# Amharic-NER-for-Telegram-E-commerce-Messages
## Project Overview
Amharic-NER-for-Telegram-E-commerce-Messages centralizes e-commerce activities from various Ethiopian-based Telegram channels, enabling real-time data extraction to create a unified platform. This project focuses on:
- Extracting real-time data (text, images, documents) from Telegram channels such as `@ZemenExpress`.
- Fine-tuning a large language model (LLM) for Amharic Named Entity Recognition (NER).
- Identifying key entities such as products, prices, and locations in Amharic text.
This repository contains code for data ingestion, preprocessing, and labeling for NER tasks, supporting EthioMart’s vision of a seamless e-commerce platform.
## Features
### Real-Time Data Ingestion
- A custom scraper connects to Telegram channels and fetches messages, images, and metadata.
### Text Preprocessing
- Includes tokenization, normalization, and handling Amharic-specific linguistic features.
### NER Labeling
- Annotates text data for NER tasks in the CoNLL format, labeling:
- **Products**: `B-Product`, `I-Product`
- **Prices**: `B-PRICE`, `I-PRICE`
- **Locations**: `B-LOC`, `I-LOC`
## Requirements
Install the required libraries using the following command:
```bash
pip install -r requirements.txt