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

Based on the feature description, n_r_ecg_p_03 represents ventricular contractions on the ECG at the time of admission to the hospital. It is a categorical variable with two possible categories: "no" and "yes". 

To analyze the relationship between this feature and the task of determining if the patient shows chronic heart failure, we can infer the following:

- If the value of n_r_ecg_p_03 is "no", it means there were no ventricular contractions on the ECG at the time of admission. This suggests that the patient did not show chronic heart failure.
- If the value of n_r_ecg_p_03 is "yes", it means there were ventricular contractions on the ECG at the time of admission. This suggests a possibility of chronic heart failure in the patient.

Since the feature n_r_ecg_p_03 has only two distinct categories - "no" and "yes", we can create a dictionary where the key is the target class ("no" or "yes") and the value is a list containing the possible values of n_r_ecg_p_03 for that target class.

In this case, the dictionary would be as follows:

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

Note that for simplicity, we are assuming that the target class values are mutually exclusive and exhaustive, meaning there are no other possible values for the target variable.