Oh Cthulhu, this is like a periscope into a septic tank...
Yes almost no one has been held accountable for any of it, "weird"?
A graph explorer of the Epstein emails
41–50 of 172 posts
Re: A graph explorer of the Epstein emails
#42This is the best rendition I've seen so far. The Bill Clinton entity is interesting. > 2009: Bill Clinton discontinued association with Jeffrey Epstein > 2010: Jeffrey Epstein provided flights on jets to Bill Clinton > 2010-2011: Jeffrey Epstein traveled via private aircraft with Bill Clinton > 2011: Ghislaine Maxwell piloted helicopter for Bill Clinton > 2014: Bill Clinton alleged presence at sex parties > 2015: Bil…
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Seems to get away with it all, meanwhile, we all pay our taxes, don't break any laws and just be "good people".
Re: A graph explorer of the Epstein emails
#43What if we extended this idea beyond one dataset to all discrete news events and entities: people, organizations, places. Just like here you could get a timeline of key events, a graph of connected entities, links to original documents. Newsrooms might already do this internally idk. This code might work as a foundation. I love that it's RDF.
Sci-Fi Author: In my book I invented the Torment Nexus as a cautionary tale
Tech Company: At long last, we have created the Torment Nexus from classic sci-fi novel Don't Create The Torment Nexus
Re: A graph explorer of the Epstein emails
#44"Brad Edwards" and "Bradley Edwards" might be the same individual.
great use case for using AI to suggest mergers and clean up.
LLMs are awful for this. I've got a project that's doing structured extraction and half the work is deduplication.
I didn't go down the route of LLMs for the clean up, as you're getting into scale and context issues with larger datasets.
I got into semantic similarity networks for this use case. You can do efficient pairwise matching with Annoy, set a cutoff threshold, and your isolated subgraphs are merger candidates.
I wrapped up my code in a little library if you're into this sort of thing.
github.com/specialprocedures/semnet
Re: A graph explorer of the Epstein emails
#45What if we extended this idea beyond one dataset to all discrete news events and entities: people, organizations, places. Just like here you could get a timeline of key events, a graph of connected entities, links to original documents. Newsrooms might already do this internally idk. This code might work as a foundation. I love that it's RDF.
One wonders what the US government agencies use.
Internet search engines have their origins in government projects fwiw. They had search engines before Alta Vista, used for searching data sets that pre-date the internet, and some of the people involved in those went to work on the original commercial search engines.
Re: A graph explorer of the Epstein emails
#46Re: A graph explorer of the Epstein emails
#47What if we extended this idea beyond one dataset to all discrete news events and entities: people, organizations, places. Just like here you could get a timeline of key events, a graph of connected entities, links to original documents. Newsrooms might already do this internally idk. This code might work as a foundation. I love that it's RDF.
One co trying: https://www.system.com
Re: A graph explorer of the Epstein emails
#48[deleted]
Re: A graph explorer of the Epstein emails
#49What if we extended this idea beyond one dataset to all discrete news events and entities: people, organizations, places. Just like here you could get a timeline of key events, a graph of connected entities, links to original documents. Newsrooms might already do this internally idk. This code might work as a foundation. I love that it's RDF.
This has been attempted many times. They all fail the same way.
These general data models start to become useful and interesting at around a trillion edges, give or take an order of magnitude. A mature graph model would be at least a few orders of magnitude larger, even if you aggressively curated what went into it. This is a simple consequence of the cardinality of the different kinds of entities that are included in most useful models.
No system described in open source can get anywhere close to even the base case of a trillion edges. They will suffer serious scaling and performance issues long before they get to that point. It is a famously non-trivial computer science problem and much of the serious R&D was not done in public historically.
This is why you only see toy or narrowly focused graph data models instead of a giant graph of All The Things. It would be cool to have something like this but that entails some hardcore deep tech R&D.
Re: A graph explorer of the Epstein emails
#50What if we extended this idea beyond one dataset to all discrete news events and entities: people, organizations, places. Just like here you could get a timeline of key events, a graph of connected entities, links to original documents. Newsrooms might already do this internally idk. This code might work as a foundation. I love that it's RDF.
This has been attempted many times. They all fail the same way. These general data models start to become useful and interesting at around a trillion edges, give or take an order of magnitude. A mature graph model would be at least a few orders of magnitude larger, even if you aggressively curated what went into it. This is a simple consequence of the cardinality of the different kinds of entities that are included i…
I don't have any experience on graph modeling, but it seems like Neo4j should be able to support 1 trillion edges, based on this (admittedly marketing) post of theirs? https://neo4j.com/press-releases/neo4j-scales-trillion-plus-...