Based on prior knowledge, the DiabetesPedigreeFunction is a numeric variable that represents the diabetes pedigree function, which measures the likelihood of a person developing diabetes based on family history. A higher value indicates a higher likelihood of developing diabetes.

To analyze the relationship between DiabetesPedigreeFunction and the task of determining whether a person has diabetes or not, we can examine the distribution of DiabetesPedigreeFunction values for each target class ('yes' and 'no').

Here is the dictionary representing the relationship between DiabetesPedigreeFunction and the target variable:

```json
{
    "yes": [0.234, 0.547, 0.798, 0.987, 1.234],
    "no": [0.092, 0.356, 0.621, 0.789, 0.987]
}
```

In this dictionary, the "yes" key represents the target class where the person has diabetes, and the "no" key represents the target class where the person does not have diabetes. The values under each key are five example DiabetesPedigreeFunction values that are typical for each target class.

Please note that the values provided in this example are hypothetical and should be replaced with actual values obtained from the dataset or domain knowledge.