Based on prior knowledge, let's analyze the relationship between the feature "n_p_ecg_p_03" (First-degree AV block on ECG at the time of admission to the hospital) and the presence of chronic heart failure.

Given that "n_p_ecg_p_03" is a categorical variable with categories 'no' and 'yes', we can analyze the relationship by comparing the distribution of these categories for patients with and without chronic heart failure.

Here's a possible analysis:

- For patients without chronic heart failure:
  - If the value of "n_p_ecg_p_03" is 'no', it means there is no First-degree AV block on ECG at the time of admission to the hospital.
  - We can include this value in the dictionary for the target class 'no'.

- For patients with chronic heart failure:
  - If the value of "n_p_ecg_p_03" is 'yes', it means there is a First-degree AV block on ECG at the time of admission to the hospital.
  - We can include this value in the dictionary for the target class 'yes'.

Based on this analysis, the dictionary would look like this:

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

This indicates that for patients without chronic heart failure, there is only one possible value for "n_p_ecg_p_03" ('no'), and for patients with chronic heart failure, there is only one possible value for "n_p_ecg_p_03" ('yes').