Dataset Samples and Templates for: Automating Named Entity Recognition for Indonesian Diplomas via Template-Based Synthetic Data Generation

This repository contains the supplementary data, anonymized templates, and structural formatting for the manuscript titled "Automating Named Entity Recognition for Indonesian Diplomas via Template-Based Synthetic Data Generation", accepted for publication in Engineering, Technology & Applied Science Research (ETASR). 📌 Repository Objective The objective of this repository is to provide visibility into the data formats, label alignments (BIO/CoNLL tagging schemes), and structural layouts used in our NER training pipeline. This ensures methodological transparency while strictly adhering to Indonesian data privacy laws and protecting proprietary intellectual property. 📂 Repository Content Structure To verify the data formats and directory structures used in our experiments, this repository is strictly organized as follows: data/ : Contains alumni_dummy.csv (sample data for generation) and ijazah_dummy.png (sample image for OCR template extraction). dataset/ : Format samples of the final split datasets (Train/Valid/Test). model/ : Output directory placeholder for fine-tuned models. output/ : Intermediate output placeholder (e.g., full.json). diploma_templates/ : Extracted anonymized template files. requirements_prep.txt : Dependencies for Env Dataset Generation. requirements_model.txt : Dependencies for Env Model Training. README.md : Project documentation. ⚠️ Data Privacy and Code Availability Disclaimer Please note the following constraints as stated in the official manuscript's Data and Code Availability Statement: Proprietary Source Code: The core generation and training pipeline scripts (.ipynb / .py) are considered proprietary intellectual property. They are NOT included in this public repository. Confidential Real-World Data: To comply with the Indonesian Personal Data Protection Law (UU PDP No. 27 of 2022), the raw real-world diploma dataset remains strictly confidential to protect the privacy of the data subjects. 📧 Code Request & Contact The proprietary source code is available strictly for non-commercial research purposes upon reasonable request. To request access, please direct your inquiries to the Corresponding Author as explicitly listed in the final published version of the manuscript in the ETASR journal.