Based on prior knowledge, we can assume that the number of stems (NLP) in soybean cultivars can have an impact on grain yield. Here's how the NLP feature may relate to the task:

1. Low grain yield: In soybean cultivars with low grain yield, we can expect the number of stems (NLP) to be relatively low. This could be due to factors such as plant stress, disease, or suboptimal growing conditions.

2. High grain yield: In soybean cultivars with high grain yield, we can expect the number of stems (NLP) to be relatively high. This indicates healthy and productive plants with optimal growing conditions.

Now, let's generate the dictionary with typical NLP values for each target class:

```json
{
	"low": [0.5, 1.2, 1.8, 2.1, 2.9],
	"high": [3.5, 4.2, 5.1, 5.8, 6.4]
}
```

Please note that these values are just hypothetical and may not represent the actual range or distribution of NLP for soybean cultivars with low or high grain yield. The actual values would require further domain-specific knowledge and analysis.