```json
{
    "no": ["no"],  
    "yes": ["yes"]
}
```
Based on prior knowledge, the feature "nr_11" represents whether the patient has observed arrhythmia in the anamnesis. To determine whether the patient shows chronic heart failure, we need to analyze the relationship between this feature and the target variable.

Since the feature is categorical with only two categories, "no" and "yes", we can directly associate these categories with the target classes of "no" and "yes".

From the available information, it is clear that if the patient has observed arrhythmia in the anamnesis, it is likely to be associated with the presence of chronic heart failure ("yes"). On the other hand, if the patient has not observed arrhythmia in the anamnesis, it is likely to be associated with the absence of chronic heart failure ("no").

Hence, the dictionary representing the relationship between the feature "nr_11" and the target classes is as follows:

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

This indicates that if the value of "nr_11" is "no", it is associated with the target class "no" (absence of chronic heart failure). Similarly, if the value of "nr_11" is "yes", it is associated with the target class "yes" (presence of chronic heart failure).