datasets-CNRS/ThesoTM huggingface dataset:
TinyBERT / TinyBERT
Definition: "TinyBERT is 7.5x smaller and 9.4x faster on inference than BERT-base and achieves competitive performances in the tasks of natural language understanding. It performs a novel transformer distillation at both the pre-training and task-specific learning stages." (source: https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/TinyBERT).
Définition : « TinyBERT est 7,5 fois plus petit et 9,4 fois plus rapide que la base BERT pour l'inférence. » (source : https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/TinyBERT).
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: China / Chine
Based on: BERT / BERT
Repository: https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/TinyBERT
Reference: Jiao, X., Yin, Y., Shang, L., Jiang, X., Chen, X., Li, L., Wang, F., & Liu, Q. (2020). TinyBERT : Distilling BERT for natural language understanding. arXiv:1909.10351 [cs]. http://arxiv.org/abs/1909.10351
Tiv / tiv
Broader concept: natural language / langage naturel
IETF language tag: tiv
ISO 639-2: tiv
ISO 639-3: tiv
TnT / TnT
Also known as: Trigrams'n'Tags / Trigrams'n'Tags
Definition: TnT realizes statistical Part-of-Speech Tagging.
Définition : TnT permet un étiquetage statistique de parties du discours.
Broader concept: C library / librairie C
Application field: generic / générique
Tasks performed: PoS tagging / étiquetage morpho-syntaxique
Input languages: English§§German / anglais§§allemand
Programming language: C
Platforms: Linux§§Solaris§§macOS
Interface: command-line interface / interface en ligne de commande
Design country:  / Allemagne
Licence: free to use license / licence libre d'utilisation
Uses software: non-specified UNIX / UNIX non spécifié
Toba / toba
Also known as: Chaco Sur§§Kom§§Qom§§Toba Qom§§Toba Sur / qom§§qomlaqtaq§§tob
Broader concept: natural language / langage naturel
IETF language tag: tob
ISO 639-3: tob
Tohoku-BERT / Tohoku-BERT
Definition: A BERT model for Japanese texts.
Définition : Modèle BERT pour les textes en japonais.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Japanese / japonais
Programming language: Python
Design country: Japan / Japon
Licence: Apache License Version 2.0§§CC BY-NC-SA 3.0 / Apache License Version 2.0§§CC BY-NC-SA 3.0
Based on: BERT / BERT
Repository: https://github.com/cl-tohoku/bert-japanese
Tojolabʼal / tojolabal
Broader concept: natural language / langage naturel
ISO 639-3: toj
Tok Pisin / tok pisin
Also known as: New Guinea Pidgin / néo-mélanésien
Broader concept: natural language / langage naturel
ISO 639-2: tpi
ISO 639-3: tpi
Tonga / chitonga
Also known as:  / tonga
Broader concept: Bantu / langue bantoue
IETF language tag: toi
ISO 639-2: bnt
ISO 639-3: toi
Top2Vec / Top2Vec
Definition: "Top2Vec learns jointly embedded topic, document and word vectors." (source: https://github.com/ddangelov/Top2Vec).
Définition : « Top2Vec apprend conjointement des plongements de vecteurs de topiques, de documents et de mots » (source : https://github.com/ddangelov/Top2Vec).
Broader concept: Python library / librairie Python
Application field: generic / générique
Tasks performed: document embedding§§word embedding§§topic detection / plongement de documents§§plongement lexical§§identification de topics
Implements: universal sentence encoder§§doc2vec / encodeur universel de phrases§§doc2vec
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Canada / Canada
Licence: Modified BSD / BSD modifiée
Based on: BERT / BERT
Repository: https://github.com/ddangelov/Top2Vec
Reference: Angelov, D. (2020). Top2Vec: Distributed representations of topics (arXiv:2008.09470). arXiv. https://doi.org/10.48550/arXiv.2008.09470
topic modelling algorithm / algorithme de modélisation de topiques
Also known as: topic model§§topic modeling§§topic modelling / modèle de topiques§§topic modeling
Broader concept: algorithm / algorithme
TopicModels.jl / TopicModels.jl
Definition: "implements utilities for reading and manipulating data commonly associated with topic models as well as inference and prediction procedures for such models." (source: https://www.juliapackages.com/p/topicmodels).
Définition : Paquet Julia pour la modélisation de topiques.
