Based on prior knowledge, we need to analyze the relationship between the feature "GB" (Presence of essential hypertension) and the presence of chronic heart failure in myocardial infarction complications data.

We can start by categorizing the target class into "yes" and "no" based on the presence or absence of chronic heart failure. 

After that, we can analyze the possible values of the "GB" feature for each target class and create a dictionary accordingly.

Here is the analysis:

Target Class "Yes" (Presence of Chronic Heart Failure):
- Possible values of feature GB for target class "yes": ['Stage 2', 'Stage 3']

Target Class "No" (Absence of Chronic Heart Failure):
- Possible values of feature GB for target class "no": ['there is no essential hypertension', 'Stage 1']

Based on this analysis, we can create the dictionary:

```json
{
	"no": ["there is no essential hypertension", "Stage 1"],
	"yes": ["Stage 2", "Stage 3"]
}
```

Please note that only the relevant values of the "GB" feature are included in the dictionary, and the possible values not mentioned here are considered hard to predict.