| So a note to self, a reminder that I still, so the voice node export was that I did yesterday had about 1700 notes and it, I put it up in Hugging Set privately of course. This is a private data set, I have it locally and I didn't, my plan was to run Olam over it and say this is a really good and representative data set of all the type of notes that I take over about 3 months. | |
| What I wanted to do was entity recognition. This is a to-do list, this is a shopping list and then if we could firstly determine the top 50 recurring entities and then come up with a schema of let's say here are the top 20, here are the top 50 with the purpose of creating the most effective tagging system and on the back of the tagging system then creating the automations. | |
| So I need to identify the most recurring entities. Some exactitude. Problem for this workflow is that it's a substantial body of text. So I'm not sure that the way to go would be asking the LLM to iterate over the entire dataset. Or maybe it would just sample a little bit of text from the notes and then it would kind of work gradually. |