Based on prior knowledge, the feature "month" represents the last contact month of the year. To analyze its relationship with the target variable of whether the client subscribes to a term deposit or not, we can examine the distribution of different month values for each target class.

Here is a dictionary showing the possible values of the "month" feature for each target class:

```json
{
    "no": ["may", "jun", "jul", "aug", "oct", "nov", "dec"],
    "yes": ["mar", "apr", "sep"]
}
```

For the target class "no", the possible month values are ["may", "jun", "jul", "aug", "oct", "nov", "dec"]. These months indicate that the majority of clients who did not subscribe to a term deposit were contacted in the middle and later months of the year. 

For the target class "yes", the possible month values are ["mar", "apr", "sep"]. These months suggest that clients who subscribed to a term deposit were contacted in the early spring and autumn months. 

The list of possible month values for each target class is not exhaustive and only includes the most frequent values based on prior knowledge.