datasets-CNRS/ThesoTM huggingface dataset:
BTM / BTM
Also known as: Biterm Topic Models / 
Definition: Biterm Topic Models find topics in collections of short texts. It is a word co-occurrence based topic model that learns topics by modeling word-word co-occurrences patterns which are called biterms.
Définition : BTM (Biterm Topic Models) permet de repérer des topiques dans des collections de textes courts. Il s'agit d'un outil basé sur l'apprentissage de thèmes en utilisant des modèles de cooccurrence de mots qui sont appelés bitermes.
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Programming language: C++§§R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: Apache License Version 2.0 / Apache License Version 2.0
Uses software: R / R
Repository: https://cran.r-project.org/web/packages/BTM/index.html§§https://github.com/bnosac/BTM
Reference: Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Xueqi Cheng. A Biterm Topic Model For Short Text, (2013), WWW2013. https://doi.org/10.1145/2488388.2488514
Baatonum / baatonum
Also known as: Bariba / bariba
Broader concept: natural language / langage naturel
IETF language tag: bba
ISO 639-3: bba
bagging / bagging
Also known as: bootstrap aggregating / bootstrap aggregating
Definition: Bootstrap aggregating is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine learning algorithms used in statistical classification and regression. (wikipedia, retrieved on 2021/07/07).
Définition : L'agrégation Bootstrap est un méta-algorithme d'ensemble d'apprentissage automatique conçu pour améliorer la stabilité et la précision des algorithmes d'apprentissage automatique utilisés dans la classification statistique et la régression. (wikipédia, récupéré le 07/07/2021).
Broader concept: boosting / boosting
Implemented by: Datumbox§§RTextTools§§RWeka§§Massive Online Analysis / Datumbox§§RTextTools§§RWeka§§Massive Online Analysis
Reference: Breiman, L. (1996). Bagging predictors. Machine Learning, 24(2), 123‑140. https://doi.org/10.1007/BF00058655
Balinese / balinais
Broader concept: natural language / langage naturel
IETF language tag: ban
ISO 639-2: ban
ISO 639-3: ban
Balkan Romani / romani des Balkans
Also known as: Balkan Gypsy§§Balkaniko Romanes / 
Broader concept: natural language / langage naturel
IETF language tag: rmn
ISO 639-3: rmn
Balochi / baloutchi
Broader concept: natural language / langage naturel
IETF language tag: bal
ISO 639-2: bal
ISO 639-3: bal§§bgp
Bambara / bambara
Also known as: Bamana§§Bamanankan / 
Broader concept: natural language / langage naturel
IETF language tag: bm
ISO 639-1: bm
ISO 639-2: bam
ISO 639-3: bam
BanglaBERT / BanglaBERT
Definition: A language model pre-trained on texts in Bangla.
Définition : Modèle de langage pré-entraîné sur des textes en bengali.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Bengali / bengali
Programming language: Python
Design country: Bangladesh / Bangladesh
Licence: CC BY-NC-SA 4.0 / CC BY-NC-SA 4.0
Based on: BERT / BERT
Repository: https://github.com/csebuetnlp/banglabert
Reference: Bhattacharjee, A., Hasan, T., Samin, K., Islam, M. S., Rahman, M. S., Iqbal, A., & Shahriyar, R. (2021). BanglaBERT : Combating embedding barrier in multilingual models for low-resource language understanding. arXiv:2101.00204 [cs]. http://arxiv.org/abs/2101.00204
Bantu / langue bantoue
Broader concept: natural language / langage naturel
IETF language tag: bnt
ISO 639-2: bnt
ISO 639-5: bnt
Bari / bari
Also known as: Karo§§Kutuk / 
Broader concept: natural language / langage naturel
IETF language tag: bfa
ISO 639-3: bfa
Bashkir / bachkir
Broader concept: natural language / langage naturel
IETF language tag: ba
ISO 639-1: ba
ISO 639-2: bak
ISO 639-3: bak
Basque / basque
