Based on prior knowledge, I don't have specific information about the direct relationship between the number of stems (NLP) and the grain yield of soybean cultivar. However, I can provide a general analysis of the feature and its possible influence on the target variable.

In a soybean cultivar, the number of stems (NLP) can potentially indirectly affect the grain yield. More stems could lead to more pods, which in turn could lead to higher grain yield. However, there are also other factors such as nutrient availability, climate conditions, disease resistance, and farming practices that can significantly impact grain yield.

To create the dictionary, I will provide a sample based on assumptions and general patterns. Please note that the values of the feature (NLP) and target class (low or high) are specific to this example and may not reflect actual patterns in your dataset.

```json
{
	"low": [1.5, 2.0, 2.5, 3.0, 3.5],
	"high": [4.5, 5.0, 5.5, 6.0, 6.5]
}
```

In this sample, the "low" target class is associated with lower values of NLP (1.5, 2.0, 2.5, 3.0, 3.5), and the "high" target class is associated with higher values of NLP (4.5, 5.0, 5.5, 6.0, 6.5). These values are just examples and should be replaced with actual values based on the relationship observed in your dataset or domain expertise.