Based on my prior knowledge, I can 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 task of determining if the patient shows chronic heart failure.

To analyze this relationship, we can take a look at the distribution of "n_p_ecg_p_03" values for each target class (chronic heart failure status). Specifically, we will examine the possible values of "n_p_ecg_p_03" for patients with and without chronic heart failure.

Here's the analysis:

- For patients without chronic heart failure:
    - Values of "n_p_ecg_p_03": 'no', 'yes'
  
- For patients with chronic heart failure:
    - Values of "n_p_ecg_p_03": 'no', 'yes'

Based on this analysis, we can create the dictionary as follows:

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

Note: The possible values for "n_p_ecg_p_03" for both target classes are included in the dictionary, i.e., all the values 'no' and 'yes'.