=== Fixing Wikidata ===
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.
=== Natural Language Queries to Wikidata: A Naive Prototype ===
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. Not the goal of the talk, but he revealed some of the key drawbacks of using "AI" in the first place:
# Outdated information
# Prone to hallucinations
# No sources (AI doesn't tell you how or why it claims to be authoritative.)
This is supposed to be addressed in part by using the <abbr title="Retrieval-Augmented Generation">RAG</abbr> technique.
{{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."}}
[[Category:MediaWiki]]
[[Category:Enterprise MediaWiki]]
