Chained-Stars-Technology/heritage-data-parser

A high-performance text optimization and parsing engine for historical West African texts. # 🌍 Project Heritage-Data: Historical West African Text Parser A high-performance text optimization and parsing engine developed by **Chained Stars Technology**. This project automates the extraction, cleanup, and structuring of raw, public-domain historical African language texts (starting with the 1871 Twi and 1913 Ewe translations) into optimized database assets. ## 🚀 The Mission Modern digital language assets often simplify indigenous vocabulary. Chained Stars Technology is bridge-building between cultural preservation and modern data engineering. By rescuing 100+ year-old public domain texts from raw, flawed 1.1GB PDF/OCR scans, we are preserving deep cultural idioms, rare proverbs, and classical grammatical structures. We transform messy historical scans into production-ready, lightweight, and structured formats (SQLite/JSON) for modern mobile and web application ecosystems. ## 🛠️ Technical Challenges & Architecture Processing century-old West African prints involves unique data engineering hurdles: 1. **Specialized Extended Orthographies**: Handling distinct linguistic characters (`ɔ`, `ɛ`, `ɖ`, `ƒ`, `ʋ`) that generic OCR engines misinterpret or corrupt. 2. **Data De-noising**: Algorithmic parsing to strip out printing press artifacts, faded ink noise, and page-bleed text. 3. **Relational Structuring**: Tokenizing raw plain text blocks into clean, indexed relational tables mapping Books, Chapters, and Verses. ### Data Pipeline Flow [Raw Scanned Image/PDF] ➔ [Custom Tesseract OCR Pipeline] ➔ [Python Text Standardization Script] ➔ [Structured SQLite Database Asset] ## 📁 Repository Structure This public repository contains our foundational infrastructure, extraction tools, and schema layouts. ```text ├── config/ # Language mapping and character replacement configs ├── src/ │ ├── cleanup_engine.py # Python scripts for regex-based text standardization │ └── database_builder.py # SQLite schema initializer and population scripts ├─ …