Based on prior knowledge, the number of pregnancies can be a relevant factor in determining whether or not a person has diabetes. Let's conduct a thorough analysis of the relationship between the feature "Pregnancies" and the target task of "Does this person have diabetes?".

To do this analysis, we can consider the feature values for individuals who have diabetes (target class "yes") and those who do not have diabetes (target class "no"). We will then identify a range of typical pregnancies values for each target class.

Analysis:

For the target class "yes" (person has diabetes), typical values of the feature "Pregnancies" could be:

1. 2.0
2. 5.0
3. 8.0
4. 10.0
5. 12.0

For the target class "no" (person does not have diabetes), typical values of the feature "Pregnancies" could be:

1. 0.0
2. 1.0
3. 3.0
4. 6.0
5. 9.0

Based on this analysis, we can construct the dictionary as follows:

```json
{
	"yes": [2.0, 5.0, 8.0, 10.0, 12.0],
	"no": [0.0, 1.0, 3.0, 6.0, 9.0]
}
```

Now, you can use this dictionary to further analyze the relationship between the feature "Pregnancies" and the target task "Does this person have diabetes?".