Based on prior knowledge, let's assume that normal diastolic blood pressure ranges from 60 to 80 mm Hg, and anything above 80 mm Hg can be considered high.

To analyze the relationship between the BloodPressure feature and the task of determining if a person has diabetes, we can look at the distribution of BloodPressure values for each target class ('yes' or 'no').

Here is the analysis and the corresponding dictionary:

```json
{
	"yes": [82.0, 88.0, 86.0, 90.0, 94.0],
	"no": [75.0, 70.0, 78.0, 72.0, 68.0]
}
```

For the target class 'yes' (person has diabetes), five typical BloodPressure values are [82.0, 88.0, 86.0, 90.0, 94.0]. These values are higher than the normal range, indicating a possible relationship between high diastolic blood pressure and diabetes.

For the target class 'no' (person does not have diabetes), five typical BloodPressure values are [75.0, 70.0, 78.0, 72.0, 68.0]. These values are within or close to the normal range, suggesting that individuals without diabetes tend to have blood pressure readings within the normal range.

Please note that the given values are just examples and may not represent the actual distribution of the BloodPressure feature. Also, this analysis assumes that BloodPressure is a relevant feature for predicting diabetes, but it's always important to consider other factors and consult medical professionals for accurate diagnosis.