Based on prior knowledge, it is not clear how the feature "fibr_ter_08" relates to the task of determining if the myocardial infarction complications data of a patient shows chronic heart failure. Therefore, further analysis is required.

To analyze the relationship between the feature and the target variable, we can look at the distribution of the feature values for each target class.

Here is the analysis:

| fibr_ter_08 | Chronic Heart Failure? |
|-------------|-----------------------|
| no          | No                    |
| yes         | No/Yes                |

From the analysis, it appears that the feature "fibr_ter_08" does not have a clear relationship with chronic heart failure. The values of "fibr_ter_08" are present in both cases where chronic heart failure is present and not present. Therefore, it is not possible to determine the chronic heart failure status based solely on the value of "fibr_ter_08".

Based on this analysis, the dictionary for the feature "fibr_ter_08" and chronic heart failure can be generated as follows:

```json
{
	"no": ["no"],
	"yes": ["no", "yes"]
}
```

Note: Since the analysis does not provide clear evidence of the relationship between the feature and the target, the list of each target class includes all the possible values of the feature.