Based on prior knowledge, we can analyze the relationship between the feature "n_p_ecg_p_09" and the target variable "chronic heart failure" to determine if the patient shows chronic heart failure depending on the value of the feature.

Here are the potential relationships:
- If the value of "n_p_ecg_p_09" is "no", it indicates that the patient does not have an incomplete LBBB on ECG at the time of admission to the hospital.
- If the value of "n_p_ecg_p_09" is "yes", it indicates that the patient has an incomplete LBBB on ECG at the time of admission to the hospital.

To create the dictionary, we need to gather the possible values of "n_p_ecg_p_09" for each target class:

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

Since "n_p_ecg_p_09" is a binary categorical variable, we only have the values "no" and "yes" in the dictionary.