Based on the task and feature description, we are trying to understand the relationship between the feature "Season" and the target variable "grain yield of soybean cultivar" in order to determine if the yield will be low or high.

To analyze this relationship, we can consider our prior knowledge and experience with soybean cultivation. Season can be a crucial factor in determining the grain yield of soybean cultivars. Soybeans are typically grown in specific seasons depending on the region. For example, in temperate regions, soybeans are usually grown during spring and summer (Season 1) or fall and winter (Season 2).

Based on this knowledge, we can hypothesize that the grain yield of the soybean cultivar will likely vary depending on the season it is grown in. Let's assume that high grain yield is associated with Season 1, while low grain yield is associated with Season 2.

To generate the dictionary, we can populate the "low" and "high" lists with typical Season values for each target class. Let's consider 5 typical values for each target class:

```json
{
	"low": [2.5, 2.6, 2.4, 2.7, 2.8],
	"high": [1.3, 1.4, 1.2, 1.5, 1.1]
}
```

Please note that these are example values and can be adjusted based on domain knowledge or more specific data analysis.