Based on the given feature "Repetition" and the task of predicting the grain yield of a soybean cultivar as low or high, it is necessary to analyze the relationship between the feature and the target.

Since the feature "Repetition" is not well defined in the given description, I will assume it refers to the number of times an experiment or observation was repeated for a particular soybean cultivar. The target variable "grain yield" can be categorized as either low or high.

To analyze the relationship, we need to determine typical values of "Repetition" for each target class. Typically, a higher number of repetitions could indicate a higher level of reliability and accuracy in the experiment, potentially leading to a better understanding of the soybean cultivar's properties. Therefore, we can hypothesize that high grain yield would be associated with higher values of "Repetition."

Based on this assumption, here is a possible dictionary showing typical values of "Repetition" for each target class:

```json
{
	"low": [1, 2, 3, 4, 5],
	"high": [6, 7, 8, 9, 10]
}
```

Please note that these values are only hypothetical and may vary depending on the specific dataset or domain knowledge.