Based on prior knowledge, we can analyze the relationship between the feature "Age" and the task of determining whether a person has diabetes or not. Age is commonly known as a relevant factor in determining the likelihood of developing diabetes. Typically, as a person gets older, the risk of diabetes increases.

Based on this analysis, we can create a dictionary that includes 5 typical age values for each target class:

```json
{
  "yes": [40.5, 55.2, 62.8, 48.9, 50.3],
  "no": [28.7, 32.1, 35.9, 31.5, 39.2]
}
```

Please note that the specific age values provided here are just examples and may not reflect actual data. The values may vary depending on the dataset used for analysis.