Based on my prior knowledge, the feature n_p_ecg_p_10 represents whether a patient had Complete LBBB (Left Bundle Branch Block) on their ECG at the time of admission to the hospital. To determine if this patient has chronic heart failure, we need to analyze the relationship between this feature and the target variable.

Here is the analysis:

- If the value of n_p_ecg_p_10 is 'no', it means that the patient did not have Complete LBBB on their ECG at the time of admission.
- If the value of n_p_ecg_p_10 is 'yes', it means that the patient did have Complete LBBB on their ECG at the time of admission.

To determine if the patient has chronic heart failure, we need to analyze the relationship between the presence of Complete LBBB and chronic heart failure. Complete LBBB can be associated with various heart conditions, including chronic heart failure. However, it is not a definitive indicator of chronic heart failure.

Based on this analysis, we can create the following dictionary:

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

As there are only two categories for the feature n_p_ecg_p_10 ('no' and 'yes'), we include both categories in the dictionary. This indicates that regardless of the value of n_p_ecg_p_10, the patient can have or not have chronic heart failure.