Based on prior knowledge, it is known that risk of heart disease differs between males and females. Therefore, there is likely to be a relationship between the Sex feature and the presence of heart disease.

To analyze the relationship between the feature Sex and the task of determining if the patient has a heart disease, we can examine the distribution of the Sex feature among the two target classes (presence or absence of heart disease) in the dataset.

Let's assume we have the following data:

|   Sex   | Heart Disease |
|---------|---------------|
|    M    |      Yes      |
|    F    |       No      |
|    F    |      Yes      |
|    M    |      No       |
|    F    |      Yes      |

Based on this data, we can construct the following dictionary:

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

Explanation:
- For the target class "no" (no heart disease), we have only one instance of Sex which is "M".
- For the target class "yes" (heart disease present), we have only one instance of Sex which is "F".

Please note that this analysis assumes that the provided dataset is representative and sufficient to derive a conclusion about the relationship between the Sex feature and the presence of heart disease.