```json
{
	"yes": ["yes"],
	"no": ["none"]
}
```

Based on the feature description and task, it appears that the "own_telephone" feature is a categorical variable with two possible categories: "yes" and "none". 

From a prior knowledge analysis, we can assume that individuals who own a telephone are more likely to have a credit. Therefore, the value "yes" in the "own_telephone" feature is more likely to be associated with the target class "yes" (person receives credit). Conversely, the value "none" indicates that the person does not own a telephone and is more likely to be associated with the target class "no" (person does not receive credit).

As there are only two categories for this feature, the dictionary contains a list of strings for each target class, with the possible values of "own_telephone" that are associated with that class.