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README.md
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## Uses
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<!-- Address questions around how the dataset is intended to be used. -->
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This dataset is intended for educational purposes.
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### Direct Use
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<!-- This section describes suitable use cases for the dataset. -->
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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## Dataset Structure
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<!-- Motivation for the creation of this dataset. -->
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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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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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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<!-- Enlazar aquí el notebook utilizado para crear el espacio de anotación de Argilla y la guía de anotación. -->
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#### Who are the annotators?
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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## Bias, Risks, and Limitations
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<!-- Aquí podéis mencionar los posibles sesgos heredados según el origen de los datos y de las personas que lo han anotado, hablar del balance de las categorías representadas, los esfuerzos que habéis hecho para intentar mitigar sesgos y riesgos. -->
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations.
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## License
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## Contact
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<!-- Email de contacto para posibles preguntas sobre el dataset. -->
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mario.crespo@uca.es
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## Uses
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<!-- Address questions around how the dataset is intended to be used. -->
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This dataset is intended for educational purposes. When we further develop this resource, we would like it to serve as learning resource for NLP and Computational Linguistics beginners - either for tests, looking up the answers to common questions or studying key concepts and methodologies of CL.
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### Direct Use
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<!-- This section describes suitable use cases for the dataset. -->
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There is no specific use case intended for this dataset. However, we would like to develop a conversational language model that answers questions on Computational Linguistics.
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The dataset could be used to develop other educational tools or resources too, such as interactive quizzes, tutorials, and study materials, to help students learn about computational linguistics concepts, methodologies, and applications.
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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The dataset is specifically designed for tasks related to computational linguistics, language processing, and natural language understanding. Therefore, using the dataset for unrelated tasks, such as image processing or numerical analysis, would be considered out of scope.
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Other out of scope uses would be using this dataset for product development or marketing, any commercial use really, as it is intended for research and educational purposes.
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## Dataset Structure
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<!-- Motivation for the creation of this dataset. -->
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The lack of NLP educational resources meant for linguists, especially in Spanish, drove us to make a first attempt of collecting information on this topic from open internet sources. We aim to grow the corpus and create a a foundational resource for teaching linguists (and other beginners) about the principles, techniques, and applications of computational linguistics and NLP.
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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Blogs, wikipedia articles and our Computational Linguistics and Language Engineering course materials at the University of Cádiz comprise the source data for this dataset.
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#### Data Collection and Processing
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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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Our team members manually checked and organized the information into sets of questions and answers, while rewriting some of the info in a more suitable style for learners.
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<!-- ### Annotations [optional] -->
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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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<!-- Enlazar aquí el notebook utilizado para crear el espacio de anotación de Argilla y la guía de anotación. -->
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We manually sorted the information into question-answer pairs. However, we did use the following Colaboratory notebook to create the JSON file:
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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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#### Who are the annotators?
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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There are no personal, sensitive or private data that should not be shown in the dataset. The only names and dates that appear in it are those of the scientists, programmes and core dates in the development of the Artificial Intelligence area NLP.
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## Bias, Risks, and Limitations
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<!-- Aquí podéis mencionar los posibles sesgos heredados según el origen de los datos y de las personas que lo han anotado, hablar del balance de las categorías representadas, los esfuerzos que habéis hecho para intentar mitigar sesgos y riesgos. -->
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Main bias might belong to the sources from which we extracted the information. Some blogs or wikipedia articles might employ different terminology for the same concept (and while we have tried to correct this, some terms could have escaped our supervisors).
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Also, the low availability of information on Computational Linguistics and NLP on Spanish on the Internet may have created an imbalance on topics tackled by the dataset. For example, there could be more information on Python usage than NLTK, or more on NLTK than Spacy, as it happens.
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Among our future plans there is balancing the topics out by translating from English sources. Plus, we would like to add QA pairs that might not appear in any relevant open info source and that we believe would be good for learners - mostly from our experience in the Linguistics and Applied Languages bachelor, although we are open to requests.
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The limitations we found while building the dataset are mostly time-related, as such a broad topic can be difficult to cover in such a limited amount of time. Furthermore, we found ourselves unable to fully balance the coverage of all the involved themes, as there were not enough information sources on the internet - plus, open to the public - that we could use in order to document our QA pairs.
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### Recommendations
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Users should be made aware of the risks, biases and limitations of the dataset.
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We recommend checking the dataset from time to time or checking our social media/contacting us via email. There we will be announcing whether a new version with more information and a broader range of sources will be launched and when.
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## License
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## Contact
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<!-- Email de contacto para posibles preguntas sobre el dataset. -->
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mario.crespo@uca.es
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isabel.moyano@uca.es
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