Based on prior knowledge, the feature "contact" represents the type of communication the bank had with the client during the marketing campaign. The contact communication type can take three categories: "unknown", "cellular", and "telephone".

To analyze the relationship between the feature "contact" and the target variable "Does this client subscribe to a term deposit?", we can calculate the distribution of contact types for each target class. By comparing these distributions, we can understand how the feature relates to the target.

Here is the analysis:

- For clients who did not subscribe to a term deposit (target class "no"), the possible values of the contact feature are "unknown", "cellular", and "telephone".
- For clients who subscribed to a term deposit (target class "yes"), the possible values of the contact feature are "unknown", "cellular", and "telephone".

Based on this analysis, we can create the dictionary:

```json
{
	"no": ["unknown", "cellular", "telephone"],
	"yes": ["unknown", "cellular", "telephone"]
}
```

This dictionary captures the possible values of the contact feature for each target class.