Update README.md

README.md

@@ -1,33 +1,37 @@
 ---
-pretty_name: EPDK Electricity Market Legislation Dataset
+pretty_name: EPDK Corpus (v2)
 tags:
 - turkish
 - energy-market
 - legislation
 - regulations
 - epdk
-- text-extraction
 - ocr
+- qwen-vl
+- text-extraction
 - domain-specific
 - language-modeling
 - legal
 dataset_info:
   features:
-  - name: source_file
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: kind
     dtype: string
-  - name: extracted_text
+  - name: method
     dtype: string
   splits:
   - name: train
-    num_bytes: 142398992
-    num_examples: 3424
-  download_size: 70357154
-  dataset_size: 142398992
+    num_examples: 3577
+  download_size: 72000000
+  dataset_size: 145000000
 configs:
-- config_name: default
+- config_name: v2
   data_files:
   - split: train
-    path: data/train-*
+    path: v2/final_corpus_dataset.jsonl
 language:
 - tr
 license: apache-2.0
@@ -35,46 +39,94 @@ task_categories:
 - text-generation
 size_categories:
 - 1K<n<10K
+version: 2.0.0
 ---
-
-# Dataset Card for EPDK Electricity Market Legislation Dataset
+# Dataset Card for **EPDK Electricity Market Corpus (v2)**
 
 ## Dataset Summary
+This corpus contains high-quality Turkish text extracted from **documents published by the Turkish Energy Market Regulatory Authority (EPDK – Enerji Piyasası Düzenleme Kurumu)**.  
+The source materials include regulations, board decisions, and official communiqués related to the **electricity market legislation**.
 
-This dataset contains cleaned Turkish text extracted from approximately 3,300 documents related to the Turkish Energy Market Regulatory Authority (EPDK - Enerji Piyasası Düzenleme Kurumu) and the Turkish electricity market legislation. The original documents were in various formats (PDF, DOCX, DOC, XLSX), including scanned documents that required Optical Character Recognition (OCR).
+Version 2.0.0 introduces a **complete re-extraction of the text using the Qwen-2.5-VL vision-language model**, which achieves dramatically better OCR accuracy than Tesseract—particularly on scanned and complex multi-column PDFs.  
+The result is a significantly cleaner and more semantically faithful representation of the original legal texts.
 
-The primary purpose of creating this dataset was to facilitate domain adaptation for Large Language Models (LLMs), enabling them to better understand and process texts specific to the Turkish energy regulation domain.
+---
 
-This version of the dataset contains the **cleaned but unchunked** text. Each entry corresponds to one processed source document.
+## Version History
 
-## Supported Tasks and Leaderboards
+| Version | Description | Date | Notes |
+|----------|--------------|------|-------|
+| **v1.0.0** | Initial release using Tesseract OCR (≈ 3.4 K docs) | 2025-04 | Baseline version. Stored under `/v1/`. |
+| **v2.0.0** | Re-extracted with Qwen-2.5-VL OCR (≈ 3.6 K docs), normalized fields (`id`, `text`, `kind`, `method`) | 2025-10 | Recommended for downstream use. |
 
-This dataset is primarily intended for **language modeling** tasks, specifically **domain adaptation** via continued pre-training or fine-tuning of causal language models. It could potentially serve as a base for downstream tasks like:
+To load a specific version:
 
-* Question Answering over EPDK regulations
-* Summarization of legal/regulatory documents
-* Text Classification (e.g., document type)
+```python
+from datasets import load_dataset
+ds = load_dataset("ogulcanakca/epdk_elektrik_piyasasi_mevzuat", revision="v2.0.0")
+```
 
-There are no official leaderboards associated with this dataset at this time.
+---
+
+## Intended Uses
+
+Designed primarily for **language-model domain adaptation** and **continued pre-training** on Turkish regulatory language.
+Potential downstream tasks include:
+
+* Legal Question Answering over EPDK documents
+* Summarization of laws and regulations
+* Document classification or clustering (e.g., tebliğ / karar / yönetmelik)
+* Information retrieval and RAG training for energy-sector LLMs
+
+---
 