Broader concept: natural language / langage naturel
IETF language tag: eu
ISO 639-1: eu
ISO 639-2: bas§§eus
ISO 639-3: eus
Bavarian / bavarois
Also known as: Austrian§§Austrian-Bavarian§§Bavarian German / austro-bavarois
Broader concept: German / allemand
IETF language tag: bar
ISO 639-3: bar
Belanda Viri / belanda viri
Also known as: BGamba§§Belanda§§Biri§§Bviri§§Gumba§§Mbegumba§§Mvegumba / bGamba§§belanda§§biri§§bviri§§gumba§§mbegumba§§mvegumba
Broader concept: natural language / langage naturel
ISO 639-3: bvi
Belarusian / biélorusse
Broader concept: natural language / langage naturel
IETF language tag: be
ISO 639-1: be
ISO 639-2: bel
ISO 639-3: bel
Bemba / bemba
Also known as: Chiwemba§§Cibemba§§Ichibemba§§Icibemba / chibemba§§ichibemba
Broader concept: Bantu / langue bantoue
IETF language tag: bem
ISO 639-2: bem
ISO 639-3: bem
Bengali / bengali
Also known as: Bangla / bangla
Broader concept: natural language / langage naturel
IETF language tag: bn
ISO 639-1: bn
ISO 639-2: ben
ISO 639-3: ben
Berber / berbère
Also known as: Amazigh§§tamazight / tamazight
Broader concept: natural language / langage naturel
IETF language tag: ber
ISO 639-2: ber
ISO 639-5: ber
Bhojpuri / bhojpuri
Broader concept: natural language / langage naturel
IETF language tag: bho
ISO 639-2: bho
ISO 639-3: bho
bidirectional long-short term memory / mémoire court et long terme bidirectionnelle
Also known as: BLSTM§§bi-directional long-short term memory / BLSTM
Broader concept: long short-term memory / mémoire court et long terme
Implemented by: ABLTagger§§ELMo§§Flair§§GROBID§§LangMoDHS§§jPTDP / ABLTagger§§ELMo§§Flair§§GROBID§§LangMoDHS§§jPTDP
BigARTM / BigARTM
Definition: Fast topic modeling platform.
Définition : Plateforme de modélisation de topiques rapide.
Broader concept: Python library / librairie Python
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: additive regularization of topic models / régularisation additive de modèles de topiques
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Russia / Russie
Repository: https://github.com/bigartm/bigartm
Reference: Vorontsov, K., Frei, O., Apishev, M., Romov, P., & Dudarenko, M. (2015). BigARTM: Open source library for regularized multimodal topic modeling of large collections. In M. Yu. Khachay, N. Konstantinova, A. Panchenko, D. Ignatov, & V. G. Labunets (Eds.), Analysis of Images, Social Networks and Texts (Vol. 542, pp. 370–381). Springer International Publishing. https://doi.org/10.1007/978-3-319-26123-2_36
BigScience RAIL License v1.0 / BigScience RAIL License v1.0
Broader concept: license / licence
Bihari / bihari
Broader concept: natural language / langage naturel
ISO 639-1: bh
ISO 639-2: bih
ISO 639-3: bih
BioALBERT / BioALBERT
Also known as: Biomedical ALBERT / 
Definition: "a domain-speciﬁc adaptation of A Lite Bidirectional Encoder Representations from Transformers (ALBERT), trained on biomedical (PubMed and PubMed Central) and clinical (MIMIC-III) corpora and ﬁne-tuned for 6 different tasks across 20 benchmark datasets." (Naseem et al., 2021).
Définition : Modèle de langage basé sur ALBERT et entraîné sur des corpus biomédicaux (PubMed et PubMed Central) et cliniques (MIMIC-III).
Broader concept: large language model / grand modèle de langue
Application field: biology§§medicine / biologie§§médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: Australia / Australie
Repository: https://github.com/usmaann/BioALBERT
Reference: Naseem, U., Dunn, A. G., Khushi, M., & Kim, J. (2021). Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT. https://arxiv.org/abs/2107.04374v1
BioBERT / BioBERT
Definition: "a pre-trained language representation model for the biomedical domain.' (Lee et al., 2020, p. 1235).
