Based on prior knowledge, we can analyze the relationship between the feature "ant_im" and the presence of chronic heart failure in the context of myocardial infarction complications.

To determine if a patient shows chronic heart failure, we need to analyze how the "ant_im" feature is related to this target variable. However, without any additional data or knowledge about the feature, it is difficult to determine the exact relationship between "ant_im" and chronic heart failure. 

To create the dictionary, we can assume that certain values of "ant_im" may be more likely to indicate chronic heart failure, while others may indicate the absence of chronic heart failure. Based on this assumption, we can create a dictionary as follows:

```json
{
    "no": ["QRS has no changes", "there is no infarct in this location"],
    "yes": ["QRS is like QS-complex", "QRS is like QR-complex", "QRS is like Qr-complex"]
}
```

In this dictionary, the values "QRS has no changes" and "there is no infarct in this location" indicate a lower likelihood of chronic heart failure. In contrast, the values "QRS is like QS-complex", "QRS is like QR-complex", and "QRS is like Qr-complex" indicate a higher likelihood of chronic heart failure.

It is important to note that this analysis is based on assumptions and limited information provided. Without further data or knowledge about the specific relationship between "ant_im" and chronic heart failure, the accuracy of these assumptions may vary.