Based on prior knowledge, we need to analyze the relationship between the feature "IM_PG_P" (Presence of a right ventricular myocardial infarction) and the task of determining if the patient has chronic heart failure or not.

To do this, we can examine the distribution of the feature with respect to the target variable (chronic heart failure). We will look at the possible values of the "IM_PG_P" feature for each target class and see if there are any patterns or differences.

Here's the analysis of the relationship between the feature and target:

- For target class "no" (no chronic heart failure):
  - IM_PG_P possible values: ['no', 'yes']

- For target class "yes" (chronic heart failure):
  - IM_PG_P possible values: ['no']

Based on this analysis, let's create the dictionary:

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

Please note that the "yes" class has only one possible value for the "IM_PG_P" feature, which is "no". However, there are two possible values for the "IM_PG_P" feature in the "no" class, i.e., "no" and "yes".