I'm Jeff, one of the founders of this+that. I've worked on named entity detection, fact extraction, knowledge management and NLP throughout my career, starting in the NLP stone age of the 1990s. I wanted to see whether a model could now write a useful wiki straight from a company's email.
Enron's mail is an obvious test because it's public, so anyone can check the pages against the messages and the history. We used 45,047 emails from eight mailboxes. Every fact quotes the sentence it came from, and a fact expires on the date the mail shows it stopped being true.
The hardest part was that the model already knows Enron. It kept adding details from the public record that the email didn't contain. The methodology page shows how we caught those, what it still gets wrong and what it cost: about $11,000 at list prices (though we used a subscription), with no attempt to bring that down.
Happy to answer questions.
Enron's mail is an obvious test because it's public, so anyone can check the pages against the messages and the history. We used 45,047 emails from eight mailboxes. Every fact quotes the sentence it came from, and a fact expires on the date the mail shows it stopped being true.
The hardest part was that the model already knows Enron. It kept adding details from the public record that the email didn't contain. The methodology page shows how we caught those, what it still gets wrong and what it cost: about $11,000 at list prices (though we used a subscription), with no attempt to bring that down.
Happy to answer questions.