Datasets:
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---
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](https://huggingface.co/papers/2510.22616)
**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).* |