{"id":18366820,"url":"https://github.com/zamgi/lingvo--postagger-ner-ru-dnn","last_synced_at":"2025-04-06T16:32:23.730Z","repository":{"id":38686510,"uuid":"478719882","full_name":"zamgi/lingvo--PosTagger-NER-ru-dnn","owner":"zamgi","description":"Part of speech tagging of words and Named-entity recognition in Russian language using deep neural network in C# for 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PosTagger\nPart of speech tagging of words in Russian language using deep neural network in C# for .NET\n\nA tensors-based deep neural network used for PoS-tagging (sequence-labeling task) text in Russian based on word endings.\nSupports both CPU and GPU computing.\n\n#\nMetrics for includes models:\n\n Custom markup corpus (sents = 41 989):\n```\nCommon-F-Score = '89.41'\n\nAdjective          : F-score = '90.11' Precision = '88.65' Recall = '91.62'\nAdjectivePronoun   : F-score = '87.77' Precision = '88.18' Recall = '87.37'\nAdverb             : F-score = '85.78' Precision = '86.04' Recall = '85.51'\nAdverbialParticiple: F-score = '91.01' Precision = '92.47' Recall = '89.58'\nAdverbialPronoun   : F-score = '83.15' Precision = '85.71' Recall = '80.74'\nAuxiliaryVerb      : F-score = '93.38' Precision = '95.48' Recall = '91.36'\nConjunction        : F-score = '90.20' Precision = '88.89' Recall = '91.55'\nInfinitive         : F-score = '97.38' Precision = '96.97' Recall = '97.80'\nInterjection       : F-score = '80.00' Precision = '93.33' Recall = '70.00'\nNoun               : F-score = '97.13' Precision = '97.45' Recall = '96.81'\nNumeral            : F-score = '93.60' Precision = '93.78' Recall = '93.41'\nOther              : F-score = '77.41' Precision = '80.76' Recall = '74.32'\nParticiple         : F-score = '68.52' Precision = '71.58' Recall = '65.71'\nParticle           : F-score = '80.78' Precision = '83.27' Recall = '78.44'\nPossessivePronoun  : F-score = '92.47' Precision = '90.39' Recall = '94.65'\nPredicate          : F-score = '92.57' Precision = '91.33' Recall = '93.84'\nPreposition        : F-score = '98.58' Precision = '98.07' Recall = '99.09'\nPronoun            : F-score = '91.82' Precision = '91.58' Recall = '92.05'\nPunctuation        : F-score = '99.87' Precision = '99.83' Recall = '99.91'\nVerb               : F-score = '96.76' Precision = '96.42' Recall = '97.10'\n\nThe number of part of speech categories = '20'\n```\n \"nerus_lenta.conllu\" corpus (sents = 8 066 461):\n```\nCommon-F-Score = '95.11'\n\nADJ  : F-score = '97.79' Precision = '97.09' Recall = '98.51'\nADP  : F-score = '99.90' Precision = '99.84' Recall = '99.96'\nADV  : F-score = '98.03' Precision = '98.75' Recall = '97.33'\nAUX  : F-score = '99.35' Precision = '99.30' Recall = '99.40'\nCCONJ: F-score = '99.64' Precision = '99.47' Recall = '99.82'\nDET  : F-score = '97.24' Precision = '96.83' Recall = '97.64'\nINTJ : F-score = '58.33' Precision = '77.78' Recall = '46.67'\nNOUN : F-score = '98.19' Precision = '96.99' Recall = '99.42'\nNUM  : F-score = '98.66' Precision = '99.04' Recall = '98.28'\nPART : F-score = '98.21' Precision = '98.69' Recall = '97.74'\nPRON : F-score = '98.75' Precision = '99.22' Recall = '98.29'\nPROPN: F-score = '93.65' Precision = '98.27' Recall = '89.45'\nPUNCT: F-score = '99.95' Precision = '99.95' Recall = '99.95'\nSCONJ: F-score = '99.29' Precision = '99.22' Recall = '99.36'\nSYM  : F-score = '86.54' Precision = '89.11' Recall = '84.11'\nVERB : F-score = '98.47' Precision = '98.76' Recall = '98.19'\nX    : F-score = '94.86' Precision = '94.52' Recall = '95.20'\n\nThe number of categories = '17'\n```\n#\n\nIncluded PosTagger UI sample:\n![alt tag](https://github.com/zamgi/lingvo--PosTagger-ru-dnn/blob/master/pos_tagger_ru.png)\n\n\n# NER\nNamed-entity recognition in Russian language using deep neural network in C# for .NET\n\n#\nMetrics for includes models:\n\n \"nerus_lenta.conllu\" corpus (sents = 500 000):\n```\nCommon-F-Score = '94.30'\n\nB-LOC: F-score = '97.37' Precision = '97.88' Recall = '96.87'\nB-ORG: F-score = '92.90' Precision = '93.34' Recall = '92.47'\nB-PER: F-score = '96.21' Precision = '97.37' Recall = '95.08'\nI-LOC: F-score = '91.90' Precision = '94.68' Recall = '89.28'\nI-ORG: F-score = '90.43' Precision = '89.45' Recall = '91.43'\nI-PER: F-score = '96.98' Precision = '97.54' Recall = '96.42'\n\nThe number of categories = '6'\n```\n \"nerus_lenta.conllu\" corpus (sents = 1 000 000):\n```\nCommon-F-Score = '96.78'\n\nB-LOC: F-score = '98.46' Precision = '98.54' Recall = '98.39'\nB-ORG: F-score = '95.22' Precision = '96.10' Recall = '94.35'\nB-PER: F-score = '98.71' Precision = '99.02' Recall = '98.40'\nI-LOC: F-score = '94.67' Precision = '95.63' Recall = '93.73'\nI-ORG: F-score = '94.43' Precision = '94.92' Recall = '93.95'\nI-PER: F-score = '98.94' Precision = '98.84' Recall = '99.04'\n\nThe number of categories = '6'\n```\n#\n\nIncluded NER UI sample:\n![alt tag](https://github.com/zamgi/lingvo--PosTagger-ru-dnn/blob/master/ner_ru.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzamgi%2Flingvo--postagger-ner-ru-dnn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzamgi%2Flingvo--postagger-ner-ru-dnn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzamgi%2Flingvo--postagger-ner-ru-dnn/lists"}