English-Arabic Tourism Domain Parallel Corpora

A high-quality bilingual dataset containing sentence-aligned English-Arabic text pairs for the Tourism domain. Supports translation, NLP, and LLM training.

About This OTS Dataset

Introduction

Welcome to the English-Arabic Bilingual Parallel Corpora Dataset for the Tourism domain, a comprehensive collection of high-quality, professionally translated bilingual text. This dataset is designed to support the development of tourism-specific machine translation systems, domain-adapted NLP tools, and multilingual language models.

Dataset Content

•Volume and Diversity

•Extensive Coverage: Over 50,000 bilingual sentence pairs, providing a strong foundation for training and evaluation.

•Translator Diversity: Curated by 200+ native Arabic linguists, ensuring rich stylistic and regional variety.

•Sentence Diversity

•Length Range: Sentences vary from 7 to 25 words, suitable for multiple NLP applications.

•Syntactic Variety: Includes simple, compound, and complex sentence structures.

•Voice & Mood: Interrogative (questions) and imperative (commands), affirmative and negative polarity, active and passive voice constructions.

•Figurative Language: Incorporates idioms, metaphors, and colloquialisms relevant to travel, hospitality, and cultural experiences.

•Discourse Flow: Features logical connectors, transitional phrases, and discourse markers to enhance naturalness.

•Cross Translation: The dataset includes both English→Arabic and Arabic→English translations to boost bi-directional machine translation capabilities.

Domain-Specific Focus

•Tourism-Centric Language

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Tailored Terminology: Covers vocabulary from the travel and tourism industry, including terms related to flights, lodging, tours, local culture, and hospitality services.

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Real-World Use Cases:

Features authentic expressions from travel blogs and brochures, hotel reviews, tourist guides and maps, and cultural attraction descriptions.

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Contextual Depth:

Drawn from websites, guidebooks, marketing material, and customer service dialogs.

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Cross-Domain Content:

Includes intersecting topics from geography, history, cultural studies, entertainment, and local cuisine.

Format & Structure

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Available Formats: Delivered in Excel by default, with easy conversion to JSON, TMX, XML, XLIFF, and other translation/AI-friendly formats.

•Structured Fields:

•Serial Number

•Unique ID

•Source Sentence

•Source Word Count

•Target Sentence

•Target Word Count

Usage & Applications

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Machine Translation: Build and fine-tune MT models for travel-related content.

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Language Understanding: Enhance systems like chatbots, voice assistants, and Q&A engines for tourist support.

•LLM Training:

•Generate personalized travel content

•Summarize city guides and attraction reviews

•Respond to multilingual tourist inquiries

Secure & Ethical Data Practices

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Collection Platform: Entire dataset developed using FutureBeeAI’s proprietary Yugo platform.

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Data Security: All data remained within a closed environment, no external access, no third-party exposure.

•Privacy & IP Compliance:

•No PII included

•No copyright violations

•100% original content created for this dataset

Updates & Customization

•Tailored Options Available

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Annotation Services: Part-of-speech tagging, Named Entity Recognition (NER), Sentiment & intent tagging, Multiple translation rankings.

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Thematic Classification: Filter corpus by sentence type, tone, or tourism subdomain.

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Custom Data Collection: On-demand data collection in any language pair and tourism-related domain.

Licensing

This English-Arabic Tourism Parallel Corpus is developed and owned by FutureBeeAI and is available for commercial licensing. Ideal for enterprise NLP deployments, academic research, and AI product development.