Based on prior knowledge, we can analyze the relationship between the "duration" feature and the task of whether the client subscribes to a term deposit. 

The "duration" feature represents the last contact duration in seconds, and it could potentially provide valuable insights into the client's decision-making process. 

To analyze the relationship, we can consider the following approach:
1. Group the data by the target variable, i.e., whether the client subscribed to a term deposit (yes or no).
2. Calculate the average durations for each target class.
3. Identify the range and distribution of duration values for both target classes.
4. Select 5 typical duration values for each target class. 

Based on this analysis, we can create a dictionary with the requested format. Here's the generated markdown code snippet:

```json
{
	"no": [129.0, 122.0, 144.0, 156.0, 151.0],
	"yes": [234.0, 367.0, 356.0, 429.0, 512.0]
}
```

Please note that the durations provided are example values and should be replaced with actual values obtained from the analysis of the dataset.