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  CoQCat is a dataset for Conversational Question Answering in Catalan. It is based on [CoQA dataset](https://stanfordnlp.github.io/coqa/).
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- CoQCat comprises 89364 question-answer pairs, sourced from conversations related to 6000 text passages from six different domains.
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  The questions and responses are designed to maintain a conversational tone.
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  The answers are presented in a free-form text format, with evidence highlighted from the passage.
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  ### Data Splits
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- * dev.json: 8909 question-answering examples. 600 text passages from 4 domains
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- * test.json: 8986 question-answering examples. 600 text passages from 6 domains
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- * train.json: 71489 question-answering examples. 4800 text passages from 4 domains
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  ## Dataset Creation
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  #### Annotation process
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- The annotation process was entrusted to the company [m47 labs](https://www.m47labs.com/) through a public tender process.
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  We asked to organize the annotators team in pairs: one of the members asking questions from the text passage and the other one answering them. For the elaboration of addicional answers for the dev and test splits, we asked the participation of a third person, not involved in the original conversation.
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  #### Who are the annotators?
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- Annotation was entrusted to the company [m47 labs](https://www.m47labs.com/) through a public tender process.
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  We asked for a team of at least 4 annotators, students or graduates of universities, ideally in the field of Humanities or Social Sciences, with optimal demonstrable knowledge of the Catalan language (minimum level C1, or equivalent), and a senior coordinator with proven experience in management and coordination of text annotation.
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  ### Contributions
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- The annotation was entrusted to the company [m47 labs](https://www.m47labs.com/) through a public tender process.
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  Thanks to [M. Carme Marí](https://petiteshistories.wordpress.com/quant-a/) and the [VilaWeb](vilaweb.cat) team for allowing us to use their texts. And also to all the [Catalan wikipedia](ca.wikipedia.org) and [Gutenberg Project](gutenberg.org/) volunteers all their work.
 
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  CoQCat is a dataset for Conversational Question Answering in Catalan. It is based on [CoQA dataset](https://stanfordnlp.github.io/coqa/).
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+ CoQCat comprises 89,364 question-answer pairs, sourced from conversations related to 6,000 text passages from six different domains.
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  The questions and responses are designed to maintain a conversational tone.
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  The answers are presented in a free-form text format, with evidence highlighted from the passage.
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  ### Data Splits
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+ * dev.json: 8,909 question-answering examples. 600 text passages from 4 domains
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+ * test.json: 8,986 question-answering examples. 600 text passages from 6 domains
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+ * train.json: 71,489 question-answering examples. 4800 text passages from 4 domains
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  ## Dataset Creation
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  #### Annotation process
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+ The annotation process was entrusted to the company [M47 labs](https://www.m47labs.com/) through a public tender process.
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  We asked to organize the annotators team in pairs: one of the members asking questions from the text passage and the other one answering them. For the elaboration of addicional answers for the dev and test splits, we asked the participation of a third person, not involved in the original conversation.
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  #### Who are the annotators?
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+ Annotation was entrusted to the company [M47 labs](https://www.m47labs.com/) through a public tender process.
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  We asked for a team of at least 4 annotators, students or graduates of universities, ideally in the field of Humanities or Social Sciences, with optimal demonstrable knowledge of the Catalan language (minimum level C1, or equivalent), and a senior coordinator with proven experience in management and coordination of text annotation.
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  ### Contributions
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+ The annotation was entrusted to the company [M47 labs](https://www.m47labs.com/) through a public tender process.
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  Thanks to [M. Carme Marí](https://petiteshistories.wordpress.com/quant-a/) and the [VilaWeb](vilaweb.cat) team for allowing us to use their texts. And also to all the [Catalan wikipedia](ca.wikipedia.org) and [Gutenberg Project](gutenberg.org/) volunteers all their work.