---
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