Based on the given feature description of SEQN (Respondent Sequence Number), it is difficult to determine the appropriate ranges without additional information or domain knowledge.

However, since the task is to predict whether a person is a senior or non-senior, it is reasonable to assume that age increases as the SEQN value increases. Therefore, it can be inferred that higher SEQN values are associated with older individuals.

To provide the requested dictionary, we'll assume that higher SEQN values correspond to seniors. Please note that this assumption may not be accurate and further domain knowledge would be required to determine the appropriate ranges of SEQN values for seniors.

Here is the requested dictionary:

```json
{
	"Adult": [10000.0, 10001.0, 10002.0, 10003.0, 10004.0],
	"Senior": [20000.0, 20001.0, 20002.0, 20003.0, 20004.0]
}
```

In this dictionary, the "Adult" key represents the target class of non-senior individuals, and the "Senior" key represents the target class of senior individuals. The values associated with each key are exemplary SEQN values.

Please note that these values are arbitrary and do not reflect any specific real-world data.