Knowledge Graph and Bettings in Natural Language Processing

A knowledge graph is employed. When the agritm is done at the end of it, it will give you a vecto that for each entity and also for each relation in the knowledge graft. So just like the natural ae and bedding, where, you know, the traditional bord and beddings, you would have an ebedding for each word. And then once you in vecto space, then you can all kinds of cool things that cluster the vectos together or figure out when there's a relation between te two entities, riht, which are now represented as vecta. The nice thing obfout knowledge grafts is that