Based on prior knowledge, it is possible that clients with a personal loan may be less likely to subscribe to a term deposit. To analyze the relationship between the feature "has personal loan?" and the task of whether the client subscribes to a term deposit, we can group the clients based on their target class and examine the distribution of loan values for each group.

Here is the analysis:

For target class "no" (client does not subscribe to a term deposit):
- Possible values of feature "loan": ['no', 'yes']

For target class "yes" (client subscribes to a term deposit):
- Possible values of feature "loan": ['no', 'yes']

Based on this analysis, we can create the dictionary as follows:

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

Note: The possible values of the loan feature for both target classes are the same in this case, which indicates that there is no clear distinction between the loan feature and the task of subscribing to a term deposit.