Based on my prior knowledge, the presence of complete RBBB (Right Bundle Branch Block) on an ECG (Electrocardiogram) can be an indication of certain heart conditions, including chronic heart failure. Therefore, it is likely that the feature "n_p_ecg_p_12" may show a relationship with the presence of chronic heart failure.

To analyze the relationship between the feature "n_p_ecg_p_12" and the occurrence of chronic heart failure, we need data that includes both the feature values and the target variable (presence or absence of chronic heart failure). Without this data, it is not possible to determine the specific relationship between the feature and the target.

However, assuming we have the data, we can analyze the relationship by examining the instances where chronic heart failure is present and the corresponding values of the feature "n_p_ecg_p_12".

Here is an example of the requested dictionary:

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

Please note that the specific values in the dictionary are purely hypothetical and would depend on the actual data. This dictionary represents possible values for the feature "n_p_ecg_p_12" for the target classes of "no" (indicating absence of chronic heart failure) and "yes" (indicating presence of chronic heart failure). If there are other categorical values for the feature that are hard to predict or not relevant to the target classes, they can be excluded from the dictionary.