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

To do this, I would compare the distribution of loan values for the two target classes: "no" and "yes".

Here is the dictionary with the requested format:

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

In this case, for the target class "no", the possible values of the feature loan are ['no'], indicating that clients without a personal loan are less likely to subscribe to a term deposit. However, for the target class "yes", the possible values of the feature loan are ['no', 'yes'], suggesting that both clients with and without a personal loan can potentially subscribe to a term deposit.