Based on prior knowledge, we can analyze the relationship between the feature "GT_POST" and the presence of chronic heart failure in the myocardial infarction complications data. 

To do this, we can look at the distribution of "GT_POST" values for patients with and without chronic heart failure. We will check if there is any significant correlation between the two variables.

Once we have analyzed the relationship, we can create a dictionary with the possible values of "GT_POST" for each target class.

Let's proceed with the analysis and create the dictionary:

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

Based on the prior knowledge, we know that the possible values for "GT_POST" are either "no" or "yes". In this case, it is not necessary to exclude any values from the dictionary since both classes have at least one corresponding value.