Based on my prior knowledge, beta-blockers are commonly prescribed for patients with chronic heart failure (CHF) as they help improve heart function and reduce the workload on the heart. Therefore, it is likely that patients with chronic heart failure would have a higher likelihood of being prescribed beta-blockers (B_BLOK_S_n = 'yes') compared to those without chronic heart failure.

To analyze the relationship between the feature B_BLOK_S_n and the task of whether the patient shows chronic heart failure, we would need access to data that includes the target variable (presence/absence of chronic heart failure) along with the B_BLOK_S_n feature. Without this data, we cannot infer the relationship directly.

However, if we assume that patients with chronic heart failure are those who exhibit myocardial infarction complications, we can make some predictions based on general knowledge. In this case, the dictionary would look as follows:

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

Since beta-blockers are typically prescribed for chronic heart failure, patients without chronic heart failure would likely not be on beta-blockers (B_BLOK_S_n = 'no'). Patients with chronic heart failure could be prescribed beta-blockers (B_BLOK_S_n = 'yes') or may not be on beta-blockers as well.

Note: This assumption may not hold true for all cases, as individual patient characteristics and other factors may influence the decision to prescribe beta-blockers. Therefore, it is important to have access to the actual data to make a more accurate analysis.