Based on prior knowledge, we 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 whether the patient shows chronic heart failure.

Since we don't have any specific information about the relationship between this feature and chronic heart failure, we can consider two scenarios:

1. If the presence of a First-degree AV block on ECG indicates chronic heart failure, we can assume that the feature value "yes" corresponds to the target class of chronic heart failure, and the feature value "no" corresponds to the target class of no chronic heart failure.

2. If the absence of a First-degree AV block on ECG indicates chronic heart failure, we can assume that the feature value "no" corresponds to the target class of chronic heart failure, and the feature value "yes" corresponds to the target class of no chronic heart failure.

To generate the dictionary, let's assume scenario 1:

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

This dictionary indicates that for the target class of chronic heart failure, the feature value "no" is present, and for the target class of no chronic heart failure, the feature value "yes" is present.

However, it's important to note that without further information or analysis, it is difficult to determine the exact relationship between the feature and the task.