Based on the provided feature description and task, the relationship between the feature "credit_history" and the target variable "Does this person receive a credit?" can be analyzed.

From prior knowledge, it can be assumed that the credit history of an individual plays a significant role in determining whether they receive a credit or not. Generally, individuals with a good credit history and a positive payment record are more likely to receive credit, while those with a poor credit history or delayed payments might not be eligible for credit.

Based on this analysis, the following dictionary can be generated:

```json
{
	"yes": ["existing paid", "no credits/all paid", "all paid"],
	"no": ["critical/other existing credit", "delayed previously"]
}
```

Note that the values "existing paid", "no credits/all paid", and "all paid" are included in the "yes" list as they indicate a positive credit history. Similarly, the values "critical/other existing credit" and "delayed previously" are included in the "no" list as they suggest a negative credit history.

Please note that this analysis is based on general assumptions and may not capture all possible variations in the relationship between "credit_history" and the target variable. Further analysis and domain-specific knowledge may be required for a more accurate understanding of the relationship.