README.md

metadata

language:
  - fa
license: apache-2.0
size_categories:
  - 100K<n<1M
task_categories:
  - question-answering
  - text-classification

📘 PerCoR: Persian Commonsense Reasoning (Multiple-Choice Sentence Completion)

Paper: PerCoR: Evaluating Commonsense Reasoning in Persian via Multiple-Choice Sentence Completion

PerCoR is a large-scale Persian benchmark for commonsense reasoning in a 4-choice sentence-completion format.
It contains ~106K examples from 40+ Persian websites across news, culture, lifestyle, tech, religion, travel, and more.
Each instance provides a prefix (context) and four candidate completions — one correct and three distractors.

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📦 What’s inside

• 🧮 Total size: ~106K multiple-choice instances
• 📊 Splits: train 86,217 • validation 10,000 • test 10,000
• 🧱 Format: single passage/prefix + 4 completions (A–D / 0–3) with one correct answer
• 🧠 Human accuracy: ~89% on a random subset

💡 The dataset is designed to be difficult for LLMs while remaining answerable by humans; no LLM text is used to generate distractors (reducing generation-style biases).