Based on prior knowledge, the feature ZSN_A, which represents the presence of chronic heart failure in the anamnesis, is directly related to the task of determining if the patient has chronic heart failure or not. 

To analyze the relationship between the feature and the task, we should examine the distribution of ZSN_A values for each target class.

Here is the dictionary generated based on the analysis:

```json
{
	"no": ["there is no chronic heart failure"], 
	"yes": ["I stage", "IIА stage", "IIB stage"]
}
```

Explanation:
- For the target class "no" (indicating no chronic heart failure), the only possible value for ZSN_A is "there is no chronic heart failure".
- For the target class "yes" (indicating the presence of chronic heart failure), the possible values for ZSN_A are "I stage", "IIА stage", and "IIB stage".

Please note that based on the given feature description, these are the specific values that can be inferred with certainty for each target class. If there are other possible values for ZSN_A that are hard to predict or not mentioned, they do not need to be included in the dictionary.