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• The CLASSLA-StanfordNLP model for UD dependency parsing of standard Croatian

  3 resources

  The model for UD dependency parsing of standard Croatian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the UD-parsed portion of the hr500k training corpus (http://hdl.handle.net/11356/1183) and using the CLARIN.SI-embed.hr word embeddings (http://hdl.handle.net/11356/1205). The estimated LAS of the parser is ~85.9.

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• VIADAT-GIS

  2 resources

  A VIADAT module; VIADAT-GIS connects the platform with maps. Developed in cooperation with ÚSD AV ČR and NFA.

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• CroSloEngual BERT 1.1

  4 resources

  Trilingual BERT (Bidirectional Encoder Representations from Transformers) model, trained on Croatian, Slovenian, and English data. State of the art tool representing words/tokens as contextually dependent word embeddings, used for various NLP classification tasks by finetuning the model end-to-end. CroSloEngual BERT are neural network weights and configuration files in pytorch format (i.e. to be used with pytorch library). Changes in version 1.1: fixed vocab.txt file, as previous verson had an error causing very bad results during fine-tuning and/or evaluation.

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• The CLASSLA-Stanza model for lemmatisation of standard Croatian 2.1

  2 resources

  The model for lemmatisation of standard Croatian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the hr500k training corpus (http://hdl.handle.net/11356/1792) and using the hrLex inflectional lexicon (http://hdl.handle.net/11356/1232). The estimated F1 of the lemma annotations is ~98.02. The difference to the previous version is that this version was trained on the new version of the hr500k corpus.

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• Liner2.5

  2 resources

  Generic framework for information extraction tasks, including recognition of named entities, temporal expressions, spatial expressions and events.

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• The CLASSLA-Stanza model for lemmatisation of non-standard Croatian 2.1

  2 resources

  The model for lemmatisation of non-standard Croatian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the hr500k training corpus (http://hdl.handle.net/11356/1792) and the ReLDI-NormTagNER-hr corpus (http://hdl.handle.net/11356/1793), using the hrLex inflectional lexicon (http://hdl.handle.net/11356/1232). These corpora were additionally augmented for handling missing diacritics by repeating parts of the corpora with diacritics removed. The estimated F1 of the lemma annotations is ~94.23. The difference to the previous version of the model is that this version is trained on a combination of two corpora (hr500k, ReLDI-NormTagNER-hr).

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• The CLASSLA-Stanza model for UD dependency parsing of standard Bulgarian 2.1

  3 resources

  The model for UD dependency parsing of standard Bulgarian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the UD-parsed portion of the BulTreeBank training corpus (https://clarino.uib.no/korpuskel/corpora) and using the CLARIN.SI-embed.bg word embeddings (http://hdl.handle.net/11356/1796). The estimated LAS of the parser is ~91.18. The difference to the previous version of the parser is that this version was trained using the new version of the Bulgarian word embeddings.

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• The CLASSLA-StanfordNLP model for UD dependency parsing of standard Slovenian

  3 resources

  The model for UD dependency parsing of standard Slovenian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the UD-parsed portion of the ssj500k training corpus (http://hdl.handle.net/11356/1210) and using the CLARIN.SI-embed.sl word embeddings (http://hdl.handle.net/11356/1204). The estimated LAS of the parser is ~92.7.

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• WMT21 Marian translation model (ca-oc multi-task)

  1 resources

  Marian NMT model for Catalan to Occitan translation. It is a multi-task model, producing also a phonemic transcription of the Catalan source. The model was submitted to WMT'21 Shared Task on Multilingual Low-Resource Translation for Indo-European Languages as a CUNI-Contrastive system for Catalan to Occitan.

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• EdUKate translation software 1

  2 resources

  This software package includes three tools: web frontend for machine translation featuring phonetic transcription of Ukrainian suitable for Czech speakers, API server and a tool for translation of documents with markup (html, docx, odt, pptx, odp,...). These tools are used in the Charles Translator service (https://translator.cuni.cz). This software was developed within the EdUKate project, which aims to help mitigate language barriers between non-Czech-speaking children in the Czech Republic and the education in the Czech school system. The project focuses on the development and dissemination of multilingual digital learning materials for students in primary and secondary schools.

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