| --- |
| license: apache-2.0 |
| task_categories: |
| - text-generation |
| language: |
| - tr |
| tags: |
| - e-commerce |
| - customer-support |
| - chain-of-thought |
| - instruction-tuning |
| pretty_name: TR E-Commerce Customer Support Instructions |
| size_categories: |
| - n<1K |
| --- |
| |
| # TR E-Commerce Customer Support Instructions 🇹🇷 |
|
|
| A high-quality **Turkish E-Commerce Customer Support** dataset designed for fine-tuning large language models (LLMs) on instruction-following customer support tasks. |
|
|
| ## Dataset Summary |
|
|
| | Feature | Value | |
| |---------|-------| |
| | **Language** | Turkish (tr) | |
| | **Domain** | E-Commerce Customer Support | |
| | **Format** | Conversation (Conversational/Chat) | |
| | **Chain-of-Thought (CoT)** | ✅ Natural paragraph reasoning (`thinking` field) | |
| | **Total Categories** | 20 | |
| | **Total Rows** | 186 conversations | |
|
|
| --- |
|
|
| ## Categories & Distribution |
|
|
| | # | Category | Description | Count | |
| |---|----------|-------------|-------| |
| | 1 | **Sipariş Oluşturma** | Cart errors, page load issues during checkout, guest checkout | 10 | |
| | 2 | **Sipariş İptali** | Order cancellation before/after shipping, partial cancellation | 10 | |
| | 3 | **Sipariş Takibi** | Status tracking, order processing delays, missing confirmation | 10 | |
| | 4 | **Kargo Gecikmesi** | Delivery delay, package stuck in transit, express delivery issues | 8 | |
| | 5 | **Teslimat Sorunlari** | Package marked delivered but not received, left with neighbor | 10 | |
| | 6 | **Eksik Ürün** | Missing items in order, missing accessories inside the box | 8 | |
| | 7 | **Yanlis Ürün** | Wrong color, size, or completely incorrect model delivered | 8 | |
| | 8 | **Hasarli Ürün** | Broken/cracked items, damaged packaging, used product received | 8 | |
| | 9 | **İade** | Return request, right of withdrawal, refund status, return shipping | 12 | |
| | 10 | **Değişim** | Size exchange, color exchange, product exchange process | 10 | |
| | 11 | **Ödeme** | 3D Secure failures, double charges, installments, bank transfer | 12 | |
| | 12 | **Kupon** | Coupon code errors, expired codes, minimum cart value rules | 8 | |
| | 13 | **Kampanya** | Discounts not applied, campaign rules, first-order discounts | 10 | |
| | 14 | **Hesap** | Login issues, account deletion (GDPR/KVKK), account hijacking | 10 | |
| | 15 | **Şifre** | Password reset steps, verification email not arriving | 8 | |
| | 16 | **Adres Değişikliği** | Changing address after shipment, updating registration address | 8 | |
| | 17 | **Fatura** | Invoice details correction, corporate invoice, PDF download | 8 | |
| | 18 | **Satıcı İletişimi** | Seller not responding, counterfeit suspicion, seller disputes | 10 | |
| | 19 | **Ürün Değerlendirmesi** | Product authenticity, stock query, size charts, descriptions | 10 | |
| | 20 | **Garanti** | Warranty period, warranty coverage, authorized service centers | 8 | |
|
|
| --- |
|
|
| ## Data Format |
|
|
| Each conversation is formatted as a list of message dictionaries featuring `role`, `content`, `images`, `thinking` (for the assistant), and `tool_calls` fields: |
|
|
| ```json |
| [ |
| { |
| "role": "user", |
| "content": "merhaba siparişim nerede kaldı acaba", |
| "images": null, |
| "thinking": null, |
| "tool_calls": null |
| }, |
| { |
| "role": "assistant", |
| "content": "Merhaba, hemen kontrol edelim. Siparişinizin durumunu sorgulayabilmem için e-posta adresinizi veya takip numaranızı paylaşabilir misiniz?", |
| "images": null, |
| "thinking": "Kullanıcı siparişinin nerede olduğunu merak ediyor. Muhtemelen kargoya verilmiş ama takip bilgisi güncellenmemiş olabilir. Kargo takip numarasıyla kontrol etmesini önermeli ya da sipariş bilgisini alıp ben kontrol etmeliyim.", |
| "tool_calls": null |
| } |
| ] |
| ``` |
|
|
| ### Dataset Key Design Features |
|
|
| 1. **Natural User Messages**: Users write in realistic, natural Turkish. Some messages contain missing punctuation or all-lowercase letters (mimicking actual human messaging habits), without using excessive chat slangs or abbreviations. |
| 2. **Diverse Assistant Openings**: Assistant responses use more than 10 different opening variations to avoid repetitive patterns in LLM fine-tuning. |
| 3. **Fluid Chain-of-Thought (CoT)**: Assistant entries include a single-paragraph `thinking` block containing the logical reasoning flow before producing the final response. |
| 4. **Varied Information Requests**: Unlike rigid datasets asking only for order numbers, the assistant requests different details depending on the scenario (e.g., e-mail, phone number, tracking ID, screenshot) or resolves the query directly without asking for any information. |
| 5. **Length Constraints**: Assistant responses are kept concise (ranging from 100 to 170 words) to mimic realistic customer support agent behaviors. |
|
|
| --- |
|
|
| ## Usage |
|
|
| You can easily load this dataset using the Hugging Face `datasets` library: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("Mer1Alii/TR-ECommerce-CustomerSupport-Instructions") |
| print(dataset["train"][0]) |
| ``` |
|
|
| --- |
|
|
| ## Fine-Tuning Tools |
|
|
| This dataset is compatible with popular training frameworks such as: |
| - [Unsloth](https://github.com/unslothai/unsloth) |
| - [Hugging Face TRL](https://github.com/huggingface/trl) |
| - [LLaMA Factory](https://github.com/hiyouga/LLaMA-Factory) |
| - [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) |
|
|
| ## License |
|
|
| This dataset is licensed under the Apache 2.0 License. It is intended for educational, research, and commercial applications. |
|
|
| ## Developer |
|
|
| **[Mert Ali Alkan](https://github.com/MertAlii)** |
|
|