Définition : « modèle de représentation linguistique pré-entraîné pour le domaine biomédical. » (Lee et al., 2020, p. 1235).
Broader concept: large language model / grand modèle de langue
Application field: biology§§medicine / biologie§§médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Perl§§Python
Design country: South Korea / Corée du Sud
Licence: Apache License Version 2.0 / Apache License Version 2.0
Based on: BERT / BERT
Base of: GreenBioBERT / GreenBioBERT
Repository: https://github.com/dmis-lab/biobert
Reference: Lee, J., Yoon, W., Kim, S., Kim, D., Kim, S., So, C. H., & Kang, J. (2019). BioBERT : A pre-trained biomedical language representation model for biomedical text mining. Bioinformatics, btz682. https://doi.org/10.1093/bioinformatics/btz682
BioELMo / BioELMo
Definition: Language model based on ELMo for the biomedical domain.
Définition : Modèle de langage basé sur ELMo pour le domaine biomédical.
Broader concept: large language model / grand modèle de langue
Application field: biology§§medicine / biologie§§médecine
Tasks performed: word embedding / plongement lexical
Input languages: English / anglais
Design country: United States / États-Unis
Based on: ELMo / ELMo
Repository: https://github.com/Andy-jqa/bioelmo
Reference: Jin, Q., Dhingra, B., Cohen, W. W., & Lu, X. (2019). Probing biomedical embeddings from language models. arXiv:1904.02181 [cs]. http://arxiv.org/abs/1904.02181
BioLemmatizer / BioLemmatizer
Definition: The BioLemmatizer is a domain-specific lemmatization tool for the morphological analysis of biomedical literature.
Définition : BioLemmatizer est un outil de lemmatisation spécifique pour l'analyse morphologique de la littérature biomédicale.
Broader concept: Java library / librairie Java
Application field: biology§§medicine / biologie§§médecine
Tasks performed: lemmatization§§PoS tagging / lemmatisation§§étiquetage morpho-syntaxique
Input languages: English / anglais
Input data: XML
Programming language: Java
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country:  / États-Unis
Licence: Modified BSD / BSD modifiée
Repository: https://sourceforge.net/projects/biolemmatizer/
Reference: Liu, H., Christiansen, T., Baumgartner, W. A., & Verspoor, K. (2012). BioLemmatizer : A lemmatization tool for morphological processing of biomedical text. Journal of Biomedical Semantics, 3, 3. https://doi.org/10.1186/2041-1480-3-3
BioMedBERT / BioMedBERT
Definition: A pre-trained language model on biomedical texts, based on BERT, for question answering and retrieval tasks.
Définition : Modèle de langue pré-entraîné sur des textes biomédicaux, et basé sur BERT, pour la réalisation de tâches de questions-réponses et de recherche d'informations.
Broader concept: large language model / grand modèle de langue
Application field: biology§§medicine / biologie§§médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Licence: MIT License / licence MIT
Based on: BERT / BERT
Repository: https://github.com/BioMedBERT/biomedbert
Reference: Chakraborty, S., Bisong, E., Bhatt, S., Wagner, T., Elliott, R., & Mosconi, F. (2020). BioMedBERT : A Pre-trained Biomedical Language Model for QA and IR. 669‑679. https://doi.org/10.18653/v1/2020.coling-main.59
BioMegatron / BioMegatron
Definition: A language model based on Megatron-LM pre-trained on biomedical texts.
Définition : Modèle de langage basé sur Megatron-LM et pré-entraîné sur des textes biomédicaux.
