Based on my prior knowledge, the feature "n_r_ecg_p_03" represents the presence or absence of ventricular contractions on the 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 need to examine the distribution of "n_r_ecg_p_03" values for each target class.

To create the dictionary, I will first categorize the "n_r_ecg_p_03" feature values for each target class, and then list the possible values for each class.

Here's the dictionary for the given scenario:

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

Since the "n_r_ecg_p_03" feature is categorical and has only two categories ('no' and 'yes'), the values for each target class are straightforward. For the "no" class, the only possible value is "no", and for the "yes" class, the only possible value is "yes".