Based on prior knowledge, there may be a relationship between a patient's sex and the likelihood of having heart disease. 

To analyze the relationship between the feature "Sex" and the task "Does the coronary angiography of this patient show heart disease?", we can examine the distribution of the target variable (heart disease) for each category of the feature.

Let's assume "yes" represents patients with heart disease and "no" represents patients without heart disease.

To create the dictionary, we need to determine the possible values of the feature "Sex" for each target class.

Here is the resulting dictionary:

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

Since the feature "Sex" is a categorical variable with two categories, "M" and "F", and it is plausible to have individuals of both sexes with or without heart disease, we include both categories in the dictionary for each target class.