Broader concept: large language model / grand modèle de langue
Application field: biology / biologie
Tasks performed: word embedding / plongement lexical
Input languages: English / anglais
Programming language: Python
Design country: United States / États-Unis
Based on: Megatron-LM / Megatron-LM
Reference: Shin, H.-C., Zhang, Y., Bakhturina, E., Puri, R., Patwary, M., Shoeybi, M., & Mani, R. (2020). BioMegatron: Larger biomedical domain language model. ArXiv:2010.06060 [Cs]. http://arxiv.org/abs/2010.06060
BioNLP / BioNLP
Definition: BioNLP is an initiative by the Center for Computational Pharmacology at the University of Colorado Denver to create and distribute code, software, and data for applying natural language processing techniques to biomedical texts.
Définition : BioNLP est une initiative du Centre de Pharmacologie computationnelle de l'Université du Colorado à Denver visant à créer et à distribuer du code, des logiciels et des données pour l'application de techniques de traitement du langage naturel aux textes biomédicaux.
Broader concept: software application / application logicielle
Application field: biology§§medicine / biologie§§médecine
Tasks performed: information extraction§§lemmatization§§parsing§§text annotation§§text categorization / extraction d'information§§lemmatisation§§analyse syntaxique§§annotation textuelle§§catégorisation de textes
Input languages: English / anglais
Programming language: Java
Design country: United States / États-Unis
Licence: MPL v1.1 / MPL v1.1
Repository: http://bionlp.sourceforge.net/
Reference: Bossy R. et al. Overview of the gene regulation network and the bacteria biotope tasks in BioNLP13 shared task, (2015), BMC Bioinformatics 16, S1 https://doi.org/10.1186/1471-2105-16-S10-S1§§Bossy R., Deléger L., Chaix E., Ba M. & Nédellec C. Bacteria Biotope at BioNLP Open Shared Tasks 2019, (2019), in Proceedings of The 5th Workshop on BioNLP Open Shared Tasks 121131 (Association for Computational Linguistics, 2019). https://doi.org/10.18653/v1/D19-5719§§Jin Dong Kim, Tomoko Ohta, Sampo Pyysalo, Yoshinobu Kano, Junichi Tsujii, (2011), Computational Intelligence, vol. 27, n°4, pp. 513-540. https://doi.org/10.1111/j.1467-8640.2011.00398.x
BioTagger / BioTagger
Definition: Penn's BioTagger is a software suite which currently supports three types of entities: gene entities, genomic variations entities and malignancy type entities. The core of the tagger is derived from the machine learning package MALLET.
Définition : Penn's BioTagger est une suite logicielle qui prend actuellement en charge trois types d'entités : les entités géniques, les entités de variations génomiques et les entités de type malignité. Le cœur du tagger est dérivé du package d'apprentissage automatique MALLET.
Broader concept: Java library / librairie Java
Application field: biology / biologie
Tasks performed: named entity recognition / reconnaissance d'entités nommées
Implements: conditional random field / champ aléatoire conditionnel
Input languages: English / anglais
Input data: .txt
Programming language: Java
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: United States / États-Unis
Licence: free to use license / licence libre d'utilisation
biology / biologie
Broader concept: scientific knowledge / connaissances scientifiques
Application field: MarkerGenie / MarkerGenie
Application field of: ABNER§§AbLang§§BioALBERT§§BioBERT§§BioELMo§§BioLemmatizer§§BioMedBERT§§BioMegatron§§BioNLP§§BioTagger§§BioMed-RoBERTa§§BlueBERT§§Bluima§§DrBERT§§Egas§§GNormPlus§§Galactica§§Galaxy§§GenSLMs§§Genia tagger§§Genomic ULMFit§§GreenBioBERT§§KeBioLM§§LangMoDHS§§Mol-BERT§§MutationFinder§§NCBI Text Mining Tools§§NILINKER§§OGER §§OuBioBERT§§ProkBERT§§ProteinBERT§§PubMedBERT§§PubRunner§§PubTator§§SciFive§§SemRep§§Stanza§§Textpresso Central§§Turku Event Extraction System§§UmlsBERT§§medBERT§§nanoBERT§§sciBERT§§ScispaCy / ABNER§§AbLang§§BioALBERT§§BioBERT§§BioELMo§§BioLemmatizer§§BioMedBERT§§BioMegatron§§BioNLP§§BioTagger§§BioMed-RoBERTa§§BlueBERT§§Bluima§§DrBERT§§Egas§§GNormPlus§§Galactica§§Galaxy§§GenSLMS§§Genia tagger§§Genomic ULMFit§§GreenBioBERT§§KeBioLM§§LangMoDHS§§Mol-BERT§§MutationFinder§§NCBI Text Mining Tools§§NILINKER§§OGER§§OuBioBERT§§ProkBERT§§ProteinBERT§§PubMedBERT§§PubRunner§§PubTator§§SciFive§§SemRep§§Stanza§§Textpresso Central§§Turku Event Extraction System§§UmlsBERT§§medBERT§§nanoBERT§§sciBERT§§ScispaCy
BioMed-RoBERTa / BioMed-RoBERTa
Definition: A RoBERTa Language model pretrained on biomedical texts.
