Based on prior knowledge, we need to analyze the relationship between the feature "n_p_ecg_p_04" (Type 1 Second-degree AV block on ECG at the time of admission to hospital) and the task of determining if the patient shows chronic heart failure.

To conduct the analysis, we can look at the distribution of the feature based on the target variable. By examining the values of "n_p_ecg_p_04" for patients with and without chronic heart failure, we can determine if there is any relationship between the feature and the target.

Let's assume the target variable is denoted as "chronic_heart_failure".

We can analyze the relationship as follows:

1. For patients without chronic heart failure:
   - "n_p_ecg_p_04" values may include: ['no', 'yes']

2. For patients with chronic heart failure:
   - "n_p_ecg_p_04" values may include: ['no', 'yes']

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

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

This dictionary indicates that for both cases - patients without chronic heart failure and patients with chronic heart failure, the possible values of "n_p_ecg_p_04" are "no" and "yes".