These are knobs that you can tune to make the graph construction more/less opinionated. Generally speaking, the more we make it opinionated the better it fits the task.

At a high-level:

(1) Domain: allows you to "talk to the graph constructor". If you care particularly about one aspect of your data, this is the place to say it. For reference, take a look at some of the example prompts on our website (https://circlemind.co/)

(2) Example Queries: if you know what class of questions users will ask, it'd be useful to give the system this information so that it will "keep these questions in mind" when designing the graph. If you don't know which kinds of questions, you can just put a couple of high-level questions that you think apply to your data.

(3) Entity Types: this has a very high impact on the final quality of the graph. Think of these as the types of entities that you want to extract from your data, e.g. person, place, event, etc

All of the above help construct the knowledge graph so that it is specifically designed for your use-case.