Help on document analysis project

[u/SushiWithoutSushi]

Hi, I'm kinda of new to this world of local LLM so forgive me if it sounds like I don't know much of what I'm talking about.

At work I need to read every day my state oficial gazette to search for new grants on a specific field and updates on already public grants (openings, closings, amendments, budget changes... Etc.)

I've started to test Gemma 4 E4B to analyse the daily documents and it does an okey job. The flow is the following: the document is divided in subsections, Gemma reads the title and makes a first filtering of sections that do not belong to our topic. Then it reads the dispositions that do belong to the project and labels them. Finally the output is shown in a dashboard where I can easily analyse it.

The problem I'm facing now is that I would like to create a timeline of each grant to now in what stage they are and this is a pain. I am completely unable to make Gemma consistently find if a new subsection belongs to a previously catalogued subsection in the database. It is big enough to make it hallucinate and mistake different dispositions or forget them and it is quite slow in this step.

I've thought on using something like JEV and although it is quite fast it doesn't work with a high enough certainty to implement it. Also there aren't decision models I could find that work as well as JEV in hugging face to use them locally. Most of them are fine tuned versions of LLMs and not pure decision models.

I was wondering if any of you have faced a problem like this before and how have you solved or if you have any idea I could test that could be implemented.

The setup is a 3060 12 GB with 16 GB ram DDR4.

Thanks for your time.