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@ -36,16 +36,18 @@ This model is limited by its training dataset of entity-annotated news articles
## Training data ## Training data
The training data for the 10 languages are from: The training data for the 10 languages are from:
Arabic: [ANERcorp](https://github.com/EmnamoR/Arabic-named-entity-recognition) Language|Dataset
German: [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/) -|-
English: [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/) Arabic | [ANERcorp](https://github.com/EmnamoR/Arabic-named-entity-recognition)
Spanish: [conll 2002](https://www.clips.uantwerpen.be/conll2002/ner/) German | [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/)
French: [Europeana Newspapers](https://github.com/EuropeanaNewspapers/ner-corpora/tree/master/enp_FR.bnf.bio) English | [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/)
Italian: []() Spanish | [conll 2002](https://www.clips.uantwerpen.be/conll2002/ner/)
Latvian: [Latvian NER](https://github.com/LUMII-AILab/FullStack/tree/master/NamedEntities) French | [Europeana Newspapers](https://github.com/EuropeanaNewspapers/ner-corpora/tree/master/enp_FR.bnf.bio)
Dutch: [conll 2002](https://www.clips.uantwerpen.be/conll2002/ner/) Italian | [Italian I-CAB](https://ontotext.fbk.eu/icab.html)
Portuguese: [Paramopama + Second Harem](https://github.com/davidsbatista/NER-datasets/tree/master/Portuguese) Latvian | [Latvian NER](https://github.com/LUMII-AILab/FullStack/tree/master/NamedEntities)
Chinese: [MSRA](https://huggingface.co/datasets/msra_ner) Dutch | [conll 2002](https://www.clips.uantwerpen.be/conll2002/ner/)
Portuguese |[Paramopama + Second Harem](https://github.com/davidsbatista/NER-datasets/tree/master/Portuguese)
Chinese | [MSRA](https://huggingface.co/datasets/msra_ner)
The training dataset distinguishes between the beginning and continuation of an entity so that if there are back-to-back entities of the same type, the model can output where the second entity begins. As in the dataset, each token will be classified as one of the following classes: The training dataset distinguishes between the beginning and continuation of an entity so that if there are back-to-back entities of the same type, the model can output where the second entity begins. As in the dataset, each token will be classified as one of the following classes:
Abbreviation|Description Abbreviation|Description