Based on prior knowledge and understanding of the feature "GT_POST" and the task of determining if the myocardial infarction complications data shows chronic heart failure, the relationship between the feature and the target variable can be analyzed.

In this case, the feature "GT_POST" refers to the presence or absence of paroxysms of ventricular tachycardia at the time of admission to the intensive care unit. Ventricular tachycardia is a fast heart rate that starts in the ventricles, which can lead to a decreased cardiac output and potentially contribute to the development of chronic heart failure.

To analyze the relationship between the feature "GT_POST" and the presence of chronic heart failure, we can examine the frequency of the different categories of the feature within each target class. This will help us identify any patterns or associations.

Now, let's create the dictionary as requested:

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

Since the feature "GT_POST" is a categorical variable with only two possible categories, "no" and "yes", we can directly map these categories to the respective target classes "no" and "yes".

Note that if there were additional values for the feature "GT_POST" that are hard to predict or have no clear relationship with the target variable, they would not be included in the dictionary. However, in this case, since the feature has only two categories, we can include them as shown in the dictionary.