Based on prior knowledge, we can analyze the relationship between the feature "n_p_ecg_p_06" and the presence of chronic heart failure in myocardial infarction patients.

If a patient has a third-degree AV block on ECG at the time of admission to the hospital (n_p_ecg_p_06 = 'yes'), it is possible that they are more likely to have chronic heart failure as a complication of myocardial infarction. On the other hand, if the patient does not have a third-degree AV block on ECG (n_p_ecg_p_06 = 'no'), it suggests that they may be less likely to develop chronic heart failure.

To summarize the relationship between the feature and the target class, we can create a dictionary with the possible values of the feature 'n_p_ecg_p_06' for each target class 'no' and 'yes'. Here's the dictionary:

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

Since 'n_p_ecg_p_06' is a categorical variable with only two possible categories ['no', 'yes'], we include these values in the respective target class lists.