Based on my prior knowledge, I will analyze the relationship between the feature "contact communication type" and the target variable "Does this client subscribe to a term deposit?". 

In this case, the feature "contact communication type" represents the method of communication used to contact the client. The possible categories are 'unknown', 'cellular', and 'telephone'. 

Now, let's analyze the relationship between this feature and the target variable:

1. 'unknown': This category represents the cases where the communication type is unknown. It is difficult to determine the relationship between this category and the target variable without further information.

2. 'cellular': This category represents cases where the client was contacted through a cellular communication method. It is possible that clients who were contacted through their cellular phones may have a higher likelihood of subscribing to a term deposit. This is because cellular phones are more personal and individuals may be more inclined to pay attention to such calls.

3. 'telephone': This category represents cases where the client was contacted through a landline telephone. It is possible that clients who were contacted through landline phones may have a lower likelihood of subscribing to a term deposit. This is because landline calls are often perceived as marketing calls and individuals may be less receptive to them.

Based on this analysis, I will create a dictionary that reflects the relationship between the feature "contact communication type" and the target variable "Does this client subscribe to a term deposit?". The dictionary will include the possible values of the feature for each target class.

The dictionary is as follows:

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

Please note that this analysis is based on prior knowledge and assumptions. It would be ideal to perform further analysis and statistical tests to confirm the relationship between the feature and the target variable.