--- license: cc-by-nc-4.0 gated: true extra_gated_prompt: Please provide the required information to access this model extra_gated_fields: Full Name: type: text Affiliation / Company: type: text Email Address: type: text Intended Use: type: select options: - Research - Education - Commercial Exploration - Academic Project - Other extra_gated_heading: Access Request – Provide Required Information extra_gated_description: Before accessing this model, please complete the form below. extra_gated_button_content: Submit Access Request configs: - config_name: Communication & Social Media data_files: - split: train path: Communication & Social Media/train-* - config_name: Culture & Heritage data_files: - split: train path: Culture & Heritage/train-* - config_name: Daily Life & Household data_files: - split: train path: Daily Life & Household/train-* - config_name: Education data_files: - split: train path: Education/train-* - config_name: Entertainment data_files: - split: train path: Entertainment/train-* - config_name: Finance & Banking data_files: - split: train path: Finance & Banking/train-* - config_name: Food data_files: - split: train path: Food/train-* - config_name: Geography data_files: - split: train path: Geography/train-* - config_name: Government Services data_files: - split: train path: Government Services/train-* - config_name: History data_files: - split: train path: History/train-* - config_name: Medical data_files: - split: train path: Medical/train-* - config_name: Nature & Environment data_files: - split: train path: Nature & Environment/train-* - config_name: Saudi Anthropology data_files: - split: train path: Saudi Anthropology/train-* - config_name: Shopping & Fashion data_files: - split: train path: Shopping & Fashion/train-* - config_name: Social Gatherings & Events data_files: - split: train path: Social Gatherings & Events/train-* - config_name: Sports & Fitness data_files: - split: train path: Sports & Fitness/train-* - config_name: Technology data_files: - split: train path: Technology/train-* - config_name: Transportation data_files: - split: train path: Transportation/train-* - config_name: Travel data_files: - split: train path: Travel/train-* - config_name: Weather & Seasons data_files: - split: train path: Weather & Seasons/train-* - config_name: Work & Office data_files: - split: train path: Work & Office/train-* dataset_info: - config_name: Communication & Social Media features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 26546 num_examples: 100 download_size: 17311 dataset_size: 26546 - config_name: Culture & Heritage features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 22676 num_examples: 102 download_size: 14135 dataset_size: 22676 - config_name: Daily Life & Household features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 16680 num_examples: 98 download_size: 11583 dataset_size: 16680 - config_name: Education features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 36869 num_examples: 150 download_size: 23302 dataset_size: 36869 - config_name: Entertainment features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 18468 num_examples: 106 download_size: 12344 dataset_size: 18468 - config_name: Finance & Banking features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 51748 num_examples: 200 download_size: 13030 dataset_size: 51748 - config_name: Food features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 27939 num_examples: 200 download_size: 15511 dataset_size: 27939 - config_name: Geography features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 14147 num_examples: 91 download_size: 9469 dataset_size: 14147 - config_name: Government Services features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 38613 num_examples: 200 download_size: 21323 dataset_size: 38613 - config_name: History features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 23662 num_examples: 150 download_size: 6347 dataset_size: 23662 - config_name: Medical features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 45448 num_examples: 200 download_size: 27780 dataset_size: 45448 - config_name: Nature & Environment features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 41532 num_examples: 200 download_size: 26052 dataset_size: 41532 - config_name: Saudi Anthropology features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 24738 num_examples: 104 download_size: 14684 dataset_size: 24738 - config_name: Shopping & Fashion features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 19514 num_examples: 100 download_size: 13309 dataset_size: 19514 - config_name: Social Gatherings & Events features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 17539 num_examples: 100 download_size: 12046 dataset_size: 17539 - config_name: Sports & Fitness features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 48747 num_examples: 200 download_size: 25461 dataset_size: 48747 - config_name: Technology features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 20857 num_examples: 100 download_size: 13317 dataset_size: 20857 - config_name: Transportation features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 13759 num_examples: 109 download_size: 10299 dataset_size: 13759 - config_name: Travel features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 26486 num_examples: 150 download_size: 13096 dataset_size: 26486 - config_name: Weather & Seasons features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 32327 num_examples: 200 download_size: 19256 dataset_size: 32327 - config_name: Work & Office features: - name: Anchor dtype: string - name: Positive dtype: string - name: Negative dtype: string splits: - name: train num_bytes: 18158 num_examples: 104 download_size: 11650 dataset_size: 18158 language: - ar pretty_name: Saudi Triplet task_categories: - feature-extraction - sentence-similarity tags: - saudi - Arabic - Triplet size_categories: - 1K