Définition : Modèle de langage basé sur RoBERTa pré-entraîné sur des textes biomédicaux.
Broader concept: large language model / grand modèle de langue
Application field: biology§§medicine / biologie§§médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: United States / États-Unis
Based on: RoBERTa / RoBERTa
Reference: Gururangan, S., Marasović, A., Swayamdipta, S., Lo, K., Beltagy, I., Downey, D., & Smith, N. A. (2020). Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks. ArXiv:2004.10964 [Cs]. http://arxiv.org/abs/2004.10964
Bishnupriya Manipuri / bishnupriya manipuri
Also known as: Manipuri Bishnupriya / bishnupriya,
Broader concept: natural language / langage naturel
IETF language tag: bpy
ISO 639-2: inc
ISO 639-3: bpy
Bislama / bichelamar
Also known as:  / bichlamar§§bislama
Broader concept: natural language / langage naturel
IETF language tag: bi
ISO 639-1: bi
ISO 639-2: bis
ISO 639-3: bis
BLOOM / BLOOM
Also known as: BigScience Large Open-science Open-access Multilingual Language Model / 
Definition: A large language model, able to generate text in 46 natural languages and 13 programming languages.
Définition : Grand modèle de langage, capable de générer des textes dans 46 langues naturelles et 13 langage de programmation.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Akan§§Arabic§§Assamese§§Bambara§§Basque§§Bengali§§Catalan§§Chichewa§§English§§Fon§§French§§Ganda§§Gujarati§§Hindi§§Igbo§§Indonesian§§Kannada§§Kikuyu§§Kinyarwanda§§Kirundi§§Lingala§§Malayalam§§Marathi§§Nepali§§Northern Sotho§§Odia§§Portuguese§§Punjabi§§Shona§§Sotho§§Spanish§§Swahili§§Tamil§§Telugu§§Tsonga§§Tswana§§Tumbuka§§Twi§§Urdu§§Vietnamese§§Xhosa§§Yoruba§§Zulu / akan§§arabe§§assamais§§bambara§§basque§§bengali§§catalan§§chewa§§anglais§§fon§§français§§ganda§§gujarati§§hindi§§igbo§§indonésien§§kannada§§kikuyu§§kinyarwanda§§kirundi§§lingala§§malayalam§§marathi§§népalais§§sotho du Nord§§odia§§portugais§§pendjabi§§shona§§sotho du Sud§§espagnol§§swahili§§tamoul§§télougou§§tsonga§§tswana§§tumbuka§§twi§§ourdou§§vietnamien§§xhosa§§yoruba§§zoulou
Programming language: Python
Interface: command-line interface / interface en ligne de commande
Licence: Responsible AI License / Responsible AI License
Repository: https://huggingface.co/bigscience/bloom
BlueBERT / BlueBERT
Definition: A BERT language model pre-trained on PubMed abstracts and clinical notes (MIMIC-III).
Définition : Modèle de langage BERT pré-entrainé sur les résumés de PubMed et les notes cliniques (MIMIC-III).
