|Open||None||T90870 selfcontained projects around Wikidata (tracking)|
|Open||None||T76230 [Epic] data quality and trust|
|Open||maiarocg||T90881 Framework for checking sources on Wikidata (Does the source actually say what we claim it says?)|
This problem is called Natural Language Inference (NLI) also known as textual entitlement . It is a super hot problem now in the NLP community, but imho research is still far away from producing usable tools in the Wikipedia context. This also requires a lot of computational resources (GPUs) to train.
Anyhow, I'm exploring if would be possible to create a usable API where you could send a claim and a document and the API will tell the relation between those pieces (confirm, reject, no information). I think the algorithm won't work well with subtle issues (eg. the references is talking about the main topic of the item, but does not content the specific information about the claim), but could be able to catch if the document (reference) is completely unrelated.
I'll keep you updated.