Based on prior knowledge, we can analyze the relationship between the feature 'n_r_ecg_p_08' and the task of determining whether the patient with myocardial infarction complications shows chronic heart failure.

Since 'n_r_ecg_p_08' represents the presence of paroxysms of supraventricular tachycardia on ECG at the time of admission to the hospital, we can assume that if the value is 'yes', it might indicate a higher likelihood of chronic heart failure. On the other hand, if the value is 'no', it might suggest a lower likelihood of chronic heart failure.

Based on this analysis, we can create a dictionary as follows:

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

This dictionary indicates that for the target class 'no' (i.e., no chronic heart failure), the possible value(s) for the feature 'n_r_ecg_p_08' is 'no'. For the target class 'yes' (i.e., chronic heart failure), the possible value(s) for the feature 'n_r_ecg_p_08' is 'yes'.

Please note that as per the given feature description, there are only two possible categories for 'n_r_ecg_p_08': 'no' and 'yes'. Therefore, the lists for each target class have only one value.