Support triple extraction use case

[caufieldjh]

In discussion with RNA-KG group (Marco Mesiti, Elena Casiraghi, Emanuele Cavalleri) and @justaddcoffee -
we would like to be able to extract triples (s, p, o) from a provided text, using graph embeddings to guide the process.
The goal is to find additional content for RNA-KG. Using OntoGPT has worked well for this so far but does not take advantage of the existing relations within the KG.

This would involve:

• Including interface (CLI and/or GUI) to use text document as input
• Providing way to index KGX and/or derive a schema from it
• Building wrapper for graph embeddings.
  • Using GRAPE directly through this project would be a heavy lift, so retrieving embeddings from an external source like Huggingface would likely work better, save time, and avoid introduction of many new dependencies
• Writing documentation for the above

Integrating some process for comparison of the extracted triples would be ideal (e.g., A vs B appears in 20 documents, 15 of them from different sources, etc).

RNA-KG group has also suggested trying an alternative vector DB (https://www.llamaindex.ai/) to see if it works better for RAG with KG data.

[cmungall]

I'm not following the part about KG embeddings. I don't think we'd want a dependency on GRAPE here. But we want to support people providing their own embeddings e.g. via venomx. However I don't get how GRAPE/node2vec style embeddings would work with RAG.

Good suggestion to explore llamaindex. But I think this is orthogonal. See #34

[justaddcoffee]

Not sure what exactly Marco had in mind for using KG embeddings with RAG, but possibly something like read in abstracts that may contain relations of interest, do NER/ground to get IDs/CURIEs of interest from text, then pull these and any related nodes using KG embeddings and send along for context? Not sure

[justaddcoffee]

Also, agree that a GRAPE dependency might not be what we want here. I've made a (draft) PR #36 to support pulling embeddings from huggingface or any other URL