 ## Languages
 
-The text in the dataset is exclusively in **Turkish (tr)**.
+All text is in **Turkish (`tr`)**.
+
+---
 
-## Data Instances
+## Data Fields
 
-The dataset is provided in JSON Lines (`.jsonl`) format. Each line represents a single processed document and is a JSON object. A typical instance looks like this:
+| Field    | Type   | Description                                                      |
+| -------- | ------ | ---------------------------------------------------------------- |
+| `id`     | string | Unique SHA-1-based identifier for the document                   |
+| `text`   | string | Cleaned text extracted from the source file                      |
+| `kind`   | string | File type (`docx`, `pdf`, `xls`, etc.)                           |
+| `method` | string | Extraction method (`python-docx`, `pandas`, `qwen-vl-ocr`, etc.) |
+
+---
+
+## Example Instance
 
 ```json
-{"source_file": "doc_files_converted_to_docx\\_PortalAdmin_Uploads_Content_FastAccess_Sayaclar565d9c06.docx", "extracted_text": "22/4/2011 tarihli ve 27913 sayılı Resmi Gazetede yayımlanmıştır.\nEnerji Piyasası Düzenleme Kurumundan\nElektrik Piyasasında Kullanılacak Sayaçlar Hakkında Tebliğde Değişiklik Yapılmasına İlişkin Tebliğ\nMADDE 1- 22/03/2003 tarihli ve 25056 sayılı Resmi Gazete'de yayımlanan Elektrik Piyasasında Kullanılacak Sayaçlar Hakkında Tebliğin geçici 4 üncü maddesi birinci fıkra (f) bendi aşağıdaki şekilde değiştirilmiş, (g) bendine “Dağıtım sistemine yüksek gerilim seviyesinden bağlı” ifadesinden sonra gelmek üzere “ve trafo gücü 630 kVA ve üzerinde olan” ibaresi eklenmiştir.\n“f) İletim sistemine bağlı serbest tüketicilerin ölçüm noktaları, tüketici tesislerindeki indirici trafonun giriş tarafında yer alır.”\nYürürlük\nMADDE 2- Bu Tebliğ yayımı tarihinde yürürlüğe girer.\nYürütme\nMADDE 3- Bu Tebliğ hükümlerini Enerji Piyasası Düzenleme Kurumu Başkanı yürütür."}
-```
+{
+  "id": "b3f7a6d9c49e",
+  "text": "Enerji Piyasası Düzenleme Kurumundan:\nKURUL KARARI\nKarar No: 9284 Karar Tarihi: 02/04/2020\n...",
+  "kind": "docx",
+  "method": "python-docx"
+}
 ```
-@dataset{ogulcanakca_epdk_mevzuat,
-  author    = {ogulcanakca},
-  title     = {EPDK Electricity Market Legislation Dataset},
+
+---
+
+## Data Structure & Access
+
+* Format: `JSONL` (one document per line)
+* Total examples: ≈ 3 577
+* Dataset path: `v2/final_corpus_dataset.jsonl`
+
+---
+
+```bibtex
+@dataset{ogulcanakca_epdk_corpus_v2,
+  author    = {Oğulcan Akca},
+  title     = {EPDK Corpus (v2)},
   year      = {2025},
-  url       = {[https://huggingface.co/datasets/ogulcanakca/epdk_elektrik_piyasasi_mevzuat](https://huggingface.co/datasets/ogulcanakca/epdk_elektrik_piyasasi_mevzuat)}
+  url       = {https://huggingface.co/datasets/ogulcanakca/epdk_elektrik_piyasasi_mevzuat}
 }
 ```
 
-Contact: akca_ogulcan@hotmail.com
+---
+
+[akca_ogulcan@hotmail.com](mailto:akca_ogulcan@hotmail.com)