Based on prior knowledge, we can assume that the feature "fibr_ter_03" represents whether the patient received fibrinolytic therapy by Celiasum 3m IU. To determine if the patient has chronic heart failure, we need to analyze the relationship between this feature and the target variable.

To perform this analysis, we will examine the values of the feature "fibr_ter_03" for each target class (yes and no) and identify any patterns or trends. Based on the description provided, we can create a dictionary with the requested format.

Here is the dictionary:

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

Since the feature "fibr_ter_03" is categorical with only two possible values (no and yes), we can directly assign the values to their respective target classes. In this case, the value "no" corresponds to the target class "no" and the value "yes" corresponds to the target class "yes".

Note: It is important to analyze features in the context of the specific data set and task at hand. This analysis assumes that the feature "fibr_ter_03" is the only relevant feature for determining the presence of chronic heart failure.