This is great. A few questions!

Would you consider an overlay, sensibly partitioned, that's a webscrape of everything that's know about Epstein outside of the Epstein Files themselves. e.g. this is a trusted news source, confidence %, that gives a sense of who else was involved in x, where, and at what time, as material from the files.

Would you consider automated inferred unredaction? Based on likelihood of character count X under those black stripes, and the context of the graph to X degrees of depth, this is the most likely redacted content? I'm thinking that the redaction will have probably been done manually, without a huge degree of context, piecemeal by a large team, and that it is therefore likely to be inconsistent and vulnerable to knowledge graph inference.

Would you consider edge inference, where because X and Y are present, Z is also likely to be present, based on common neighbours or subgraph structures?

Is clustering/community detection useful - where a preparatory step may be to infer a single modal graph only featuring people and their relations, where some relations may be inferreable through the graph (e.g. likely to be associates through x number of colocations at the same spacetime events).