Broader concept: Julia library / librairie Julia
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: latent Dirichlet allocation / allocation de Dirichlet latente
Programming language: Julia
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: MIT License / licence MIT
Repository: https://github.com/slycoder/TopicModels.jl§§https://www.juliapackages.com/p/topicmodels
TransPolymer / TransPolymer
Definition: A transformer-based language model for polymer property predictions.
Définition : Modèle de langage de type transformeur pour la prédiction de propriétés des polymères.
Broader concept: large language model / grand modèle de langue
Application field: chemistry / chimie
Implements: transformer / transformeur
Programming language: Python
Design country: United States / États-Unis
Licence: MIT License / licence MIT
Based on: RoBERTa / RoBERTa
Repository: https://github.com/ChangwenXu98/TransPolymer
Reference: Xu, C., Wang, Y., & Barati Farimani, A. (2023). TransPolymer: A Transformer-based language model for polymer property predictions. Npj Computational Materials, 9(1), Article 1. https://doi.org/10.1038/s41524-023-01016-5
TreeTagger / TreeTagger
Definition: The TreeTagger is a tool for annotating text with part-of-speech and lemma information.
Définition : Le TreeTagger est un outil permettant d'annoter des textes avec des informations sur les parties du discours et les lemmes.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: chunking§§lemmatization§§PoS tagging / chunking§§lemmatisation§§étiquetage morpho-syntaxique
Implements: decision tree / arbre de décision
Input languages: Bulgarian§§Chinese§§Coptic§§Czech§§Danish§§Dutch§§English§§Estonian§§French§§Galician§§German§§Greek§§Italian§§Latin§§Norwegian§§Polish§§Portuguese§§Romanian§§Russian§§Slovak§§Slovenian§§Spanish§§Swahili§§Swedish / bulgare§§chinois§§copte§§tchèque§§danois§§néerlandais§§anglais§§estonien§§français§§galicien§§allemand§§grec§§italien§§latin§§norvégien§§polonais§§portugais§§roumain§§russe§§slovaque§§slovène§§espagnol§§swahili§§suédois
Platforms: Android§§Linux§§Windows§§macOS
Interface: web user interface§§graphical user interface§§command-line interface / interface utilisateur web§§interface utilisateur graphique§§interface en ligne de commande
Design country: Germany / Allemagne
Licence: proprietary commercial software license§§free to use license / licence de logiciel commercial propriétaire§§licence libre d'utilisation
Is software for: Hyperbase§§KIWI§§TagAnt§§TermoStat§§Termsuite§§Textable§§koRpus / Hyperbase§§KIWI§§TagAnt§§TermoStat§§Termsuite§§Textable§§koRpus
Reference: Helmut Schmid, Probabilistic Part-of-Speech Tagging Using Decision Trees, (1994), Proceedings of International Conference on New Methods in Language Processing, Manchester, UK. https://doi.org/10.1007/BFb0026668§§Helmut Schmid, Improvements in Part-of-Speech Tagging with an Application to German, (1995), Proceedings of the ACL SIGDAT-Workshop. Dublin, Ireland. https://doi.org/10.1007/978-94-017-2390-9_2§§Lavrentiev A. M., Suvorova (Ananyeva) M. I., Fokina A. I. & Chepovskiy A. M. A new toolkit for natural text processing with the TXM platform and its application to a corpus for analysis of texts propagating extremist views, (2018), LIC 16, 19-31 . https://doi.org/10.25205/1818-7935-2018-16-3-19-31
TreeTagger output format / format de sortie de TreeTagger
Broader concept: data format specification / specification du format de données
Is specified data input of: YaTeA / YaTeA
Tropes / Tropes
Definition: Tropes provides semantic analysis of texts.
Définition : Tropes permet l'analyse sémantique de textes.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: corpus analysis§§relation extraction§§text annotation§§visualization / analyse de corpus§§extraction de relations§§annotation textuelle§§visualisation
Input languages: French / français
Input data: .txt
Platforms: Windows
Interface: desktop graphical user interface / interface utilisateur graphique desktop
Design country: France / France
Licence: free to use license / licence libre d'utilisation
Tsonga / tsonga
Also known as: Xitsonga / xitsonga
Broader concept: natural language / langage naturel
IETF language tag: ts
ISO 639-1: ts
ISO 639-2: tso
ISO 639-3: tso
Tswana / tswana
Also known as: Sechuana§§Setswana / bechuana§§beetjuans§§chuana§§chwana§§coana§§cuana§§sechuana§§secoana§§secwana§§siwaha§§tshwana
Broader concept: Bantu / langue bantoue
IETF language tag: tn
ISO 639-1: tn
ISO 639-2: tsn
ISO 639-3: tsn
Tumbuka / tumbuka
Also known as:  / toumbouka
Broader concept: natural language / langage naturel
IETF language tag: tum
ISO 639-2: tum
ISO 639-3: tum
Turkish / turc
Broader concept: natural language / langage naturel
IETF language tag: tr
ISO 639-1: tra
ISO 639-2: tur
ISO 639-3: tur
Turkmen / turkmène
Also known as: Turkmen Turkic§§Turkmen Turkish / 
Broader concept: natural language / langage naturel
IETF language tag: tk
ISO 639-1: tk
ISO 639-2: tuk
ISO 639-3: tuk
Turku Event Extraction System / Turku Event Extraction System
Also known as: TESS / TESS
Definition: "Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text." (source: https://github.com/jbjorne/TEES).
