license: cc-by-4.0
language:
- zh
tags:
- text-generation
- e-commerce advertise
pretty_name: AdvertiseGen
task_categories:
- text-generation
Dataset Card for Alpaca-zh
- formal url: https://www.luge.ai/#/luge/dataDetail?id=9
Dataset Description
数据集介绍
AdvertiseGen是电商广告文案生成数据集。
AdvertiseGen以商品网页的标签与文案的信息对应关系为基础构造，是典型的开放式生成任务，在模型基于key-value输入生成开放式文案时，与输入信息的事实一致性需要得到重点关注。
- 任务描述：给定商品信息的关键词和属性列表kv-list，生成适合该商品的广告文案adv；
- 数据规模：训练集114k，验证集1k，测试集3k；
- 数据来源：清华大学CoAI小组；
Supported Tasks and Leaderboards
The Alpaca dataset designed for instruction training pretrained language models.
Languages
The data in AdvertiseGen are in Chinese.
Dataset Structure
Data Instances
An example of "train" looks as follows:
{
"content": "类型#上衣*材质#牛仔布*颜色#白色*风格#简约*图案#刺绣*衣样式#外套*衣款式#破洞",
"summary": "简约而不简单的牛仔外套，白色的衣身十分百搭。衣身多处有做旧破洞设计，打破单调乏味，增加一丝造型看点。衣身后背处有趣味刺绣装饰，丰富层次感，彰显别样时尚。"
}
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Discussion of Biases
[More Information Needed]
Other Known Limitations
The alpaca data is generated by a language model (text-davinci-003) and inevitably contains some errors or biases. We encourage users to use this data with caution and propose new methods to filter or improve the imperfections.
Additional Information
Dataset Curators
[More Information Needed]
Citation Information
数据集引用
如在学术论文中使用本数据集，请添加相关引用说明，具体如下：
Shao, Zhihong, et al. "Long and Diverse Text Generation with Planning-based Hierarchical Variational Model." Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.
Contributions
[More Information Needed]