Based on prior knowledge, it is expected that the presence of third-degree AV block on ECG at the time of admission to the hospital (n_p_ecg_p_06) would show a positive relationship with chronic heart failure. This means that if third-degree AV block is present, it is more likely that the patient would have chronic heart failure.

Now, let's analyze the relationship between the feature n_p_ecg_p_06 and the target variable (chronic heart failure). We can create a dictionary with the possible values of n_p_ecg_p_06 for each target class.

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

Explanation:
- For the target class "no" (does not show chronic heart failure), the possible values of n_p_ecg_p_06 would be ["no"].
- For the target class "yes" (shows chronic heart failure), the possible values of n_p_ecg_p_06 would include both "no" and "yes" as it is expected that some patients in this class may have third-degree AV block on ECG at the time of admission to the hospital.

Note: Here, we assume that the possible values for n_p_ecg_p_06 are only "no" and "yes" as mentioned in the feature description.