Based on prior knowledge, we can analyze the relationship between the feature "NLP" (Number of stems) and the target variable "grain yield". 

In general, a higher number of stems can indicate better health and growth of the soybean plants, which may potentially lead to a high grain yield. However, there might be other factors that can affect grain yield, such as soil quality, weather conditions, and the overall health of the plants. Therefore, it is important to consider these factors along with the NLP value to determine the potential grain yield.

To generate the required dictionary, we need to provide five typical NLP values for each target class 'low' and 'high'. Let's assume the following typical NLP values for each class:

For target class 'low':
- NLP values: 0.5, 1.2, 1.7, 2.1, 3.0

For target class 'high':
- NLP values: 2.5, 3.2, 3.7, 4.1, 5.0

Based on this analysis, we can create the dictionary in the desired format:

```json
{
	"low": [0.5, 1.2, 1.7, 2.1, 3.0],
	"high": [2.5, 3.2, 3.7, 4.1, 5.0]
}
```