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Developing an NLP UI for an OWL Knowledge Graph

First, I'm a total noob with Wolfram so apologies in advance if this is a dumb question. I have a bunch of data for the domain of the UN Sustainable Development Goals in an OWL knowledge graph. I see that Wolfram can import data in Turtle or RDF/XML, both of which are natural export formats for the graph. It has information such as what Non-governmental Organizations (NGOs) are working on various UN Sustainable Development Goals. What I would like to to is to import the data and then use the Wolfram LLM so that users (e.g., an economist at the UN) can ask questions like "Which NGOs in India are working on eliminating poverty?" and get appropriate answers. Are there any tutorials or examples that are similar and would give me a head start? Also, it doesn't have to be an example using Turtle or RDF/XML. That would be the best format because it would preserve the most info but I can easily export most of the data to more common formats like CSV files and preserve most of the information.

Thanks in advance for any help.
Michael DeBellis
https://www.michaeldebellis.com/blog

POSTED BY: Michael DeBellis
2 Replies

(It would be helpful if you provided an example Turtle/RDF file and some relevant example questions)

You might consider using the LLM prompt to generate a SPARQL query (as in https://apex974.com/articles/chatgpt-for-info-retrieval-from-knowledge-graph) which you then apply using the various Mathematica SPARQL commands (https://reference.wolfram.com/language/GraphStore/guide/SPARQLQuery.html)

POSTED BY: Joshua Schrier
POSTED BY: Michael DeBellis
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