Based on my expertise, the feature "n_p_ecg_p_06" represents the presence or absence of Third-degree AV block on ECG at the time of admission to the hospital. To analyze the relationship between this feature and the task of detecting chronic heart failure, we need to examine how the feature values indicate the presence or absence of chronic heart failure.

Considering the feature values, there are two categories: "no" and "yes". To determine whether these values indicate chronic heart failure, we need additional information or domain knowledge. Without such information, it is difficult to predict how these values are related to chronic heart failure. Therefore, for the purposes of this task, we cannot generate a definite dictionary with specific details.

However, for the sake of completeness, we can assume that some values may indicate the presence or absence of chronic heart failure, while others may be inconclusive. In this case, we can create a dictionary with two lists, one for each target class:

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

Please note that these lists only contain the possible values of the feature for each target class. Since we do not have enough information to determine the relationship between the feature and the target, we cannot provide a comprehensive dictionary in this case.