Why?

Human annotated datasets play a critical role in training language models. But sourcing them is considered expensive and time-consuming. The irony is that researchers invariably create such annotations for themselves, without being aware of their value. 

Imagine a dapp where you could (a) own each annotation that you made on a public document, (b) encrypt and preserve it as a private asset or deposit it in a common pool for rewards, (c) collect public assets shared by others, (e) combine owned and  collected assets into private curations.

Hyvmind is being created for and by legal researchers. It is designed to serve as an ontologically plural library of domain-subgraphs.