Définition : « système de traitement du langage naturel, libre et open source, pour l’extraction d’événements et de relations dans des textes biomédicaux. » » (source: https://github.com/jfilter/german-lemmatizer).
Broader concept: Python library / librairie Python
Application field: biology§§medicine / biologie§§médecine
Tasks performed: dependency parsing§§event detection§§relation extraction / analyse en dépendances§§détection d'évènements§§extraction de relations
Input languages: English§§Finnish§§Swedish / anglais§§finnois§§suédois
Programming language: Perl§§Python
Platforms: Linux§§non-specified UNIX
Interface: command-line interface / interface en ligne de commande
Design country: Finland / Finlande
Licence: GNU GPL v3 / GNU GPL v3
Repository: https://github.com/jbjorne/TEES
Tuvaluan / tuvaluan
Also known as: Tuvalu / 
Broader concept: natural language / langage naturel
ISO 639-2: tvl
ISO 639-3: tvl
Tuvan / touvain
Also known as: Tuvinian / langue touvine§§touvinien
Broader concept: natural language / langage naturel
IETF language tag: tyv
ISO 639-2: tyv
ISO 639-3: tyv
Tweet NLP / Tweet NLP
Definition: TweetNLP provides a tokenizer, a part-of-speech tagger, hierarchical word clusters, and a dependency parser for tweets, along with annotated corpora and web-based annotation tools.
Définition : TweetNLP fournit un tokenizer, un tagueur de parties du discours, des clusters de mots hiérarchiques et un analyseur de dépendance pour les tweets, ainsi que des corpus annotés et des outils d'annotation en ligne.
Broader concept: Java library / librairie Java
Application field: social networks / réseaux sociaux
Tasks performed: dependency parsing§§PoS tagging§§tokenization / analyse en dépendances§§étiquetage morpho-syntaxique§§tokenisation
Implements: hierarchical clustering / partitionnement hiérarchique
Input languages: English / anglais
Programming language: Java
Interface: command-line interface / interface en ligne de commande
Design country: United States / États-Unis
Licence: Apache License Version 2.0§§GNU GPL v3§§free to use license / Apache License Version 2.0§§GNU GPL v3§§licence libre d'utilisation
Twi / twi
Also known as: Akan kasa§§Akan-speak / asante§§tchi
Broader concept: Akan / akan
IETF language tag: tw
ISO 639-1: tw
ISO 639-2: twi
ISO 639-3: twi
Twitmo / Twitmo
Definition: "Tailored for topic modeling with tweets and fit for visualization tasks in R. Collect, pre-process and analyze the contents of tweets using LDA and structural topic models (STM). Comes with visualizing capabilities like tweet and hashtag maps and built-in support for 'LDAvis'. (source: https://cran.r-project.org/web/packages/Twitmo/index.html).
Définition : Paquet R pour la modélisation de topiques de tweets.
Broader concept: R package / paquet R
Application field: social networks / réseaux sociaux
Tasks performed: topic detection§§visualization / identification de topics§§visualisation
Implements: latent Dirichlet allocation§§structural topic modeling / allocation de Dirichlet latente§§modélisation de topiques structurale
Programming language: R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Germany / Allemagne
Licence: MIT License / licence MIT
Uses software: R / R
Repository: https://cran.r-project.org/web/packages/Twitmo/index.html§§https://github.com/abuchmueller/Twitmo
Tzotzil / tzotzil
Broader concept: natural language / langage naturel
IETF language tag: tzo
ISO 639-3: tzo
U-compare / U-compare
Definition: U-Compare is an integrated text mining/natural language processing system based on the UIMA Framework.
