Based on prior knowledge and analysis, the feature "Time, months since first donation" could potentially have a relationship with the target variable "Did the person donate blood?". Let's assume that a person who donated blood in the past is more likely to donate again in the future.

Here is a dictionary that includes five typical Time values for each target class:

```json
{
	"yes": [2.0, 4.0, 6.0, 8.0, 10.0],
	"no": [1.0, 3.0, 5.0, 7.0, 9.0]
}
```

In this dictionary, the "yes" key represents the target class for individuals who have donated blood, while the "no" key represents the target class for individuals who have not donated blood. The corresponding list of float values under each key represents the possible values of the feature "Time" for that target class.

These values are just suppositions based on general knowledge and understanding of blood donation patterns. Actual analysis and exploration of the data would be necessary to determine the true relationship between the feature and the target variable.