Based on my prior knowledge, the relationship between the feature "ChestPainType" and the task of determining if the coronary angiography shows a heart disease might be as follows:

- "ATA" (Atypical Angina): This type of chest pain is often less likely to indicate a heart disease. So, it might have a higher chance of being associated with the target class "no".

- "NAP" (Non-Anginal Pain): This type of chest pain is typically not related to heart disease. Therefore, it might have a higher chance of being associated with the target class "no".

- "ASY" (Asymptomatic): Asymptomatic individuals do not experience chest pain, which might suggest a lower likelihood of heart disease. Therefore, it might have a higher chance of being associated with the target class "no".

- "TA" (Typical Angina): This type of chest pain is usually associated with heart disease. Hence, it might have a higher chance of being associated with the target class "yes".

Based on this analysis, the dictionary would be:

```json
{
    "no": ["ATA", "NAP", "ASY"],
    "yes": ["TA"]
}
```