Based on prior knowledge, there might be a relationship between sex and heart disease. Studies have shown that heart disease can differ between males and females. For example, men are generally more prone to heart disease at a younger age, while women tend to develop heart disease after menopause.

To analyze the relationship between the feature "Sex" and the task "Does the coronary angiography of this patient show a heart disease?", we can examine the distribution of sexes among patients with and without heart disease.

We cannot provide specific details without access to the dataset. However, we can create a general dictionary based on the understanding that both males and females may exhibit heart disease. Here is an example dictionary:

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

This suggests that both sexes, males and females, can be present in both the "no" (does not show heart disease) and "yes" (shows heart disease) categories.