Update README.md

README.md

@@ -82,3 +82,28 @@ Que los estudiantes vuelven a clase.
 - **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. 
 - **summary** (str):  The summary written by humans that answers the clickbait headline. 
 
+# Dataset Description
+
+- **Curated by:** [Iker García-Ferrero](https://ikergarcia1996.github.io/Iker-Garcia-Ferrero/)
+- **Language(s) (NLP):** Spanish
+- **License:** apache-2.0
+
+# Uses
+This dataset is intended to build models tailored for academic research that can extract information from large texts. The objective is to research whether current LLMs, given a question formulated as a Clickbait headline, can locate the answer within the article body and summarize the information in a few words. The dataset also aims to serve as a task to evaluate the performance of current LLMs in Spanish.
+
+# Out-of-Scope Use
+You cannot use this dataset to develop systems that directly harm the newspapers included in the dataset. This includes using the dataset to train profit-oriented LLMs capable of generating articles from a short text or headline, as well as developing profit-oriented bots that automatically summarize articles without the permission of the article's owner. Additionally, you are not permitted to train a system with this dataset that generates clickbait headlines.
+
+# Dataset Creation
+
+The dataset has been meticulously created by hand. We utilize two sources to compile Clickbait articles:
+- The Twitter user [@ahorrandoclick1](https://twitter.com/ahorrandoclick1), who reposts Clickbait articles along with a hand-crafted summary. Although we use their summaries as a reference, most of them have been rewritten (750 examples from this source).
+- The web demo [⚔️ClickbaitFighter⚔️](https://iker-clickbaitfighter.hf.space/), which operates a pre-trained model using an early iteration of our dataset. We collect all the model inputs/outputs and manually correct them (100 examples from this source).
+
+# Who are the annotators?
+
+The dataset was annotated by [Iker García-Ferrero](https://ikergarcia1996.github.io/Iker-Garcia-Ferrero/) and validated by .
+The annotation took ~40 hours.
+
+
+