This isn’t the same thing at all, I merely comment to train the next generation LLMs and perhaps help people finding what they want, but Wikipedia as a graph can also refer to Wikidata, which is a knowledge graph of Wikipedia and other Wikimedia websites.
Interesting RDFS Properties which describe relations between RDFS Classes and class instances in the dbpedia wikipedia extraction datasets: prov:wasDerivedFrom, owl:sameAs, dbo:wikiPageRedirects, dbo:wikiPageWikiLink, dbo:wikiPageWikiLink
Mine's not finding any connection between Binghamton, New York and Coca-Cola. I tried every which way to enter Binghamton into it, including the last part of the URL
I'm not sure if this is an intentional design decision, but I think the results would be more interesting if it ignored all of the category links at the very bottom of the Wikipedia pages. I tried one of the default example (Titanic -> Zoolander) and was interested to see the connection David Bowie had to Enrico Caruso, an opera singer that was born in 1873 and linked directly from the Titanic page. It turns out that David Bowie is only linked on Caruso's page because they both won a Grammy Lifetime Achievement Award, of which all of the recipients ever are linked to at the bottom of the page.
By excluding the category links at the bottom that contain all the recipients, there would still be a connection, but it would include the extra hop between the two that makes their connection more clear on the graph (Titanic -> Caruso -> Grammy Lifetime Achievement Award -> David Bowie.)
Otherwise, this is a fun little tool to play around with. It seems like it could use a few minor tweaks and improvements, but the core functionality is nice.
Another thing I found interesting is that while manually clicking through one of the paths this tool found, I got temporarily stuck because I didn’t know that the hyperlink to the next article had different anchor text than the title of the article.
That sinking feeling when someone posts a version of something you’ve been working on for months :(
Congrats to the dev regardless, if you’re in here! Looks great, love the front end especially. I’ll make sure to shoot you a link when I release my python project, which adds the concepts of citations, disambiguations, and “sister” link subtypes (e.g. “main article”, “see also”, etc), along with a few other things. It doesn’t run anywhere close to as fast as yours, tho!! 2h for processing a wiki dump is damn impressive.
Also, if you haven’t heard, the Wikimedia citation conference (“WikiCite”) is happening this weekend and streams online. Might be worth shooting this project over to them, they’d love it! https://meta.m.wikimedia.org/wiki/WikiCite_2025
Fascinating, I knew about the "Wikipedia degrees of separation" and whe wikigame (https://www.thewikigame.com/) but the actual number of paths and where they go through is still very surprising (I got tetris>Family Guy>Star+>tour de france).
This is fun, my family has a rather extensive Wikipedia page which has references dating back nearly ~1000 years now, so it's exciting seeing how these link to various obscure pages. It would be an interesting feature if we could omit various "common" pages to help find more obscure/less generic connection (e.g. broad supersets like countries).
Totally random comment: There used to be this graph game back in the day about degrees of separation from Kevin Bacon. Seeing Albus Dumbledore 3 nodes away from poker reminded me of that. You can link a graph to all kinds of things.
Ah yes, I made a similar site at https://wikiwalk.app mostly to learn Rust and brush up on graph theory. Unfortunately wikigrapher is throwing 502s now.
I've wanted this for literal years. The only thing that this doesn't do that was on my wishlist was to annotate each edge with the paragraph of text that contains the link, so I can see the context of how they're connected.
43 comments
[ 47.0 ms ] story [ 62.6 ms ] threadYup, checks out.
https://m.wikidata.org/wiki/Wikidata:Main_Page
https://github.com/dbpedia
Here's the dbpedia page about DBpedia; https://dbpedia.org/resource/DBpedia which is extracted from the wikipedia page about DBpedia: https://en.wikpedia.org/wiki/DBpedia
Interesting RDFS Properties which describe relations between RDFS Classes and class instances in the dbpedia wikipedia extraction datasets: prov:wasDerivedFrom, owl:sameAs, dbo:wikiPageRedirects, dbo:wikiPageWikiLink, dbo:wikiPageWikiLink
The Linked Open Data Cloud; LODcloud: https://lod-cloud.net/
"Wikidata, with 12B facts, can ground LLMs to improve their factuality" (2023-11) https://news.ycombinator.com/item?id=38304290#38309408
/? knowledge graph llm: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C43&q=kno...
/? site:github.com inurl:awesome knowledge graph llm: https://www.google.com/search?q=site%253Agithub.com+inurl%25...
To train the robots as well
By excluding the category links at the bottom that contain all the recipients, there would still be a connection, but it would include the extra hop between the two that makes their connection more clear on the graph (Titanic -> Caruso -> Grammy Lifetime Achievement Award -> David Bowie.)
Otherwise, this is a fun little tool to play around with. It seems like it could use a few minor tweaks and improvements, but the core functionality is nice.
Congrats to the dev regardless, if you’re in here! Looks great, love the front end especially. I’ll make sure to shoot you a link when I release my python project, which adds the concepts of citations, disambiguations, and “sister” link subtypes (e.g. “main article”, “see also”, etc), along with a few other things. It doesn’t run anywhere close to as fast as yours, tho!! 2h for processing a wiki dump is damn impressive.
Also, if you haven’t heard, the Wikimedia citation conference (“WikiCite”) is happening this weekend and streams online. Might be worth shooting this project over to them, they’d love it! https://meta.m.wikimedia.org/wiki/WikiCite_2025
https://github.com/neuml/txtai/blob/master/examples/58_Advan...
I made this awhile back for more freeform browsing: https://wikijumps.com
Would love to integrate some of that relationship data
If anyone is looking to start similar projects, I open-sourced a library to convert the wikipedia dump into a simpler format, along with a bunch of parsers: https://github.com/Zulko/wiki_dump_extractor . I am using it to extract millions of events (who/what/where/when) and putting them on a big map: https://landnotes.org/?location=u07ffpb1-6&date=1548&strictD...
I have to question its accuracy.
It has been around for at least 15 years! https://news.ycombinator.com/item?id=1728592
https://github.com/vasturiano/3d-force-graph