Based on prior knowledge, the occupation of an individual can potentially be related to their income. Certain occupations may have higher average salaries, while others may have lower average salaries. 

To analyze the relationship between the occupation feature and the task of determining whether a person earns more than 50000 dollars per year, we can calculate the percentage of individuals in each occupation category who earn more than 50000 dollars per year. 

First, we need to gather data on the target variable and the occupation feature. Once we have the data, we can calculate the percentages and analyze the relationship.

Based on the given feature description, we have the following occupation categories: 
['Machine-op-inspct', 'Farming-fishing', 'Protective-serv', '?', 'Other-service', 'Prof-specialty', 'Craft-repair', 'Adm-clerical', 'Exec-managerial', 'Tech-support', 'Sales', 'Priv-house-serv', 'Transport-moving', 'Handlers-cleaners', 'Armed-Forces']

To generate the dictionary, let's assume we have the following analysis:

```json
{
	"no": ["Machine-op-inspct", "Farming-fishing", "Protective-serv", "?", "Handlers-cleaners"],
	"yes": ["Prof-specialty", "Exec-managerial", "Tech-support", "Sales", "Craft-repair"]
}
```

Please note that this analysis is hypothetical and the actual analysis should be performed on the dataset to obtain accurate results.