Based on prior knowledge, the education level of a client may have an impact on their likelihood of subscribing to a term deposit. Higher education levels like tertiary may indicate a higher income or financial awareness, which could increase the chances of subscribing. Secondary education levels may have a slightly lower impact, while unknown or primary education levels may have a lower likelihood of subscribing.

Analyzing the relationship between the feature "education level" and the target "Does this client subscribe to a term deposit?", we can create a dictionary as follows:

```json
{
	"no": ["unknown", "primary"], 
	"yes": ["tertiary", "secondary"]
}
```

This dictionary suggests that clients with unknown or primary education levels are more likely to not subscribe to a term deposit, while clients with tertiary or secondary education levels are more likely to subscribe. Note that we have excluded values that are hard to predict from the dictionary, as mentioned in the task description.