To analyze the relationship between the Repetition feature and the grain yield of the soybean cultivar, we can use our prior knowledge and observe historical data or experimental results.

Since the feature description only mentions "Repetition" without further details, we'll assume that it refers to the number of times a specific cultivar has been repeated in a dataset or experimental trial.

To determine the appropriate ranges of values for the Repetition feature, we need more information. Without it, we cannot precisely define the ranges or intervals. However, for the purpose of this analysis, we can still generate sample values for both the 'low' and 'high' target class.

Based on historical data or experimental results, we can create the dictionary:

```json
{
	"low": [1.0, 2.0, 3.0, 4.0, 5.0],
	"high": [10.0, 12.0, 15.0, 20.0, 25.0]
}
```

This dictionary suggests some possible values for the Repetition feature that are associated with the 'low' and 'high' grain yield of soybean cultivars. Note that the values provided here are primarily for illustrative purposes and should be adjusted based on actual data and domain knowledge.