Yaron Koren gave a great presentation ([https://commons.wikimedia.org/wiki/File:Fixing_Wikidata_-_SMWCon_2023.pdf slides]) called '''[http://wikiworks.com/enhanced-wikibase.html Enhanced Wikibase]''' on how [[Wikibase]] (and therefore Wikidata) are missing features. He showed how he implemented these missing features in a series of developments. One is showcased at [https://wikidatawalkabout.org/ Wikidata Walkabout] - a drill-down and query interface to Wikibase sites; powered by [https://github.com/sahajsk21/Anvesha Anvesha] - a JavaScript library. [https://www.youtube.com/live/lYpi08dqBPs?si=ci0swXD2e-e7qCwy&t=19983 Video presentation]
===Natural Language Queries to Wikidata: A Naive Naïve Prototype===
[[File:Architecture - Ask Wikidata SMWCon 2023.png|alt=Application architecture|thumb|architecture]] Robert Timms - Sr. Software Engineer Wikibase Suite, Wikimedia Deutschland gave [https://www.semantic-mediawiki.org/wiki/SMWCon_Fall_2023/Natural_Language_Queries_to_Wikidata:_A_Na%C3%AFve_Prototype a talk] ([https://github.com/rti/askwikidata code] [https://docs.google.com/presentation/d/1YgDmcvoXaqnYdRyX5RxewVkeioEJ92nb8Sfb_halBsM slides] [https://colab.research.google.com/drive/1yRZshpNj0kXwY0XuUYw5ziqjw_RffxH- try it]) about querying Wikibase with an LLM. Slides 9-22 go from the application architecture to the 'tada' moment.
{{Notice|The 'gpt' in ChatGPT stands for "Generative Pre-trained Transformer" - or a fancy way to say "guess". The '''artificial''' intelligence of large language model GPTs '''guess''' what you would say next based on the prompt given and the dataset they are trained on. In OpenAI's own words: "Generative AI models formulate responses by matching patterns or words, while RAG systems retrieve data based on similarity of meaning or semantic searches."}}
=== Major changes on interfaces of MediaWiki RDBMS library ===
https://www.mediawiki.org/wiki/Manual:Database_access
[[Category:MediaWiki]]
[[Category:Enterprise MediaWiki]]
