Based on prior knowledge, the feature n_p_ecg_p_07 represents whether the patient has left bundle branch block (LBBB) on their electrocardiogram (ECG) at the time of admission to the hospital. 
To analyze its relationship with the presence of chronic heart failure, we can examine the values of n_p_ecg_p_07 for each target class.

Here is the analysis:

- If n_p_ecg_p_07 is "no" (indicating no LBBB on ECG), it is possible that the patient does not have chronic heart failure.
- If n_p_ecg_p_07 is "yes" (indicating LBBB on anterior branch of ECG), it is possible that the patient has chronic heart failure.

Now let's create the dictionary:

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

In this case, since the feature n_p_ecg_p_07 has only two possible categories ('no' and 'yes'), we can include both in the dictionary. The values are presented as strings in lists for each target class.