Based on prior knowledge, we can analyze the relationship between the PH feature and the target variable (grain yield) to determine the appropriate ranges of values.

Here is the analysis and the resulting dictionary:

```json
{
	"low": [2.5, 2.6, 2.7, 2.8, 2.9],
	"high": [3.5, 3.6, 3.7, 3.8, 3.9]
}
```

The analysis suggests that typically, when the PH feature is around 2.5 to 2.9, the grain yield of the soybean cultivar tends to be low. On the other hand, when the PH feature ranges from 3.5 to 3.9, the grain yield tends to be high. These values are just examples and may vary depending on the specific dataset and context.