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Comment by audiala | Hacker News Reader

Wikidata is such a treasure. There is quite a learning curve to master the SPARQL query language but it is really powerful. We are testing it to provide context to LLMs when generating audio-guides and the results are very impressive so far.

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I wish there was a way to add results from scientific papers to wikidata - imagine doing meta-analyses by SPARQL queries

You totally can! - https://www.wikidata.org/wiki/Q30249683

It's just pretty sparse, so you would need a focused effort to fill out predicates of interest.

Indeed, and hopefully -if there was a structured way of doing it - people might want to do that effort in relation to doing reviews or meta-analysis to make the underlying data available for others, and make it easier to reproduce or update the results over time

Am I missing something? I do not see any results indicated in the statements of that entity.

Right, such a result would need to be marked with a new predicate (verb) like: ``` Subject - Transformer's Paper Predicate - Score Object - BLEU (28.4) ``` One of the trickiest things use a semantic triple store like this is that there's a lot of ways of phrasing the data, lots of ambiguity. LLMs help in this case by being able to more gracefully handle cases like having both 'Score' and 'Benchmark' predicates, mergining the two together.

One of my favorite things about ChatGPT is that I pretty much never have to write SPARQL myself anymore. I’ve had zero problems with the resulting queries either, except in cases where I’ve prompted it incorrectly.

Yeah, it works so well, I wonder if it's just a natural fit due to the attention mechanism and graph databases sharing some common semantic triple foundations

Any recommendations to learn SPARQL? I've looked into it and decided against it about as often as Nix.

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