Based on prior knowledge, we can analyze the relationship between the feature "fibr_ter_06" and the target variable "chronic heart failure". 

From the feature description, "fibr_ter_06" represents the fibrinolytic therapy by Celiasum 500k IU, which is a categorical variable with two categories: 'no' and 'yes'.

To determine if the patient has chronic heart failure, we need to analyze the relationship between "fibr_ter_06" and the presence of chronic heart failure.

To create the dictionary, we'll need to look at the possible values of "fibr_ter_06" for both target classes - "no" and "yes".

Based on this analysis, the dictionary can be constructed as follows:

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

Since "fibr_ter_06" is a categorical variable, we can see that the possible values for both the "no" and "yes" target classes are only the categories 'no' and 'yes', respectively. Therefore, the lists consist of these single values.

Please note that if there are additional possible values for "fibr_ter_06" that are hard to predict, they can be excluded from the dictionary. However, make sure that the list for each target class is not empty.