Knowledge graph methodology and resources doubt

If I have 5 node categories A,B,C,D,E such that A1, A2 … etc are nodes belonging to type A, and these nodes have edges connecting to them (A1 → B2 → C1 … and so on) , and any edge connecting A and B are of a certain type, and that connecting B and C are of a certain type. How can I find an entire graph for an unknown A(i) as input . (Basically the output should give edge type AB, node B value, Edge type for BC, Node C value and so on).

Can you please mention any good resources I can read on to better understand and achieve this? Thank you so much.

Kindly let me know if I can rephrase my question or clarify anything. I am still a rookie trying to navigate and understand my way around graphs and graph machine learning

Do you mean getting all the nodes/edges that are reachable from a given node?

Yes! That was my doubt. If given one node as input for prediction after training, it should be able to output a graph with it’s possible connections to other nodes of different type.

Hi, sorry for the late reply. You could achieve so by using the out_edges API of DGLGraph iteratively, which simulates graph traversal.

Thank you @minjie. I shall check it out. appreciate it