To analyze the relationship between the feature "n_r_ecg_p_05" and the task of determining if the patient shows chronic heart failure, we need to consider the distribution of the feature values for each target class.

Based on the description, the feature "n_r_ecg_p_05" represents the presence or absence of paroxysms of atrial fibrillation on the electrocardiogram (ECG) at the time of admission to the hospital. It is a categorical variable with two possible categories: 'no' and 'yes'.

To create the dictionary, we need to identify the possible values of "n_r_ecg_p_05" for each target class.

Here is the dictionary for the given feature and task:

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

Explanation:
- For the target class "no" (patients without chronic heart failure), the only possible value for "n_r_ecg_p_05" is 'no'.
- For the target class "yes" (patients with chronic heart failure), the possible values for "n_r_ecg_p_05" are both 'no' and 'yes'.

Note that the "n_r_ecg_p_05" feature only has a single value ('no') for patients without chronic heart failure. However, there are two possible values ('no' and 'yes') for patients with chronic heart failure.