Upon initial analysis, it seems that the feature "Repetition" does not directly determine the grain yield of a soybean cultivar. The feature "Cultivar names" is also not relevant as a numeric variable since the ranges of values are not specified and its relationship with the target is not clear.

However, assuming that the repetition refers to the number of times an experiment is repeated or replicated, we can make some assumptions about its relationship with the grain yield. In general, higher repetition of experiments can lead to more accurate and reliable results, which may result in a higher grain yield prediction. Therefore, we can speculate that a higher repetition value may be associated with a higher grain yield.

Based on this analysis, the dictionary would look like this:

```json
{
	"low": [1.0, 2.0, 3.0, 4.0, 5.0],
	"high": [6.0, 7.0, 8.0, 9.0, 10.0]
}
```

Please note that these assumptions and values are based on limited information and should not be treated as conclusive evidence. A more accurate analysis and understanding would require detailed information about the specific characteristics of soybean cultivars and the experiment design.