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

To analyze this relationship, we can look at the distribution of the "loan" feature for each target class. Specifically, we can calculate the possible values of the feature "loan" for each target class.

Here is the resulting dictionary:

```json
{
    "no": ["no"],
    "yes": ["no", "yes"]
}
```

In this case, for the target class "no" (client does not subscribe to a term deposit), the only possible value for the "loan" feature is "no". However, for the target class "yes" (client subscribes to a term deposit), both "no" and "yes" are possible values for the "loan" feature.