Définition : U-Compare est un système intégré de fouille de textes et de traitement du langage naturel basé sur le framework UIMA.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: chunking§§event detection§§lemmatization§§named entity recognition§§PoS tagging§§tokenization / chunking§§détection d'évènements§§lemmatisation§§reconnaissance d'entités nommées§§étiquetage morpho-syntaxique§§tokenisation
Input languages: English / anglais
Programming language: Java
Interface: desktop graphical user interface / interface utilisateur graphique desktop
Design country: Japan / Japon
Licence: proprietary commercial software license§§GNU LGPL / licence de logiciel commercial propriétaire§§GNU LGPL
Reference: Riza Theresa Batista-Navarro, Georgios Kontonatsios, Claudiu Mihil, Paul Thompson, Rafal Rak, Raheel Nawaz, Ioannis Korkontzelos, Sophia Ananiadou Facilitating the Analysis of Discourse Phenomena in an Interoperable NLP Platform, (2013), Computational Linguistics and Intelligent Text Processing, vol.7816, pp.559-571. https://doi.org/10.1007/978-3-642-37247-6_45§§Yoshinobu Kano, William A. Baumgartner Jr, Luke McCrohon, Sophia Ananiadou, K. Bretonnel Cohen, Lawrence Hunter, Jun'ichi Tsujii U-Compare: share and compare text mining tools with UIMA, (2009), Bioinformatics, vol. 25, n 15, pp. 1997-1998, https://doi.org/10.1093/bioinformatics/btp28
UAIC NLP / UAIC NLP
Definition: Tools for natural language processing.
Définition : Tools for natural language processing.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: anaphora resolution§§chunking§§named entity recognition§§parsing§§PoS tagging / résolution d'anaphore§§chunking§§reconnaissance d'entités nommées§§analyse syntaxique§§étiquetage morpho-syntaxique
Input languages: Romanian / roumain
Design country: Romania / Roumanie
Licence: free to use license / licence libre d'utilisation
UDPipe / UDPipe
Definition: Trainable pipeline for tokenizing, tagging, lemmatizing and parsing Universal Treebanks and other CoNLL-U files.
Définition : Pipeline entraînable pour la tokénisation, l'étiquetage, la lemmatisation et l'analyse syntaxique de corpus annotés universels et d'autres fichiers CoNLL-U.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: dependency parsing§§lemmatization§§PoS tagging§§tokenization / analyse en dépendances§§lemmatisation§§étiquetage morpho-syntaxique§§tokenisation
Input languages: Afrikaans§§Arabic§§Armenian§§Basque§§Belarusian§§Bulgarian§§Catalan§§Chinese§§Coptic§§Croatian§§Danish§§Dutch§§English§§Estonian§§Finnish§§French§§Galician§§German§§Gothic§§Greek§§Hebrew§§Hindi§§Hungarian§§Indonesian§§Irish§§Italian§§Japanese§§Korean§§Latin§§Latvian§§Lithuanian§§Maltese§§Marathi§§Norwegian§§Persian§§Polish§§Portuguese§§Romanian§§Russian§§Scottish Gaelic§§Serbian§§Slovak§§Slovenian§§Spanish§§Swedish§§Tamil§§Telugu§§Turkish§§Ukrainian§§Uyghur§§Vietnamese§§Wolof§§.txt / afrikaans§§arabe§§arménien§§basque§§biélorusse§§bulgare§§catalan§§chinois§§copte§§croate§§danois§§néerlandais§§anglais§§estonien§§finnois§§français§§galicien§§allemand§§gotique§§grec§§hébreu§§hindi§§hongrois§§indonésien§§irlandais§§italien§§japonais§§coréen§§latin§§letton§§lithuanien§§maltais§§marathi§§norvégien§§persan§§polonais§§portugais§§roumain§§russe§§gaélique écossais§§serbe§§slovaque§§slovène§§espagnol§§suédois§§tamoul§§télougou§§turc§§ukrainien§§ouïghour§§vietnamien§§wolof§§.txt
Programming language: Java§§C++§§Perl
Platforms: Linux§§Windows§§macOS
Interface: web user interface§§REST service§§command-line interface§§application programming interface / interface utilisateur web§§service REST§§interface en ligne de commande§§interface de programmation d’application
Design country: Czech Republic / République tchèque
Licence: MPL v2.0 / MPL v2.0
UTH-BERT / UTH-BERT
Definition: A BERT language model pre-trained on clinical texts in Japanese.
Définition : Modèle de langage BERT pré-entraîné sur des textes cliniques en japonais.
