Amharic E-commerce Named Entity Recognition (NER) This project focuses on building a Named Entity Recognition (NER) model tailored for Amharic-language e-commerce data. It aims to identify and extract key entities such as product names, brands, prices, quantities, vendor names, and locations from unstructured Amharic text.
# Amharic E-Commerce Named Entity Recognition
A production-ready NLP system that extracts products, prices, and locations from Amharic Telegram posts to power vendor financing decisions.
## Features
- **Amharic NER Model**: Fine-tuned BERT model for Ethiopian e-commerce text
- **Vendor Scoring**: Automated lending score calculation
- **Web Interface**: Streamlit dashboard for easy interaction
- **API Ready**: Can be deployed as a microservice
## Installation
```bash
git clone
github.com
cd amharic-ecommerce-ner
pip install -r requirements.txt
Usage
1. Training the Model
- python src/ner_pipeline.py
2.
Here's your enhanced **professional README.md** with all requested additions, formatted for optimal GitHub presentation:
```markdown
# Amharic E-Commerce Named Entity Recognition (NER)
A production-grade NER system for Amharic e-commerce messages, with full pipeline from data collection to interpretable predictions.
## π Key Features
- **Telegram Scraper** for Amharic e-commerce chats
- **Custom BERT Tokenizer** for Amharic script
- **SHAP/LIME Integration** for model explainability
- **Vendor Analytics Dashboard** (see `src/vendor_analytics.py`)
## π Project Overview
**Domain**: Ethiopian e-commerce message parsing
**Input**: Amharic Telegram messages
**Output**: Structured entity extraction:
| Entity | Examples (Amharic) | Examples (Transliterated) |
|-----------|--------------------------|---------------------------|
| VENDOR | α¨α±α α±α
, οΏ½α
α α»α α€α΅ | Yusuf Shop, Hilal Tea House |
| PRODUCT | οΏ½αα α α
, α½αα | Wine, Traditional Cloth |
| PRICE | 250 α₯α, 15 αΆαα | 250 Birr, 15 USD |
| LOCATION | αα΅αα οΏ½α
α³α΄, α°α α αα΄α | Meskel Hidase, Saber Hotel |
## π Repository Structure
```
amharic-ecommerce-ner/
βββ data/ # Dataset directories
β βββ raw/telegram_messages.csv # Scraped messages
β βββ labeled/ner_labeled_data.conll # 12,000 annotated sen β¦