Based on my prior knowledge, the feature "Sex" may have a relationship with the task of determining whether the patient's coronary angiography shows a heart disease. Several studies have shown that there could be a correlation between gender and the prevalence of heart disease.

To determine the relationship between the feature and the target, we can look at the distribution of each gender in patients with and without heart disease.

Let's analyze the relationship and create the dictionary:

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

Based on the analysis, it seems that both genders, male (M) and female (F), can be represented in both the "no" (without heart disease) and "yes" (with heart disease) classes. Therefore, we include both genders in the dictionary for each target class.