```json
{
	"yes": ["yes"],  
	"no": ["none"]
}
```
Based on the given feature "own_telephone" which has two categories 'yes' and 'none', we can analyze the relationship between this feature and the task of determining whether a person receives a credit.

From the analysis, we can see that if the value of the "own_telephone" feature is "yes", then the person receives a credit (target class "yes"). On the other hand, if the value of the "own_telephone" feature is "none", then the person does not receive a credit (target class "no").

Therefore, we can create a dictionary with the listed possible values of the "own_telephone" feature for each target class as follows:

- For the target class "yes": The possible value of the "own_telephone" feature is "yes".
- For the target class "no": The possible value of the "own_telephone" feature is "none".

So, according to the analysis, the dictionary for the relationship between the "own_telephone" feature and the task of whether a person receives a credit is as mentioned above.