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@@ -122,19 +122,18 @@ Data collection efforts were performed between 2024/01/01-2024/02/23.
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  #### Personal and Sensitive Information
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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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  [More Information Needed]
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- This
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- Furthermore, text coming from susa (literature) and subtitles sources, may content hate speech, slurs or explicit language.
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  We decided to include them in the corpus, to ensure that the corpus contains conversational data.
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  We did not perform any cleaning or censoring of those, since it might be needed for tasks like hate speech detection.
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- We suggest filtering those before pretraining an LLM for end tasks like interactive chat.
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  [More Information Needed]
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@@ -142,9 +141,10 @@ We suggest filtering those before pretraining an LLM for end tasks like interact
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
 
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- ## Citation [optional]
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  <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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  #### Personal and Sensitive Information
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+ The dataset contains publicly available data that might be considered personal and sensitive (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.).
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  [More Information Needed]
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+ This corpus inherits the Basque speaking society's stereotypes (gender bias, ethnical bias, cultural bias, linguistic bias, ...).
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+ Furthermore, text coming from susa (literature) and subtitles sources, contain hate speech, slurs or explicit language.
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  We decided to include them in the corpus, to ensure that the corpus contains conversational data.
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  We did not perform any cleaning or censoring of those, since it might be needed for tasks like hate speech detection.
 
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  [More Information Needed]
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+ Users should be made aware of the risks, biases and limitations of the dataset.
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+ We suggest filtering sources containing hate speech, slurs or explicit language before pretraining an LLM for end tasks like interactive chat.
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+ ## Citation
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  <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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