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README.md
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features:
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- name: web_url
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dtype: string
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- name:
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dtype: string
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- name: web_text
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dtype: string
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path: data/validation-*
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- split: test
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path: data/test-*
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---
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features:
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- name: web_url
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dtype: string
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- name: web_headline
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dtype: string
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- name: web_text
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dtype: string
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path: data/validation-*
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- split: test
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path: data/test-*
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language:
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- es
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tags:
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- summarization
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- clickbait
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- news
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pretty_name: NoticIA
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multilinguality:
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- monolingual
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source_datasets:
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- original
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task_categories:
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- summarization
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size_categories:
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- n<1K
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---
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<p align="center">
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<img src="https://huggingface.co/datasets/Iker/NoticIA/resolve/main/assets/logo.png" style="height: 250px;">
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</p>
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<h3 align="center">"A Spanish dataset for Clickbait articles summarization"</h3>
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We introduce a dataset that contains articles with clickbait headlines. We provide the clickbait headline for the article, the corresponding web text, and the summary. The summaries are written by humans and aim to answer the clickbait headlines using the fewest words possible.
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- 📖 Paper: [Coming soon]()
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- 💻 Baseline Code: [https://github.com/ikergarcia1996/NoticIA](https://github.com/ikergarcia1996/NoticIA)
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- 🔌 Online Demo: [https://iker-clickbaitfighter.hf.space/](https://iker-clickbaitfighter.hf.space/)
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For example, given the following headline and web text:
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```
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# ¿Qué pasará el 15 de enero de 2024?
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Al parecer, no todo es dulzura en las vacaciones de fin de años, como lo demuestra la nueva intrig....
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```
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The summary is:
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```
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Que los estudiantes vuelven a clase.
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```
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# Data explanation
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- **web_url** (int): The URL of the news article
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- **web_headline** (str): The headline of the article, which is a Clickbait.
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- **web_text** (int): The body of the article.
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- **clean_web_text** (str): The `web_text` has been downloaded from the web HTML and can contain undesired text not related to the news article. The `clean_web_text` has been cleaned using the OpenAI gpt-3.5-turbo-0125 model. We ask the model to remove any sentence unrelated to the article.
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- **summary** (str): The summary written by humans that answers the clickbait headline.
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