lower earning potential compared to the others. Certain countries might have better economic conditions or job opportunities that could lead to higher incomes.

2. It is possible that individuals from the United States may have a higher likelihood of earning more than $50,000 per year compared to individuals from other countries. The United States is often associated with higher average incomes compared to many other countries.

3. Individuals from other developed countries such as Germany, Canada, and the United Kingdom might also have a higher probability of earning more than $50,000 per year due to their economic conditions.

4. On the other hand, individuals from some countries with lower average incomes, such as Peru, Guatemala, Mexico, and the Dominican Republic, may have a lower probability of earning more than $50,000 per year.

5. Some countries might have a small number of samples in the dataset, making it difficult to make specific predictions about individuals from those countries.

Based on this analysis, the dictionary can be generated as follows:

```json
{
	"no": ["?" , "Peru", "Guatemala", "Mexico", "Dominican-Republic", "Outlying-US(Guam-USVI-etc)"],
	"yes": ["United-States", "Ireland", "Germany", "Philippines", "Thailand", "Haiti", "El-Salvador", "Puerto-Rico", "Vietnam", "South", "Columbia", "Japan", "India", "Cambodia", "Poland", "Laos", "England", "Cuba", "Taiwan", "Italy", "Canada", "Portugal", "China", "Nicaragua", "Honduras", "Iran", "Scotland", "Jamaica", "Ecuador", "Yugoslavia", "Hungary", "Hong", "Greece", "Trinadad&Tobago", "France", "Holand-Netherlands"]
}
```