Based on prior knowledge, we can analyze the relationship between the number of stems (NLP) and the grain yield of soybean cultivars.

NLP is a numeric variable that represents the number of stems for a soybean cultivar. Generally, a higher number of stems indicates a more bushy and productive plant, which can potentially lead to higher grain yield. 

To determine the appropriate ranges of NLP values for the target classes 'low' and 'high' grain yield, we need more specific information such as quantitative data or thresholds. Without such information, it is difficult to determine exact ranges for NLP values and their relationship with grain yield. Nonetheless, we can still provide a general analysis and suggest some typical values.

Assuming a higher NLP generally leads to a higher grain yield, we can speculate some ranges of values for the target classes:

- For 'low' grain yield: 
  - Possible NLP values: [0.0, 1.0, 2.0, 3.0, 4.0]

- For 'high' grain yield:
  - Possible NLP values: [8.0, 9.0, 10.0, 11.0, 12.0]

Keep in mind that these values are purely speculative and should be validated with actual data or domain knowledge. The given NLP values are presented as floats in the lists for each target class.

Here is the generated dictionary:

```json
{
	"low": [0.0, 1.0, 2.0, 3.0, 4.0],
	"high": [8.0, 9.0, 10.0, 11.0, 12.0]
}
```