Team

✈️

Travel
Mohammed Alhassan

🍔

Food
Abdulelah Alankari

🛍️

Fashion
Reem Alsuliman

🎓

Education
Joud Aloqla

💼

Work
Nouf Alessa

📱

Tech
Jude Alsubaie

🏋️

Sports
Albara Aseri

🚗

Transport
Wajn Alqahtani

🎬

Entertainment
Muzon Assiri

🏠

Daily Life
Jana Alsuhaibani

💰

Finance
Abdullah Alsalem

🌤️

Weather
Huda Aldawsari

🎉

Events
Shaden Alosaimi

🩺

Medical
Munirah Alsubaie

📢

Social
Mohammed Alziyad

🇸🇦

Culture
Shatha Alotaibi

🌿

Nature
Norah Altwijri

📜

History
Renad Alrifai

🗺️

Geography
Murtada Altarouti

🏛️

Gov
Lama Almutairi

👥

Anthro
Adnan Hawsawi
--- ## 📊 Dataset Statistics | Statistic | Value | | :--- | :--- | | **Total Triplets** | 2,964 | | **Total Domains** | 21 | | **Language** | Saudi Dialect | | **Duplicate Anchors** | 59 (Multi-positive/negative pairings) | ### 📏 Sentence Lengths (Word Count) The dataset consists primarily of short-to-medium length queries and sentences, typical of search and conversational inputs. | Metric | Anchor | Positive | Negative | | :--- | :--- | :--- | :--- | | **Mean** | 6.42 | 6.50 | 5.34 | | **Std Dev** | 1.85 | 1.96 | 1.77 | | **Min** | 2 | 2 | 2 | | **Max** | 13 | 15 | 12 | --- ## 🏙️ Domain Distribution The dataset is balanced across high-resource topics (Food, Finance) and specific cultural topics (Anthropology, Heritage). | Domain | Count | | :--- | :--- | | **Food** | 200 | | **Finance & Banking** | 200 | | **Government Services** | 200 | | **Medical** | 200 | | **Sports & Fitness** | 200 | | **Weather & Seasons** | 200 | | **Nature & Environment** | 200 | | **Education** | 150 | | **Travel** | 150 | | **History** | 150 | | **Transportation** | 109 | | **Entertainment** | 106 | | **Saudi Anthropology** | 104 | | **Work & Office** | 104 | | **Culture & Heritage** | 102 | | **Shopping & Fashion** | 100 | | **Technology** | 100 | | **Communication & Social Media** | 100 | | **Social Gatherings & Events** | 100 | | **Daily Life & Household** | 98 | | **Geography** | 91 | --- ## 📂 Data Structure Each row in the dataset represents a training triplet designed for Contrastive Learning (e.g., MNRL). | Column Name | Type | Description | | :--- | :--- | :--- | | `Anchor` | String | The reference sentence/query in Saudi dialect. | | `Positive` | String | A sentence semantically similar to the Anchor (paraphrase or answer). | | `Negative` | String | A sentence semantically dissimilar to the Anchor (different topic or meaning). | | `Domain` | String | The topic category of the triplet. | --- ## 📝 Data Samples Below are real examples from the dataset showing the dialectal variations and domain diversity. | Domain | Anchor (Query) | Positive (Match) | Negative (Mismatch) | | :--- | :--- | :--- | :--- | | **Shopping & Fashion** | أبي فرشه تفك العقد وما تقطع الشعر | ابي مشط ما يخرب الشعر وينتفه | متى بيوصلني طقم الألماس اللي طلبته؟ | | **Finance & Banking** | أبغا أفتح محفظة أسهم وأبدأ استثمار بسيط | أفكر أبدأ تداول خفيف في الأسهم عن طريق المحفظة | ناوي أزور العائلة في القرية الأسبوع الجاي | | **Culture & Heritage** | أمس سمعت قصائد عن الشجاعة والفروسية | القصايد البدوية معانيها قوية | شغلت الغسالة بالغلط | | **Food** | السوفليه عندهم فخم | السوفليه يذوب بالفم | ما وصلت الشحنة | | **History** | الوالد كان دايم يذكر مملكة لحيان | شفت برنامج يتكلم عن سوق عكاظ | طلبي تأخر بالمطعم | | **Travel** | وين أحصل على جولات سياحية رخيصة؟ | أبغى ألقى عروض سياحية اقتصادية | الجو حار وما أقدر أطلع | --- ## ⚠️ Quality & Integrity * **Missing Data:** There are **no missing values** in the Anchor, Positive, or Negative columns. * **Duplicates:** There are **59 duplicate anchors**. This is intentional in some cases to provide multiple positive pairings for the same query or to enforce separation from different hard negatives. * **Dialect Intensity:** The text ranges from "White Dialect" (understandable by most Arabs) to deep Saudi vernacular (specific to Najd/Hijaz/South). --- ## 🛠️ Usage This dataset is optimized for training sentence transformers using `MultipleNegativesRankingLoss`. ```python from datasets import load_dataset # Load the dataset (Example path) dataset = load_dataset("Omartificial-Intelligence-Space/Saudi-Triplet-Dataset") # Print first example print(dataset['train'][0]) ```