Based on prior knowledge, fibr_ter_01 is a categorical feature representing whether the patient received fibrinolytic therapy by Celiasum 750k IU. To analyze the relationship between fibr_ter_01 and the presence of chronic heart failure, we can examine the distribution of fibr_ter_01 categories for the target classes "yes" (indicating chronic heart failure) and "no" (indicating no chronic heart failure) separately.

Here is a dictionary denoting the relationship between the feature fibr_ter_01 and the target class "yes" and "no":

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

Since the feature fibr_ter_01 has categories 'no' and 'yes', we can conclude that for the target class "no" (no chronic heart failure), the only possible value for fibr_ter_01 is "no". Similarly, for the target class "yes" (chronic heart failure), the only possible value for fibr_ter_01 is "yes".

Note: As per the requirement, if there are any other possible values of fibr_ter_01 that are hard to predict or not mentioned in the dataset, they can be excluded from the dictionary.