Fine-tuned NER model to extract product names, prices, and locations from Amharic Telegram e-commerce messages, using XLM-Roberta and BERT models. Features real-time data extraction and model interpretability with SHAP and LIME.
# Telegram-ECommerce-NER
## Overview
This project aims to develop a Named Entity Recognition (NER) system for EthioMart, a centralized e-commerce platform in Ethiopia. The system will extract key business entities such as product names, prices, and locations from Amharic text, images, and documents shared across multiple Telegram channels.
## Business Need
EthioMart's vision is to become the primary hub for all Telegram-based e-commerce activities in Ethiopia. By consolidating real-time data from multiple e-commerce Telegram channels, EthioMart aims to provide a seamless experience for customers to explore and interact with multiple vendors in one place.
## Key Objectives
1. Real-time data extraction from Telegram channels
2. Fine-tuning Large Language Models (LLMs) for Amharic Named Entity Recognition
3. Extraction of entities such as Product names, Prices, and Locations
## Project Structure
The project is divided into the following main tasks:
1. Data Ingestion and Preprocessing
2. Data Labeling in CoNLL Format
3. Fine-tuning NER Models
4. Model Comparison and Selection
5. Model Interpretability
## Folder Structure
```plaintext
Telegram-ECommerce-NER/
├── .vscode/
│ └── settings.json
├── .github/
│ └── workflows/
│ └── unittests.yml # GitHub Actions
├── .gitignore # files and folders to be ignored by git
├── requirements.txt # contains dependencies for the project
├── README.md # Documentation for the projects
├── src/
│ └── __init__.py
├── notebooks/
│ ├── __init__.py
| |──preprocessing_analysis.ipynb # Jupyter notebook for amharic data processing
| |──ner_labelling.ipynb # Jupyter notebook to label amharic tokens in conll format
| |──ner_finetuning.ipynb # Jupyter notebook to fine-tune a Named Entity Recognition (NER) model
| |──model_comparison.ipynb # Jupyter notebook to compares different models for Named Entity Recognition (NER)
| |──qenashcom_sin …