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

Based on the given feature description and task, it appears that the feature "n_p_ecg_p_10" represents the presence or absence of complete left bundle branch block (LBBB) on the electrocardiogram (ECG) at the time of admission to the hospital. 

Since the task is to determine whether the patient shows chronic heart failure or not, it is important to analyze how the presence or absence of LBBB on the ECG relates to chronic heart failure. 

To perform this analysis, we can consider the following possibilities:

1. If the patient has complete LBBB on the ECG at the time of admission to the hospital (n_p_ecg_p_10 = "yes"), it is possible that they may have a higher likelihood of showing chronic heart failure. In this case, we can include "yes" as a possible value for the feature "n_p_ecg_p_10" when the target class is "yes".

2. If the patient does not have complete LBBB on the ECG at the time of admission to the hospital (n_p_ecg_p_10 = "no"), it is possible that they may have a lower likelihood of showing chronic heart failure. In this case, we can include "no" as a possible value for the feature "n_p_ecg_p_10" when the target class is "no".

Please note that we do not have any information on other possible values for the feature "n_p_ecg_p_10" or how they may relate to chronic heart failure. Therefore, the dictionary includes only the values "yes" and "no" for the feature "n_p_ecg_p_10".