Based on my prior knowledge, fibr_ter_07 is a feature that represents whether the patient has received fibrinolytic therapy by Celiasum 250k IU. To analyze the relationship between this feature and the presence of chronic heart failure, we can examine the distribution of the feature values for each target class.

Here's the analysis of the relationship between the feature fibr_ter_07 and the presence of chronic heart failure:

For the target class "no" (chronic heart failure not present):
- Possible values of feature fibr_ter_07: ['no', 'yes']

For the target class "yes" (chronic heart failure present):
- Possible values of feature fibr_ter_07: ['no', 'yes']

Based on the analysis, it seems that the feature fibr_ter_07 does not provide strong discriminatory information regarding the presence of chronic heart failure. Both target classes have the same set of possible values for the feature.

Here's the dictionary representing the relationship between the feature fibr_ter_07 and the presence of chronic heart failure:

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

Note that both lists of feature values for each target class include both "no" and "yes", indicating that there is no clear relationship between the feature fibr_ter_07 and the presence of chronic heart failure.