Based on the given feature description and task, we need to analyze the relationship between the feature "fibr_ter_06" and the target variable "chronic heart failure" to determine if the patient's myocardial infarction complications data indicates the presence or absence of chronic heart failure.

To conduct this analysis, we can examine the distribution of the feature values for each class of the target variable. We should categorize the feature values for each class of the target variable and input these values into the dictionary.

Let's analyze the relationship between the feature "fibr_ter_06" and the target variable "chronic heart failure":

For the target class "no" (indicating no chronic heart failure):

- Possible values of "fibr_ter_06" for target class "no" are: ['no']

For the target class "yes" (indicating chronic heart failure):

- Possible values of "fibr_ter_06" for target class "yes" are: ['no', 'yes']

Based on this analysis, we can create the dictionary:

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

Note: As per the analysis, the feature "fibr_ter_06" has a value of "no" for patients without chronic heart failure (target class "no") and it can have values of both "no" and "yes" for patients with chronic heart failure (target class "yes").