--- license: cc-by-nd-4.0 language: - fa - en - ar tags: - 500x - chat - reasoning - JibayAi - evaluation - benchmark - persian - english - arabic - artificial intelligence task_categories: - text-generation pretty_name: PRCC-BENCH size_categories: - n<1K paperswithcode_id: pprc-bench configs: - config_name: fa data_files: - split: test path: PPRC-Bench-FA-JibayAi-500x.json - config_name: en data_files: - split: test path: PPRC-Bench-EN-JibayAi-500x.json - config_name: ar data_files: - split: test path: PPRC-Bench-AR-JibayAi-500x.json - config_name: all data_files: - split: test path: PRCC-BENCH-NO.csv --- # PRCC-BENCH

# Persian Reasoning, Comprehension, Conversation Benchmark ### Developed by Jibay Ai Persian Benchmark for Evaluating Understanding, Reasoning, Question Answering, Information Extraction, Instruction Following and Analysis.
--- # About PRCC-BENCH is a large-scale Persian benchmark developed by **Jibay Ai** to evaluate real-world capabilities of language models. Unlike traditional benchmarks that mainly focus on memorization or factual recall, PRCC-BENCH evaluates whether a model can truly: - Understand - Reason - Answer questions - Extract information - Follow instructions - Analyze complex situations The benchmark aims to provide a practical and realistic measurement of Persian language intelligence. --- # Benchmark Information | Property | Value | |---|---| | Name | PRCC-BENCH | | Organization | Jibay Ai | | Language | Persian | | Version | 1.0.0 | | Total Questions | 500 | | Scoring | +5 Correct | | Incorrect | 0 | | Blank | 0 | | Evaluation | Exact + Semantic | --- # Evaluation Categories ## 1. Comprehension Measures whether a model truly understands language. Capabilities: - Context understanding - Event tracking - Entity understanding - Reference resolution - Passage comprehension - Multi-step understanding Examples: - Identify actors - Understand actions - Detect context relationships - Interpret meaning --- ## 2. Reasoning Measures logical thinking ability. Capabilities: - Deduction - Cause and effect - Multi-step reasoning - Temporal reasoning - Consistency Examples: - Infer hidden conclusions - Connect multiple facts - Solve contextual tasks --- ## 3. Question Answering Measures: - Accuracy - Completeness - Precision - Context awareness Task types: - Direct QA - Contextual QA - Implicit answers - Multi-part questions --- ## 4. Information Extraction Measures: - Entity extraction - Number extraction - Fact retrieval - Relationship understanding - Context filtering Examples: - Extract important details - Ignore irrelevant information --- ## 5. Instruction Following Measures: - Obeying requirements - Exact formatting - Rule execution - Constraint handling Examples: - Structured output - Following conditions - Response discipline --- ## 6. Analysis Measures: - Deep understanding - Comparison - Problem decomposition - Conclusion generation Examples: - Analytical reasoning - Evidence comparison --- # Scoring System | Result | Score | |---|---| | Correct | +5 | | Incorrect | 0 | | Blank | 0 | | Near Match | 0 | Rule: Only fully correct responses receive points. --- # Judging Modes ## Exact Match Normalization includes: - Spaces - Persian digits - Punctuation Comparison occurs after normalization. --- ## Semantic Match Answers are accepted only if meaning remains fully equivalent. --- ## List Exact All required information must exist. --- ## Order Exact Required order must remain preserved. --- # Intended Use Cases PRCC-BENCH may be used for: - AI Evaluation - LLM Benchmarking - Academic Research - Product Testing - Regression Testing - Persian Model Comparison - Quality Assurance --- # Philosophy Understanding > Memorization Reasoning > Pattern Matching Execution > Generation --- # License This project is licensed under: ## CC BY-ND Creative Commons Attribution — No Derivatives Permission granted: ✅ Use ✅ Evaluate ✅ Publish Results ✅ Compare Models ✅ Share Benchmark Conditions: - Attribution must remain visible. - Original benchmark identity must remain unchanged. Additional Project Policy: - Modifying PRCC-BENCH is not authorized for official distribution. - Publishing altered versions as official releases is not permitted. - Publishing under another benchmark identity is not recognized as an official release. - Official upgrades and official benchmark publications are reserved exclusively for Jibay Ai. --- # Citation If you use PRCC-BENCH: PRCC-BENCH Developed by Jibay Ai --- # فارسی ## معرفی PRCC-BENCH یک بنچمارک زبان فارسی توسعه‌یافته توسط **Jibay Ai** است. هدف این پروژه ارزیابی توانایی واقعی مدل‌های هوش مصنوعی در انجام وظایف زبانی و تحلیلی است. این بنچمارک بر موارد زیر تمرکز دارد: - درک - استدلال - سوال و جواب - استخراج اطلاعات - پیروی از دستورات - تحلیل --- # مشخصات | ویژگی | مقدار | |---|---| | نام | PRCC-BENCH | | توسعه‌دهنده | Jibay Ai | | زبان | فارسی | | نسخه | 1.0.0 | | تعداد سوال | 500 | | امتیاز پاسخ صحیح | 5 | | پاسخ غلط | 0 | | ارزیابی | دقیق + معنایی | --- # بخش‌های ارزیابی ## درک سنجش توانایی مدل در: - فهم متن - دنبال کردن رویداد - تشخیص ارجاع - درک رابطه‌ها --- ## استدلال بررسی: - منطق - علت و معلول - تحلیل چندمرحله‌ای - نتیجه‌گیری --- ## سوال و جواب ارزیابی: - دقت - کامل بودن - وابستگی به متن --- ## استخراج اطلاعات بررسی: - استخراج موجودیت - استخراج عدد - تشخیص اطلاعات مهم --- ## پیروی از دستورات بررسی: - رعایت محدودیت - اجرای دقیق - حفظ ساختار --- ## تحلیل بررسی: - تجزیه مسئله - مقایسه - استنتاج --- # سیستم امتیازدهی پاسخ صحیح: ۵ سایر حالت‌ها: ۰ فقط پاسخ کاملاً صحیح امتیاز دریافت می‌کند. --- # مجوز این پروژه تحت مجوز: ## CC BY-ND منتشر شده است. همه افراد و سازمان‌ها مجاز هستند: ✅ استفاده کنند ✅ ارزیابی انجام دهند ✅ نتایج منتشر کنند ✅ مقایسه انجام دهند اما: ❌ هیچ شخص یا سازمانی اجازه تغییر یا ارتقاء نسخه رسمی را ندارد. ❌ انتشار نسخه تغییر یافته به عنوان نسخه رسمی مجاز نیست. ❌ انتشار با نام دیگر به عنوان نسخه رسمی مجاز نیست. ✅ حق توسعه نسخه رسمی، ارتقاء و انتشارات رسمی فقط متعلق به Jibay Ai است. --- PRCC-BENCH by jibay.ir