Based on prior knowledge of myocardial infarction complications and chronic heart failure, we can analyze the relationship between the feature "nr_03" (Paroxysms of atrial fibrillation in the anamnesis) and the task of determining if the patient has chronic heart failure.

Possible scenarios:

1. If the value of "nr_03" is 'no', it indicates that the patient does not have a history of paroxysms of atrial fibrillation in the anamnesis. In this case, it is unlikely that the patient has chronic heart failure.


2. If the value of "nr_03" is 'yes', it suggests that the patient has a history of paroxysms of atrial fibrillation in the anamnesis. This increases the likelihood of chronic heart failure, as atrial fibrillation can be a contributing factor.

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

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

Note: Since the feature "nr_03" is a categorical variable with categories 'no' and 'yes', we can only consider these two possible values in the dictionary.