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{ |
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"lang":"da", |
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"name":"dacy_medium_ner_fine_grained", |
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"version":"0.1.0", |
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"description":"\n<a href=\"https://github.com/centre-for-humanities-computing/Dacy\"><img src=\"https://centre-for-humanities-computing.github.io/DaCy/_static/icon.png\" width=\"175\" height=\"175\" align=\"right\" /></a>\n\n# DaCy_medium_ner_fine_grained\n\nDaCy is a Danish language processing framework with state-of-the-art pipelines as well as functionality for analyzing Danish pipelines.\nAt the time of publishing this model, also included in DaCy encorporates the only models for fine-grained NER using DANSK dataset - a dataset containing 18 annotation types in the same format as Ontonotes.\nMoreover, DaCy's largest pipeline has achieved State-of-the-Art performance on Named entity recognition, part-of-speech tagging and dependency parsing for Danish on the DaNE dataset. \nCheck out the [DaCy repository](https://github.com/centre-for-humanities-computing/DaCy) for material on how to use DaCy and reproduce the results. \nDaCy also contains guides on usage of the package as well as behavioural test for biases and robustness of Danish NLP pipelines.\n ", |
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"author":"Centre for Humanities Computing Aarhus", |
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"email":"Kenneth.enevoldsen@cas.au.dk", |
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"url":"https://chcaa.io/#/", |
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"license":"apache-2.0", |
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"spacy_version":">=3.5.0,<3.6.0", |
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"spacy_git_version":"Unknown", |
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"vectors":{ |
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"width":0, |
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"vectors":0, |
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"keys":0, |
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"name":null |
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}, |
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"labels":{ |
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"transformer":[ |
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], |
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"ner":[ |
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"CARDINAL", |
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"DATE", |
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"EVENT", |
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"FACILITY", |
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"GPE", |
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"LANGUAGE", |
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"LAW", |
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"LOCATION", |
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"MONEY", |
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"NORP", |
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"ORDINAL", |
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"ORGANIZATION", |
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"PERCENT", |
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"PERSON", |
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"PRODUCT", |
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"QUANTITY", |
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"TIME", |
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"WORK OF ART" |
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] |
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}, |
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"pipeline":[ |
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"transformer", |
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"ner" |
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], |
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"components":[ |
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"transformer", |
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"ner" |
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], |
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"disabled":[ |
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], |
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"performance":{ |
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"ents_f":0.8055281343, |
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"ents_p":0.7937743191, |
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"ents_r":0.8176352705, |
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"ents_per_type":{ |
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"ORGANIZATION":{ |
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"p":0.8376623377, |
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"r":0.8657718121, |
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"f":0.8514851485 |
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}, |
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"PERSON":{ |
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"p":0.8875739645, |
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"r":0.8571428571, |
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"f":0.8720930233 |
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}, |
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"NORP":{ |
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"p":0.8958333333, |
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"r":0.8775510204, |
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"f":0.8865979381 |
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}, |
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"CARDINAL":{ |
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"p":0.7797356828, |
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"r":0.7831858407, |
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"f":0.7814569536 |
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}, |
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"GPE":{ |
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"p":0.764957265, |
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"r":0.9274611399, |
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"f":0.8384074941 |
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}, |
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"DATE":{ |
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"p":0.8248587571, |
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"r":0.8957055215, |
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"f":0.8588235294 |
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}, |
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"PRODUCT":{ |
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"p":0.6184210526, |
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"r":0.6527777778, |
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"f":0.6351351351 |
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}, |
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"LOCATION":{ |
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"p":0.7, |
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"r":0.7777777778, |
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"f":0.7368421053 |
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}, |
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"FACILITY":{ |
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"p":0.5, |
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"r":0.5714285714, |
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"f":0.5333333333 |
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}, |
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"WORK OF ART":{ |
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"p":0.6078431373, |
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"r":0.6739130435, |
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"f":0.6391752577 |
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}, |
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"TIME":{ |
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"p":0.5, |
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"r":0.6666666667, |
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"f":0.5714285714 |
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}, |
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"MONEY":{ |
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"p":1.0, |
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"r":1.0, |
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"f":1.0 |
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}, |
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"PERCENT":{ |
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"p":0.9230769231, |
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"r":1.0, |
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"f":0.96 |
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}, |
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"QUANTITY":{ |
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"p":0.5666666667, |
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"r":0.7727272727, |
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"f":0.6538461538 |
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}, |
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"ORDINAL":{ |
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"p":0.7777777778, |
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"r":0.6363636364, |
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"f":0.7 |
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}, |
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"LANGUAGE":{ |
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"p":1.0, |
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"r":0.3214285714, |
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"f":0.4864864865 |
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}, |
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"LAW":{ |
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"p":0.7142857143, |
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"r":0.5555555556, |
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"f":0.625 |
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}, |
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"EVENT":{ |
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"p":0.5555555556, |
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"r":0.5882352941, |
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"f":0.5714285714 |
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} |
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}, |
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"transformer_loss":172.7275591314, |
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"ner_loss":820.9019488291 |
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}, |
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"requirements":[ |
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"spacy-transformers>=1.1.2,<1.2.0" |
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], |
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"datasets":"chcaa/DANSK", |
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"sources":[ |
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{ |
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"name":"DANSK - Danish Annotations for NLP Specific TasKs", |
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"url":"https://huggingface.co/datasets/chcaa/DANSK", |
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"license":"Creative Commons Attribution Share Alike 4.0 International", |
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"author":"chcaa" |
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}, |
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{ |
|
"name":"vesteinn/DanskBERT", |
|
"author":"V\u00e9steinn Sn\u00e6bjarnarson", |
|
"url":"https://huggingface.co/vesteinn/DanskBERT", |
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"license":"agpl-3.0" |
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} |
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] |
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} |