English-Italian Gaming Domain Parallel Corpora

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

Category

Parallel Corpora

Volume

50K+ Sentence Pairs

Last Updated

July 2025

Number of participants

200+ People

Gaming domain Multilingual Parallel corpus in Italian

About This OTS Dataset

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Introduction

The English-Italian Gaming Parallel Corpora is a curated bilingual dataset designed to support game localization, machine translation, and language model training for the Gaming industry. It consists of over 50,000 sentence pairs, professionally translated between English and Italian, capturing the linguistic and cultural depth of gaming content.

Dataset Content

  • Volume and Translator Diversity
  • Total Sentence Pairs: 50,000+
  • Contributors: Over 200 native and professional translators
  • Source: All content is original and tailored specifically for the Gaming domain
  • Sentence Variety
  • Sentence Length: 7 to 25 words
  • Sentence Types: Includes simple, compound, and complex sentences
  • Forms Covered: Interrogative, imperative, affirmative, and negative sentences
  • Voice Diversity: Sentences written in both active and passive voice
  • Stylistic Coverage: Includes idioms, metaphors, gaming slang, and figurative expressions
  • Discourse Elements: Contains conjunctions, logical connectors, and transitional phrases for natural flow
  • Bidirectional Structure: Includes English to Italian and Italian to English translations for robust model training
  • Domain-Specific Focus

  • Gaming Language Coverage
  • Terminology: Covers in-game elements, UI/UX, controls, multiplayer features, and genre-specific phrases
  • Dialogue Content: Includes NPC dialogue, tutorial lines, mission briefings, walkthroughs, and strategy guidance
  • Communication Scenarios: Reflects live chat, support queries, and multiplayer messaging
  • Cross-Domain Inclusion: Contains relevant terms from adjacent domains like entertainment, esports, virtual worlds, and AR/VR
  • Format and Structure
  • File Formats: Delivered in Excel, with optional conversion to JSON, TMX, XML, XLIFF, XLS, or other standard formats
  • Structure Fields: Serial Number, Unique ID, Source Sentence, Source Word Count, Target Sentence, Target Word Count
  • Sentence Alignment: Sentence-level parallel pairs with consistent formatting for MT pipelines
  • Usage and Applications

  • Machine Translation: Train and fine-tune domain-specific MT engines for gaming content
  • Game Localization: Adapt games across English-Italian markets while preserving nuance and playability
  • NLP Tools: Power predictive keyboards, grammar checkers, spelling correction, and sentence completion models
  • LLM Fine-Tuning: Strengthen bilingual comprehension and translation capabilities in large language models
  • Dialogue Systems: Enable context-aware, conversational AI for in-game or support environments
  • Bilingual Retrieval: Use for cross-language search, sentence matching, and similarity scoring
  • Alignment Confidence and Quality Assurance

  • All translations are manually verified by native bilingual experts for accuracy, naturalness, and domain relevance
  • Each sentence pair is reviewed to ensure semantic alignment and stylistic consistency
  • Quality checks include internal audits, reviewer feedback loops, and alignment validation metrics
  • Tokenization and Preprocessing

  • Dataset is provided in raw, untokenized form by default
  • Optional preprocessing available on request, including:
  • Tokenization
  • Lowercasing
  • Sentence-type tagging
  • Named entity masking
  • Format-specific encoding for MT or LLM use
  • Secure and Ethical Collection

  • Data Collection Platform: Created using FutureBeeAI’s proprietary platform, Yugo
  • Data Security: All data was collected, stored, and processed in a secure environment with no external exposure
  • Privacy Assurance: Contains no personally identifiable information
  • IP Safety: All content is original, created exclusively for this corpus, and free of third-party intellectual property
  • Updates and Customization

  • Continuous Expansion: Regularly updated with new sentence pairs and linguistic structures
  • Annotation Services Available:
  • Named Entity Recognition (NER)
  • Sentiment Analysis
  • Intent Classification
  • Translation Quality Ranking
  • POS tagging
  • Custom Dataset Collection: Available for any language pair or domain on request
  • Sentence Classification: Organize by subdomain, difficulty, sentence type, or discourse function
  • Licensing

    This dataset is developed and maintained by FutureBeeAI. It is available for commercial use under flexible licensing terms for enterprise, research, and application development.

    Use Cases

    Use of parallel corpus dataset in MT Engine

    MT Engine

    Use of parallel corpus dataset in Language modeling

    Language model

    Use of parallel corpus dataset in Predictive keyboards

    Predictive keyboards

    Use of parallel corpora dataset in Spell checker

    Spell check

    Use of parallel corpus dataset in grammar correction tool

    Grammar correction

    Use of parallel corpus dataset in Text/speech system

    Text/speech systems

    Dataset Sample(s)

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    Dataset Details

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    Dataset Type

    Text Corpus

    Volume

    50K+ Sentences

    Media type

    Text

    Language Pair

    English-Italian

    File Details

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    Type

    Bilingual

    Word Count

    7 to 25 Words per Asset

    Format

    XLSX, TMX, XML, XLIFF, XLS

    Annotation

    NA

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