Based on prior knowledge and common sense, we can analyze the relationship between the feature "property_magnitude" and the target variable "Does this person receive a credit?". 

Looking at the possible values of the feature "property_magnitude" - real estate, life insurance, no known property, and car, we can make some assumptions about their relationship with the target variable.

Since real estate and life insurance are typically considered valuable assets, it is reasonable to assume that individuals with these property magnitudes are more likely to receive credit. On the other hand, individuals with no known property or only a car may have a higher risk of defaulting on credit, making it less likely for them to receive credit.

Based on this analysis, we can create the following dictionary:

```json
{
	"yes": ["real estate", "life insurance"],
	"no": ["no known property", "car"]
}
```

This dictionary represents the possible values of the feature "property_magnitude" for each target class.