Based on the provided feature description, we can analyze the relationship between the feature IBS_POST and the presence of chronic heart failure in the patient.

I will assume that if the patient has no chronic heart failure, the task will be marked as "no", and if the patient has chronic heart failure, the task will be marked as "yes".

To analyze the relationship, we need to look at the frequency distribution of IBS_POST values for each target class. Let's calculate it:

For target class "no":
- IBS_POST values: ['there was no СHD', 'exertional angina pectoris', 'unstable angina pectoris']

For target class "yes": 
- IBS_POST values: ['there was no СHD', 'exertional angina pectoris', 'unstable angina pectoris']

Based on the feature description, it seems that the IBS_POST values do not provide direct information about the presence of chronic heart failure. The possible values for both target classes are the same.

Therefore, the dictionary can be generated as follows:

```json
{
	"no": ["there was no СHD", "exertional angina pectoris", "unstable angina pectoris"],
	"yes": ["there was no СHD", "exertional angina pectoris", "unstable angina pectoris"]
}
```

Note: Since there is no specific information about the IBS_POST values that indicate chronic heart failure, we include all the possible values for both target classes.