Based on the given information, it seems that the feature "Season" is a numeric variable with two possible values: 1 and 2. We need to analyze how this feature relates to the target variable, which is the grain yield of a soybean cultivar categorized as "low" or "high". 

To analyze the relationship, we can examine historical data or use our prior knowledge of soybean cultivation. Suppose 1 represents the planting season for soybean cultivars with low grain yield, while 2 represents the planting season for soybean cultivars with high grain yield. However, it's important to note that this analysis is based on assumptions and prior knowledge; further research or data validation might be necessary for more accurate results.

Here is the requested dictionary:

```json
{
	"low": [1.0, 1.0, 1.0, 1.0, 1.0], 
	"high": [2.0, 2.0, 2.0, 2.0, 2.0]
}
```

In this dictionary, we have provided 5 typical values for each target class: "low" and "high". For the "low" class, the typical values of the feature "Season" are 1.0, indicating that historically soybean cultivars planted in season 1 tend to have low grain yield. Similarly, for the "high" class, the typical values of the feature "Season" are 2.0, suggesting that soybean cultivars planted in season 2 have a higher grain yield.

Please note that this analysis is based on assumptions made using prior knowledge and may not reflect the actual relationship between the feature and target variable without further validation or data analysis.