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- # Ancora-Ca-NER
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  ## Dataset Description
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  ### Dataset Summary
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- This is a dataset for Named Entity Recognition (NER) in Catalan. It adapts <a href="http://clic.ub.edu/corpus/">Ancora corpus</a> for Machine Learning and Language Model evaluation purposes.
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- AnCora corpus is used under [CC-by](https://creativecommons.org/licenses/by/4.0/) licence.
 
 
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- This dataset was developed by BSC TeMU as part of the AINA project, and to enrich the Catalan Language Understanding Benchmark (CLUB).
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  ### Supported Tasks and Leaderboards
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  ### Data Splits
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- We took the original train, dev and test splits from the [UD version of the corpus] (https://huggingface.co/datasets/universal_dependencies)
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  - train: 10,630 examples
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  - validation: 1,429 examples
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  ### Methodology
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- We adapted the NER labels from Ancora corpus to a word-per-line format.
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  ### Curation Rationale
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  #### Initial Data Collection and Normalization
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- AnCora consists of a Catalan corpus (AnCora-CA) and a Spanish corpus (AnCora-ES), each of them of 500,000 tokens (some multi-word). The corpora are annotated for linguistic phenomena at different levels.
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  AnCora corpus is mainly based on newswire texts. For more information, refer to Taulé, M., M.A. Martí, M. Recasens (2009). <a href="http://www.lrec-conf.org/proceedings/lrec2008/pdf/35_paper.pdf">"AnCora: Multilevel Annotated Corpora for Catalan and Spanish”, Proceedings of 6th International Conference on language Resources and Evaluation"</a>.
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  #### Who are the source language producers?
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- Catalan Ancora corpus is compiled from articles from the following news outlets: <a href="https://www.efe.com">EFE</a>, <a href="https://www.acn.cat">ACN</a>, <a href="https://www.elperiodico.cat/ca/">El Periodico</a>.
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  ### Annotations
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  #### Annotation process
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- We adapted the NER labels from Ancora corpus to a token-per-line, multi-column format.
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  #### Who are the annotators?
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- Original annotators from Ancora corpus.
 
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  ### Personal and Sensitive Information
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  No personal or sensitive information included.
 
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  task_ids: []
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  ---
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+ # AnCora-Ca-NER
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  ## Dataset Description
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  ### Dataset Summary
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+ This is a dataset for Named Entity Recognition (NER) in Catalan. It adapts <a href="http://clic.ub.edu/corpus/">AnCora corpus</a> for Machine Learning and Language Model evaluation purposes.
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+ [AnCora corpus](http://clic.ub.edu/corpus/) is used under [CC-by](https://creativecommons.org/licenses/by/4.0/) licence.
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+
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+ This dataset was developed by [BSC TeMU](https://temu.bsc.es/) as part of the [projecte Aina](https://politiquesdigitals.gencat.cat/ca/tic/aina-el-projecte-per-garantir-el-catala-en-lera-digital/), to enrich the [Catalan Language Understanding Benchmark (CLUB)](https://temu-bsc.github.io/catalan-language-understanding-benchmark/).
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  ### Supported Tasks and Leaderboards
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  ### Data Splits
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+ We took the original train, dev and test splits from the [UD version of the corpus](https://huggingface.co/datasets/universal_dependencies)
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  - train: 10,630 examples
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  - validation: 1,429 examples
 
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  ### Methodology
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+ We adapted the NER labels from [AnCora corpus](http://clic.ub.edu/corpus/) to a word-per-line format.
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  ### Curation Rationale
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  #### Initial Data Collection and Normalization
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+ [AnCora](http://clic.ub.edu/corpus/) consists of a Catalan corpus (AnCora-CA) and a Spanish corpus (AnCora-ES), each of them of 500,000 tokens (some multi-word). The corpora are annotated for linguistic phenomena at different levels.
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  AnCora corpus is mainly based on newswire texts. For more information, refer to Taulé, M., M.A. Martí, M. Recasens (2009). <a href="http://www.lrec-conf.org/proceedings/lrec2008/pdf/35_paper.pdf">"AnCora: Multilevel Annotated Corpora for Catalan and Spanish”, Proceedings of 6th International Conference on language Resources and Evaluation"</a>.
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  #### Who are the source language producers?
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+ Catalan [AnCora corpus](http://clic.ub.edu/corpus/) is compiled from articles from the following news outlets: <a href="https://www.efe.com">EFE</a>, <a href="https://www.acn.cat">ACN</a>, <a href="https://www.elperiodico.cat/ca/">El Periodico</a>.
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  ### Annotations
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  #### Annotation process
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+ We adapted the NER labels from [AnCora corpus](http://clic.ub.edu/corpus/) to a token-per-line, multi-column format.
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  #### Who are the annotators?
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+ Original annotators from [AnCora corpus](http://clic.ub.edu/corpus/).
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+
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  ### Personal and Sensitive Information
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  No personal or sensitive information included.