Based on prior knowledge, the workclass feature can provide information about a person's employment status, which can be an indicator of their income level. To analyze the relationship between workclass and the task of whether a person earns more than 50000 dollars per year, we can examine the distribution of workclass values for each target class.

To create the dictionary, we will analyze the dataset and identify the workclass values that are associated with each target class based on the given task.

Here is the analysis and corresponding dictionary:

```json
{
    "no": ["?", "Without-pay", "Never-worked"],  
    "yes": ["Private", "Local-gov", "Federal-gov", "State-gov", "Self-emp-inc", "Self-emp-not-inc"]
}
```

In this analysis, we have identified the workclass values that are associated with each target class. The "no" class is associated with the values ['?', 'Without-pay', 'Never-worked'], while the "yes" class is associated with the values ['Private', 'Local-gov', 'Federal-gov', 'State-gov', 'Self-emp-inc', 'Self-emp-not-inc'].

Please note that the values 'Private', 'Local-gov', 'Federal-gov', 'State-gov', 'Self-emp-inc', and 'Self-emp-not-inc' are potential indicators of earning more than 50000 dollars per year, and the values '?', 'Without-pay', and 'Never-worked' are potential indicators of earning less than or equal to 50000 dollars per year.

