Based on my prior knowledge, I will analyze the relationship between the feature IBS_POST and the presence of chronic heart failure.

Since the task is to determine if the patient's myocardial infarction complications data shows chronic heart failure, the presence of chronic heart failure would indicate a positive ("yes") value for the target class, while the absence of chronic heart failure would indicate a negative ("no") value for the target class.

Analyzing the feature IBS_POST, we can make the following observations:

- "there was no СHD" category: It suggests that there was no coronary heart disease in recent weeks or days before admission to the hospital. This category might be associated with a negative ("no") value for chronic heart failure.

- "exertional angina pectoris" category: It suggests the presence of exertional angina pectoris, indicating some level of coronary heart disease. This category might be associated with a positive ("yes") value for chronic heart failure.

- "unstable angina pectoris" category: It suggests the presence of unstable angina pectoris, which is a more severe form of coronary heart disease compared to exertional angina pectoris. This category might also be associated with a positive ("yes") value for chronic heart failure.

Based on this analysis, the dictionary for the relationship between the feature IBS_POST and the target variable (presence of chronic heart failure) can be constructed as follows:

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

Note that in this scenario, the feature values "there was no СHD" are associated with the target class "no" (negative), while the feature values "exertional angina pectoris" and "unstable angina pectoris" are associated with the target class "yes" (positive).