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README.md
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<!-- Resumen del dataset. -->
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- **Curated by:** Jorge Zamora Rey
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- **Funded by:** SomosNLP, HuggingFace, Argilla, Universidad de Cádiz <!-- Si contasteis con apoyo de otra entidad (e.g. vuestra universidad), añadidla aquí -->
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- **Language(s) (NLP):** es-ES <!-- Enumerar las lenguas en las que se ha entrenado el modelo, especificando el país de origen. Utilizar códigos ISO. Por ejemplo: Spanish (`es-CL`, `es-ES`, `es-MX`), Catalan (`ca`), Quechua (`qu`). -->
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- **License:** apache-2.0 <!-- Elegid una licencia lo más permisiva posible teniendo en cuenta la licencia del model pre-entrenado y los datasets utilizados -->
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<!-- This section describes suitable use cases for the dataset. -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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<!-- Enlazar aquí los scripts y notebooks utilizados para generar el corpus. -->
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#### Who are the source data producers?
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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[More Information Needed]
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### Annotations [optional]
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<!-- Resumen del dataset. -->
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- **Curated by:** [Jorge Zamora Rey](https://huggingface.co/reddrex), [Isabel Moyano Moreno](https://huggingface.co/issyinthesky), [Mario Crespo Miguel](https://huggingface.co/MCMiguel) <!-- Nombre de los miembros del equipo -->
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- **Funded by:** SomosNLP, HuggingFace, Argilla, Instituto de Lingüística Aplicada de la Universidad de Cádiz <!-- Si contasteis con apoyo de otra entidad (e.g. vuestra universidad), añadidla aquí -->
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- **Language(s) (NLP):** es-ES <!-- Enumerar las lenguas en las que se ha entrenado el modelo, especificando el país de origen. Utilizar códigos ISO. Por ejemplo: Spanish (`es-CL`, `es-ES`, `es-MX`), Catalan (`ca`), Quechua (`qu`). -->
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- **License:** apache-2.0 <!-- Elegid una licencia lo más permisiva posible teniendo en cuenta la licencia del model pre-entrenado y los datasets utilizados -->
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<!-- This section describes suitable use cases for the dataset. -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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<!-- Enlazar aquí los scripts y notebooks utilizados para generar el corpus. -->
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First, we collected information on different aspects of Computational Linguistics (statistics, computer science, linguistics, corpus linguistics, etc.) from open blogs and webpages with [Bootcat](https://bootcat.dipintra.it).
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After this, we manually extracted information and created questions for each information segment. Then all three revised the whole document, deleted duplicated questions from each member's corpus portion and checked expressions.
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We also tried to make some explanations easier to comprehend for a broader audience, as the purpose of this project is mainly educational.
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Here we link the scripts used in the creation of the corpus, which are the following:
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- https://github.com/reddrex/lingcomp_QA/blob/main/dataset/Creación_archivo_JSON_a_partir_de_txt.ipynb
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- https://github.com/reddrex/lingcomp_QA/blob/main/train%20and%20test%20split/Train_and_test_LingComp_QA_split.ipynb
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#### Who are the source data producers?
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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### Annotations [optional]
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