Based on the given feature description and task, we can assume that the repetition refers to the number of times a particular experiment or trial is conducted for a soybean cultivar. To analyze the relationship between the repetition feature and the target variable (grain yield), we can use our prior knowledge and assumptions.

Dictionary analysis for the feature "Repetition" and task "yield of soybean cultivar":

```json
{
    "low": [1.0, 2.0, 3.0, 4.0, 5.0],  
    "high": [10.0, 12.0, 15.0, 18.0, 20.0]
}
```

This dictionary represents the possible values of the feature "Repetition" for each target class "low" and "high". We have selected 5 typical values for each target class based on our analysis. In this case, the values have been assumed to be numeric floats.

Please note that the specific numeric values given for "Repetition" are arbitrary and represent hypothetical values. To generate a more accurate analysis, it would be necessary to have actual data or a well-defined range of values for the cultivar names and their yield classifications.