Based on my prior knowledge, fibr_ter_07 is a feature that represents whether the patient received Fibrinolytic therapy by Celiasum 250k IU or not. To determine the relationship between this feature and the presence of chronic heart failure, I will analyze the distribution of fibr_ter_07 values for both the "no" and "yes" classes of chronic heart failure.

Here is the analysis of the relationship between feature fibr_ter_07 and the task of chronic heart failure:

For the class "no" (no chronic heart failure):
- There may be patients who did not receive Fibrinolytic therapy, so the "no" class may have the value 'no' for fibr_ter_07.

For the class "yes" (chronic heart failure):
- Patients with chronic heart failure may have received Fibrinolytic therapy, so the "yes" class may have the value 'yes' for fibr_ter_07.

Based on this analysis, let's create the dictionary:

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

In this case, the possible values for feature fibr_ter_07 in the "no" class are ['no'] and in the "yes" class is ['yes'].