thoddnn/OpenDataGen-factuality-en-v0.1

---
license: mit
task_categories:
- question-answering
language:
- en
tags:
- wikipedia
- synthetic
- synthetic data
size_categories:
- n<1K
---

This synthetic dataset was generated using the Open DataGen Python library. (https://github.com/thoddnn/open-datagen)

# Methodology:

1) Retrieve random article content from the HuggingFace Wikipedia English dataset.
2) Construct a Chain of Thought (CoT) to generate a Multiple Choice Question (MCQ).
3) Utilize a Large Language Model (LLM) to score the results then filter it.

All these steps are prompted in the 'template.json' file located in the specified code folder.

Code: https://github.com/thoddnn/open-datagen/blob/main/opendatagen/examples/opendata-eval/

Feel free to reach me on Linkedin (https://www.linkedin.com/in/thomasdordonne/) or Twitter (https://twitter.com/thoDdnn)

原始信息汇总

数据集概述

许可证

• MIT

任务类别

• 问答

语言

• 英语

标签

• Wikipedia
• 合成数据
• 合成数据集

数据集大小

• 小于1K

生成方法

1. 从HuggingFace的Wikipedia英语数据集中随机获取文章内容。
2. 构建思维链（Chain of Thought, CoT）以生成多选题（Multiple Choice Question, MCQ）。
3. 利用大型语言模型（Large Language Model, LLM）对结果进行评分并过滤。

代码文件

• 相关代码位于指定的代码文件夹中，具体路径为：https://github.com/thoddnn/open-datagen/blob/main/opendatagen/examples/opendata-eval/