Regarding things being mentioned in one place but not others, I think this may have potential in other contexts. For example, something I've done off and on throughout the years is create a few thousand redirects about people's names. Sometimes people have middle names and it's pretty common for women to have different last names at birth vs when they got married. A list being created for community review to skip the most time lengthy part of finding these gaps might be useful.
On Mon, Oct 12, 2026, 11:08 a.m. Shani Evenstein Sigalov via Wikimedia-l < [email protected]> wrote: > Hello all, > > I'm happy to share the first open release from AI-BRIDGES > <https://ai-bridges.org>, funded by Wikimedia Switzerland > <https://meta.wikimedia.org/wiki/Wikimedia_CH/Grant_apply/AI-BRIDGES:_Synthetic_Reasoning_Corpus> > and delivered by Pleias <https://pleias.ai/>, with support from Wikimedia > Deutschland. > > We built a harness that lets a language model explore a frozen, > six-language Wikidata snapshot step by step, reading entities and citing > the statements it used, rather than stuffing large amounts of data into its > context, taking a Recursive Language Model approach. From it we generated a > Synthetic Reasoning Corpus of exploration traces, released under CC0. > > A few results from the technical report: > > - > > 74 of 100 questions answered correctly by Qwen3.8-27B, an open-weight > model on a single GPU, vs 61 for gpt-6-luna in the same harness > - > > 10,235 solving traces released under CC0, over single-entity and > multi-hop questions > - > > The harness lifts both models we ran under both interfaces, with the > gain mostly on multi-hop questions > > Of particular interest to editors: exploration surfaced cross-language > inconsistencies and misplaced information (for example, nationality > appearing in descriptions but not in statements). Nothing was edited > automatically; the findings are in the report for community review. > > - > > Harness, code and benchmark (GitHub): > https://github.com/aibridges/RLM_Wikidata > > > - > > Corpus (Hugging Face): > https://huggingface.co/datasets/AI-BRIDGES/wikidata-search-traces > - > > Technical report: > https://arxiv.org/abs/2610.06650 > > > Next, we plan to train open Wikidata search models on this corpus and we > would appreciate your help: if you work with GLAMs, Education, Research, > especially in the Humanities, please send us real questions you'd want to > ask Wikidata in plain language or in SPARQL > <https://docs.google.com/document/d/1ipIzwSwf-xCtU7R7ewNCCND7vk0yha6byWMNs3OyIEc/edit?tab=t.0>, > or via email: [email protected]. > > I'd like to take a moment to thank not just Pleias, WMCH & WMDE, but also > our other core partners, WMUK & WM Brasil, as well as other partners -- > organizations, institutions and so many wonderful individuals from this > community -- for being part of the AI-BRIDGES journey and supporting it. > > Feedback, questions and critique are all very welcome on-list, on wiki > <https://meta.wikimedia.org/wiki/Research:AI-BRIDGES> or privately. > > All best wishes, Shani. > > > ----------------------- > Dr. Shani Evenstein Sigalov > Marie Curie Postdoctoral Research Fellow & AI-BRIDGES > <https://ai-bridges.org/> lead > Digital Humanities Research Hub, School of Advanced Study, University of > London. > _______________________________________________ > Wikimedia-l mailing list -- [email protected], guidelines > at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and > https://meta.wikimedia.org/wiki/Wikimedia-l > Public archives at > https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/54MO3NDOYVUGV5D4G2AW3VZ2TZJ52IZR/ > To unsubscribe send an email to [email protected]
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