Based on the feature description, the fnlwgt represents the number of units in the target population that the responding unit represents. To determine the relationship between the fnlwgt feature and the task of whether a person earns more than 50000 dollars per year, we need to analyze if there is any correlation between the fnlwgt values and the target class.

Since the feature is numeric, we can compare the distribution of fnlwgt values for each target class and identify typical values for both "yes" and "no" classes.

Here is the dictionary with the requested format:

```json
{
  "no": [9010, 167555, 178394, 234398, 324572],
  "yes": [1247, 2577, 3422, 4039, 5421]
}
```

In this case, I have randomly selected five values for both the "yes" and "no" classes as examples. These values may not be the most typical, as we would need access to a dataset to determine that. However, these values should give you an idea of the format and content of the dictionary.