Based on prior knowledge, the ST_Slope feature is related to the target variable of heart disease as it represents the slope of the peak exercise ST segment. The slope of the ST segment can potentially indicate abnormalities in the heart. Let's analyze the relationship between the ST_Slope feature and the presence of heart disease.

To do this analysis, we would need a dataset that includes the ST_Slope feature and the corresponding target variable indicating whether the coronary angiography shows a heart disease or not. Without the actual dataset, it is difficult to provide specific details. However, based on standard medical knowledge, we can make some general assumptions:

- If the ST_Slope is "Up", it could indicate myocardial ischemia, which is often associated with heart disease. Therefore, this value might be more common in the "yes" category.
- If the ST_Slope is "Down", it could indicate myocardial infarction or abnormal heart rhythms, which are also associated with heart disease. Therefore, this value might also be more common in the "yes" category.
- If the ST_Slope is "Flat", it might suggest a less severe or normal condition of the heart. Therefore, it could be more common in the "no" category.

Again, these assumptions are based on general medical knowledge and without the actual dataset, we cannot provide specific details or percentages. However, based on these assumptions, we can generate the dictionary as requested:

```json
{
	"no": ["Flat"],
	"yes": ["Up", "Flat", "Down"]
}
```

Please note that this is a general analysis and the actual relationship between the ST_Slope feature and the presence of heart disease should be confirmed using real data.