Based on prior knowledge, the feature "n_r_ecg_p_03" represents ventricular contractions on an electrocardiogram (ECG) at the time of admission to the hospital. 

To analyze the relationship between this feature and the presence of chronic heart failure, we can examine the distribution of "n_r_ecg_p_03" values for each target class (yes or no for chronic heart failure). 

Let's assume that the dataset contains the following records:

| n_r_ecg_p_03  | Chronic Heart Failure |
|--------------|-----------------------|
| no           | yes                   |
| yes          | no                    |
| no           | no                    |
| no           | no                    |
| yes          | yes                   |
| no           | no                    |
| yes          | no                    |

Based on this data, we can generate the following dictionary:

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

Since the feature "n_r_ecg_p_03" only has two categories, "no" and "yes", we only include those values in the dictionary. Other values that might exist but are not included in this dataset do not need to be considered.