Wiki_Greek_Personalities Dataset

Developed by NCSR-D, this dedicated dataset focuses on expanding LLM knowledge regarding Greek public figures, enhancing domain knowledge, and providing accurate biographical data on prominent Greek personalities. The dataset systematically transforms unstructured biographical data derived from a recent dump of the Greek Wikipedia into highly structured training examples. The full dataset contains 142,200 Question-Answering (QA) pairs for 16,075 Greek public figures, while the subset contains 1,650 QA pairs for 170 Greek public figures.

Dataset Structure

The dataset is provided in a standard JSON format containing a list of objects. Each object represents a single QA context entry:

Schema Overview

Both configurations share an identical schema containing the following fields:

• title (string): Target subject's identity name.
• full_text (string): The cleaned reference source text snippet from Greek Wikipedia.
• question (string): Natural language prompt querying essential biographical facts.
• answer (string): The validated accurate response text.

Data Instance Example

{
  "title": "Person",
  "full_text": "Ο Person είναι Έλληνας πολιτικός ...",
  "question": "Πότε και πού γεννήθηκε ο Person;",
  "answer": "Ο Person γεννήθηκε στις Date στον Location."
}

Dataset Configurations & Statistics

The repository currently features two distinct configurations built dynamically through an advanced LLM generation and validation pipeline:

1. full_dataset

• Size: 142,200 validated QA pairs.
• Coverage: 16,075 unique Greek public figures.
• Domains Covered: Politics, science, academia, culture, arts, sports, business, and public life.

2. subset

• Size: 1,650 validated QA pairs.
• Coverage: 170 unique Greek public figures.
• Purpose: A smaller version of the full dataset focused exclusively on the most recognizable public figures, ideal for rapid evaluation, validation, or targeted benchmarking.

Dataset Creation & Curation Pipeline

1. Extraction & Scraping

NCSR-D identified and targeted 16,075 unique Wikipedia pages matching Greek individuals. The system extracted specific Wikipedia person properties directly from the latest dump to ensure up-to-date and robust context mappings.

2. Synthetic QA Generation

The language model google/gemma-3-12b-it (Gemma Team, 2025) was used to automatically draft QA pairs. The model was constrained to generate questions and answers exclusively from the biographical details embedded within each individual's text profile to combat hallucinations.

3. Dual-LLM Quality Control & Filtering

To ensure clean data and exceptional linguistic consistency, a second-pass evaluation was executed using google/gemma-4-12B (Gemma Team, 2026). The evaluation system filtered out data based on strict validation parameters:

• Factual correctness and total consistency against the source text.
• Linguistic compliance, measuring grammar, syntax, phrasing clarity, and overall Greek structural correctness.

Pairs failing any parameter were pruned from the final training split.

Loading and Usage

Load either configuration natively using the Hugging Face datasets package:

from datasets import load_dataset
 
# To load the full collection of 142,200 QA pairs:
dataset_full = load_dataset("PharosAIFactory/Wiki_Greek_Personalities", "full_dataset")
 
# To load the smaller validation subset of 1,650 QA pairs:
dataset_subset = load_dataset("PharosAIFactory/Wiki_Greek_Personalities", "subset")

Additional Information

• Curator Organization: NCSR-D / PharosAIFactory