# Process Overview
The purpose of the Process system is to extract meta-data from the ingested material in a format useful for the next stage.

The Process pipeline performs the following steps for each input entity:
1. Normalization: translate all source material into the working language (English? Hebrew?)
2. Metadata: annotate each entity with relevant metadata, such as locations, dates/times, and actors.
3. Reconcilliation: map new entity to existing entities, creating or updating the canoncial entity graph.
4. RAG preparation: chunk the data, create embeddings, store in a vector data-base

# Objects

Canonical Entity:
    Type: Person
    Name: [list_of_names]
    References: [entities]

Metadata:
    [Date/time]
    [Location]
    [Person]

Entity:
    Type: Letter, Photograph
    Metadata
    Content: english_text
    Raw Content: original_text

# Technologies

## Evaluation criteria
Bellow is a prioritized list of the evaluation criteria. This is the most important part to align on before choosing the right tech. stack.

Normalization: translate between languages
Metadata: extract insights from text
RAG prep: chunking, embedding, vector-DB

## (A) Llama 3.2

URL: https://www.llama.com

Supports: multilingual translation, metadata extraction, embedding