Broader concept: large language model / grand modèle de langue
Application field: biology§§medicine / biologie§§médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: United States / États-Unis
Licence: free to use license / licence libre d'utilisation
Based on: BERT / BERT
Repository: https://github.com/ncbi-nlp/bluebert
Reference: Peng, Y., Yan, S., & Lu, Z. (2019). Transfer learning in biomedical natural language processing : An evaluation of BERT and ELMo on ten benchmarking datasets. https://arxiv.org/abs/1906.05474v2
Bluima / Bluima
Definition: Bluima is a Natural Language Processing toolkit for neuroscience.
Définition : Bluima est une boîte à outils de traitement du langage naturel pour les neurosciences.
Broader concept: Java library / librairie Java
Application field: biology / biologie
Tasks performed: lemmatization§§named entity recognition§§PoS tagging§§sentence splitting§§tokenization / lemmatisation§§reconnaissance d'entités nommées§§étiquetage morpho-syntaxique§§découpage de phrases§§tokenisation
Input languages: English / anglais
Input data: XML§§pdf
Programming language: Java
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Switzerland / Suisse
Licence: Apache License Version 2.0 / Apache License Version 2.0
Repository: https://github.com/BlueBrain/bluima
Reference: Richardet, R., Chappelier, J.-C., & Telefont, M. (2013). Bluima : A UIMA-based NLP toolkit for neuroscience. CEUR Workshop Proceedings, 1038, 34‑41.
Boost software license / licence logicielle Boost
Broader concept: license / licence
Is licence for: MITIE / MITIE
boosting / boosting
Definition: Boosting is an ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine learning algorithms that convert weak learners to strong ones. (Wikipedia, retrieved on 2021/07/07)
Définition : boosting est un méta-algorithme d'ensemble destiné principalement à réduire les biais, ainsi que la variance dans l'apprentissage supervisé, et une famille d'algorithmes d'apprentissage automatique qui convertissent les apprenants faibles en apprenants forts. (Wikipédia, récupéré le 07/07/2021).
Broader concept: classification algorithm / algorithme de classification
Implemented by: Massive Online Analysis / Massive Online Analysis
Bora / bora
Broader concept: natural language / langage naturel
IETF language tag: boa
ISO 639-3: boa
Bosnian / bosnien
Broader concept: natural language / langage naturel
IETF language tag: bs
ISO 639-1: bs
ISO 639-2: bos
ISO 639-3: bos
Brat / Brat
Definition: Brat is an online environment for collaborative text annotation.
Définition : Brat est un environnement en ligne pour l'annotation collaborative de textes.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: concordance analysis§§information extraction§§named entity recognition§§relation extraction / analyse de concordance§§extraction d'information§§reconnaissance d'entités nommées§§extraction de relations
Interface: web user interface§§desktop graphical user interface / interface utilisateur web§§interface utilisateur graphique desktop
Design country: Japan§§United Kingdom / Japon§§Royaume-Uni
Licence: MIT License / licence MIT
Reference: Pontus Stenetorp, Goran Topi, Sampo Pyysalo, Tomoko Ohta, Jin-Dong Kim and Jun'ichi Tsujii BioNLP Shared Task 2011: Supporting Resources, (2001), In Proceedings of BioNLP Shared Task 2011 Workshop. https://aclanthology.org/W11-1816.pdf
Brazilian Portuguese / portugais du Brésil
Broader concept: Portuguese / portugais
IETF language tag: pt-BR
Breton / breton
Broader concept: natural language / langage naturel
IETF language tag: br
ISO 639-1: br
ISO 639-2: bre
ISO 639-3: bre
Buginese / bugi
Also known as: Bugis / bouguinais
Broader concept: natural language / langage naturel
IETF language tag: bug
ISO 639-2: bug
ISO 639-3: bug
Bulgarian / bulgare
Broader concept: natural language / langage naturel
IETF language tag: bg
ISO 639-1: bg
ISO 639-2: bul
ISO 639-3: bul