abstracthinking

Yes, I will add worldwide membership in the future. Wikidata coverage is lower for Asian and African countries, but I believe it will show interesting connections. Right now only most prominent figures appear. It takes some time to elaborate data, and I had limited resources, that is why I decided to exclude certain countries.

Built this due to my passion to explore the connections between known people and organizations, for now data includes entities from EU, USA and CA, some important entities from other countries appear due to having multiple connection to stored entities. Look people and organizations leaderboard, and navigate whoever you are interested into. Best for desktop usage. Tech stach used: ArangoDB, Backend API Python with FastAPI, Frontend Vue 3 + Vite, Cytoscape.js, Redis. Data source: Wikidata, Wikimedia, SEC

They have just released it, give it some time, they probably haven't pretested it with Pi

Built this due to my passion to explore the connections between known people and organizations, now data includes entities from EU, USA and CA. There is also a Trivia game section that i built to know/explore new persons and discover facts. Tech stach used: - ArangoDB because its native for graph traversal, great for storing Wikidata format style - Backend API Python with FastAPI, well known and stable library - Frontend Vue 3 + Vite, fast and stable enough - Cytoscape.js, for graph visualization, traversal and animations - Redis for caching frequent people requests and game rounds Wikidata and Wikimedia commons as data source. Hope you find entertaining and fast exploring the graph, investigate button to look people's awards, career, organization info and SEC information(there is a report button in about section). The website seems interesting to me, but i'm looking to expand the types of connections shown.

Your comment doesn't make any sense, opus 4.6 was release two months ago, what jump would you expect?

I don't see the value in this post, are hacker news post being upvoted by bots?

Each european countries has various orgs, types of license. It is easier to start from SEC to integrate that data into my site, also you have to test a bit what users care about.

Humans will be held accountable, not machines, whatever is the technology used. The jobs you suggest are based on the state of LLM right now, this could change rapidly, considering the state of progress. These are just activities that are already done by people that work with these instruments, because they want to optimize and obtain the best/safest output from these machines.

I agree with you, site also looks too much a one day vibecoded stuff. Can you give me references where I can these graphs of people, I am interested because I am working on something similar.

Look now that the site loads, is it a bit sketchy that you are asking 50 dollars subscription, one can't even navigate the site a bit without subscribing. You don't even have a working and tested product and already want to make money.

I worked on a knowledge graph map using Wikidata to get relationship between people and organizations, but data was limited to family, basic stuff. Being from Europe, there isn't an open data analogue of SEC. Now I will download this data, it is open so no license at all, and try to show these kind of relationships. It has the potential of being very investigative, especially for USA residents.

Interesting, you should save part of the data to do some caching and avoid api requests for old positions.

Built this due to my passion to explore the connections between known people and organizations, for now data includes entities from EU, USA and CA, some important entities from other countries appear due to having multiple connection to stored ones. Look people and organizations leaderboard, and navigate whoever you are interested into. Trivia game section that i built to know/explore new persons and discover facts. Best for desktop use. Tech stach used: - ArangoDB because its native for graph traversal, great for storing Wikidata format style - Backend API Python with FastAPI, well known and stable library - Frontend Vue 3 + Vite, fast and stable enough. - Cytoscape.js, for graph visualization, traversal and animations. - Redis for caching frequent people requests and game rounds. - Wikidata and Wikimedia commons are used as data source. Hope you find entertaining and fast exploring the graph, let me know if you have features, improvements or find bugs (there is also a report button in site "about" section).

Article is paywalled, for sure there isn't world access knowledge to this piece :)