Based on prior knowledge, I can analyze the relationship between the feature 'duration' and the task of whether the client subscribes to a term deposit or not.

Typically, I would expect that a longer duration of the last contact with the client would indicate a higher likelihood of the client subscribing to a term deposit. However, it is important to note that this relationship may not hold true in all cases and may also depend on other factors. 

To create the dictionary with the requested format, I will analyze the relationship between the 'duration' feature and the target variable 'subscription'. I will then provide lists of typical duration values for each target class ('no' and 'yes').

```json
{
    "no": [200.0, 250.0, 300.0, 350.0, 400.0],
    "yes": [500.0, 550.0, 600.0, 650.0, 700.0]
}
```

These lists include 5 typical duration values for each target class, representing the potential range of durations for clients who did not subscribe to a term deposit ('no') and those who did subscribe ('yes'). Please note that the values provided here are just examples and might not be accurate for a specific dataset.