To analyze the relationship between the "FK_STENOK" feature and the presence of chronic heart failure, we can look at the distribution of feature values for both the "yes" and "no" classes.

Based on prior knowledge, it is expected that higher functional class of angina pectoris (higher values of "FK_STENOK") may indicate a higher likelihood of chronic heart failure.

Here is the generated dictionary:

```json
{
	"no": ["there is no angina pectoris", "II FC"],
	"yes": ["IV FC", "I FC", "III FC."]
}
```

The values "there is no angina pectoris" and "II FC" are the possible values of the "FK_STENOK" feature associated with the target class "no," indicating that patients with these values are less likely to have chronic heart failure.

On the other hand, the values "IV FC", "I FC", and "III FC." are the possible values of the "FK_STENOK" feature associated with the target class "yes," suggesting a higher likelihood of chronic heart failure for patients with these values.

As per the requirement, values that are hard to predict or not mentioned in the dictionary are not included.