From 60c9238433de8747fe6f8f4416c1ef8d738b2ec9 Mon Sep 17 00:00:00 2001 From: Davlanade Date: Tue, 24 Aug 2021 23:42:01 +0200 Subject: [PATCH] update readme data --- README.md | 22 ++++++++++++---------- 1 file changed, 12 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 1ddec76..be0c8c9 100644 --- a/README.md +++ b/README.md @@ -36,16 +36,18 @@ This model is limited by its training dataset of entity-annotated news articles ## Training data The training data for the 10 languages are from: -Arabic: [ANERcorp](https://github.com/EmnamoR/Arabic-named-entity-recognition) -German: [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/) -English: [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/) -Spanish: [conll 2002](https://www.clips.uantwerpen.be/conll2002/ner/) -French: [Europeana Newspapers](https://github.com/EuropeanaNewspapers/ner-corpora/tree/master/enp_FR.bnf.bio) -Italian: []() -Latvian: [Latvian NER](https://github.com/LUMII-AILab/FullStack/tree/master/NamedEntities) -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) +Language|Dataset +-|- +Arabic | [ANERcorp](https://github.com/EmnamoR/Arabic-named-entity-recognition) +German | [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/) +English | [conll 2003](https://www.clips.uantwerpen.be/conll2003/ner/) +Spanish | [conll 2002](https://www.clips.uantwerpen.be/conll2002/ner/) +French | [Europeana Newspapers](https://github.com/EuropeanaNewspapers/ner-corpora/tree/master/enp_FR.bnf.bio) +Italian | [Italian I-CAB](https://ontotext.fbk.eu/icab.html) +Latvian | [Latvian NER](https://github.com/LUMII-AILab/FullStack/tree/master/NamedEntities) +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: Abbreviation|Description