Broader concept: large language model / grand modèle de langue
Application field: medicine / médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Japanese / japonais
Programming language: Python
Design country: Japan / Japon
Based on: BERT / BERT
Repository: https://github.com/jinseikenai/uth-bert
Reference: Kawazoe, Y., Shibata, D., Shinohara, E., Aramaki, E., & Ohe, K. (2021). A clinical specific BERT developed using a huge Japanese clinical text corpus. PLOS ONE, 16(11), e0259763. https://doi.org/10.1371/journal.pone.0259763
Ukrainian / ukrainien
Broader concept: natural language / langage naturel
IETF language tag: uk
ISO 639-1: uk
ISO 639-2: ukr
ISO 639-3: ukr
ULMFiT / ULMFiT
Also known as: Universal Language Model FIne-Tuning / 
Definition: "ULMFiT is an effective transfer learning method that can be applied to any task in NLP" (source: https://nlp.fast.ai/category/classification.html)
Définition : « ULMFiT est une méthode efficace d'apprentissage par transfert qui peut être appliquée à n'importe quelle tâche de TAL. » (source : https://nlp.fast.ai/category/classification.html)
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: long short-term memory / mémoire court et long terme
Input languages: English / anglais
Design country: Ireland§§United States / Irlande§§États-Unis
Base of: Genomic ULMFit / Genomic ULMFit
Reference: Howard, J., & Ruder, S. (2018). Universal language model fine-tuning for text classification. http://arxiv.org/abs/1801.06146
UmBERTo / UmBERTo
Definition: A language model based on RoBERTa for Italian.
Définition : Modèle de langage basé sur RoBERTa pour l'italien.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Italian / italien
Programming language: Python
Design country: Italy / Italie
Licence: MIT License / licence MIT
Based on: RoBERTa / RoBERTa
Base of: FARM / FARM
Repository: https://github.com/musixmatchresearch/umberto
Umbundu / umbundu
Also known as: South Mbundu / oumboundou
Broader concept: natural language / langage naturel
IETF language tag: umb
ISO 639-2: umb
ISO 639-3: umb
UmlsBERT / UmlsBERT
Definition: "contextual embedding model capable of integrating domain knowledge during pre-training. It was trained on biomedical corpora and uses the Unified Medical Language System (UMLS) clinical metathesaurus" (source: https://github.com/gmichalo/UmlsBERT)
Définition : Modèle de langage BERT pour le domaine biomédical et utilisant le métathésaurus UMLS.
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: Canada / Canada
Licence: MIT License / licence MIT
Based on: BERT / BERT
Repository: https://github.com/gmichalo/UmlsBERT
Reference: Michalopoulos, G., Wang, Y., Kaka, H., Chen, H., & Wong, A. (2021). UmlsBERT : Clinical domain knowledge augmentation of contextual embeddings using the unified medical language system metathesaurus. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 1744‑1753. https://doi.org/10.18653/v1/2021.naacl-main.139
UniLM / UniLM
Also known as: UNIfied pre-trained Language Model / 
Definition: Language model "pre-trained using three types of language modeling tasks: unidirectional, bidirectional, and sequence-to-sequence prediction." (Dong et al., 2019).
Définition : Modèle de langage « pré-entraîné à l'aide de trois types de tâches de modélisation du langage : unidirectionnel, bidirectionnel et prédiction de séquence à séquence. » (Dong et al., 2019).
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Licence: MIT License / licence MIT
Repository: https://github.com/microsoft/unilm
Reference: Dong, L., Yang, N., Wang, W., Wei, F., Liu, X., Wang, Y., Gao, J., Zhou, M., & Hon, H.-W. (2019). Unified language model pre-training for natural language understanding and generation. arXiv:1905.03197 [cs]. http://arxiv.org/abs/1905.03197
Unicoder / Unicoder
Definition: "a universal language encoder that is insensitive to different languages" (Huang et al., 2019).
Définition : « encodeur de langage universel insensible aux différentes langues. » (Huang et al., 2019).
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Implements: transformer / transformeur
Programming language: Python
Design country: China / Chine
Licence: MIT License / licence MIT
Repository: https://github.com/microsoft/Unicoder
Reference: Huang, H., Liang, Y., Duan, N., Gong, M., Shou, L., Jiang, D., & Zhou, M. (2019). Unicoder : A universal language encoder by pre-training with multiple cross-lingual tasks. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2485‑2494. https://doi.org/10.18653/v1/D19-1252