Based on prior knowledge, it is difficult to determine the relationship between the feature "n_p_ecg_p_06" (Third-degree AV block on ECG at the time of admission to hospital) and the presence of chronic heart failure without further information. However, we can proceed with the analysis by examining the values of the feature for each target class.

To generate the required dictionary, we need to analyze the feature values for the two target classes, "no" and "yes".

Let's analyze the relationship between the feature "n_p_ecg_p_06" and the presence of chronic heart failure:

- For target class "no", we need to gather the possible values of the feature "n_p_ecg_p_06" where chronic heart failure is not present.
- For target class "yes", we need to gather the possible values of the feature "n_p_ecg_p_06" where chronic heart failure is present.

Based on this analysis, we can create the dictionary:

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

Please note that the dictionary in this case includes all the possible values of the feature for the respective target classes. However, in this scenario, if there are other values for the feature that are hard to predict or are not relevant in determining the presence of chronic heart failure, they do not need to be included in the dictionary.