Based on prior knowledge, the feature "month" represents the last contact month of the year. To analyze the relationship between this feature and the target variable (whether the client subscribes to a term deposit), we can look at the distribution of the feature values for each target class.

Here is the analysis and resulting dictionary:

For clients who do not subscribe to a term deposit ("no"):

- Possible values of feature month: ['may', 'jun', 'jul', 'aug', 'oct', 'nov', 'dec']

For clients who subscribe to a term deposit ("yes"):

- Possible values of feature month: ['mar', 'apr', 'sep']

Based on the analysis, we can create the dictionary:

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

This means that for clients who do not subscribe to a term deposit, the feature "month" can have any value from the list ["may", "jun", "jul", "aug", "oct", "nov", "dec"]. On the other hand, for clients who subscribe to a term deposit, the feature "month" can have any value from the list ["mar", "apr", "sep"].