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• The CLASSLA-Stanza model for lemmatisation of spoken Slovenian 2.2

  2 resources

  This model for lemmatisation of spoken Slovenian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the SST treebank of spoken Slovenian (https://github.com/UniversalDependencies/UD_Slovenian-SST) combined with the SUK training corpus (http://hdl.handle.net/11356/1959) and using the CLARIN.SI-embed.sl word embeddings (http://hdl.handle.net/11356/1791) that were expanded with the MaCoCu-sl Slovene web corpus (http://hdl.handle.net/11356/1517). The estimated F1 of the lemma annotations is ~99.23.

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• The CLASSLA-StanfordNLP model for lemmatisation of non-standard Croatian 1.0

  2 resources

  The model for lemmatisation of non-standard Croatian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the hr500k training corpus (http://hdl.handle.net/11356/1210), the ReLDI-NormTagNER-hr corpus (http://hdl.handle.net/11356/1241), the RAPUT corpus (https://www.aclweb.org/anthology/L16-1513/) and the ReLDI-NormTagNER-sr corpus (http://hdl.handle.net/11356/1240), 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 ~97.54.

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

  2 resources

  The model for lemmatisation of standard Bulgarian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the BulTreeBank training corpus (https://clarino.uib.no/korpuskel/corpora) and using the Bulgarian inflectional lexicon (Popov, Simov, and Vidinska 1998). The estimated F1 of the lemma annotations is ~98.93. The difference to the previous version of the lemmatizer is that this version was trained using the new version of the Bulgarian word embeddings.

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

  2 resources

  The model for lemmatisation of non-standard Serbian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the SETimes.SR training corpus (http://hdl.handle.net/11356/1200) and the ReLDI-NormTagNER-sr corpus (http://hdl.handle.net/11356/1794), using the srLex inflectional lexicon (http://hdl.handle.net/11356/1233). 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 ~94.92. The difference to the previous version of the model is that this version is trained on a combination of two corpora (SETimes.SR, ReLDI-NormTagNER-sr).

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• The Model latinpipe-evalatin24-240520 for LatinPipe 2024

  2 resources

  The latinpipe-evalatin24-240520 is a PhilBerta-based model for LatinPipe 2024 <https://github.com/ufal/evalatin2024-latinpipe>, performing tagging, lemmatization, and dependency parsing of Latin, based on the winning entry to the EvaLatin 2024 <https://circse.github.io/LT4HALA/2024/EvaLatin> shared task. It is released under the CC BY-NC-SA 4.0 license.

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• Universal Dependencies 2.10 models for UDPipe 2 (2022-07-11)

  2 resources

  Tokenizer, POS Tagger, Lemmatizer and Parser models for 123 treebanks of 69 languages of Universal Depenencies 2.10 Treebanks, created solely using UD 2.10 data (https://hdl.handle.net/11234/1-4758). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_210_models . To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .

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• The CLASSLA-StanfordNLP model for lemmatisation of non-standard Slovenian 1.1

  2 resources

  The model for lemmatisation of non-standard Slovenian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the ssj500k training corpus (http://hdl.handle.net/11356/1210) and the Janes-Tag corpus (http://hdl.handle.net/11356/1238), using the Sloleks inflectional lexicon (http://hdl.handle.net/11356/1230). 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 ~98.86. The difference to the previous version of the lemmatizer is that now it relies solely on XPOS annotations, and not on a combination of UPOS, FEATS (lexicon lookup) and XPOS (lemma prediction) annotations.

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• The CLASSLA-StanfordNLP model for lemmatisation of standard Slovenian 1.1

  2 resources

  The model for lemmatisation of standard Slovenian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the ssj500k training corpus (http://hdl.handle.net/11356/1210) and using the Sloleks inflectional lexicon (http://hdl.handle.net/11356/1230). The estimated F1 of the lemma annotations is ~99.0. The difference to the previous version of the model is that it is trained with the lemmatiser padding bug removed, cf. https://github.com/stanfordnlp/stanfordnlp/issues/143.

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• The CLASSLA-StanfordNLP model for lemmatisation of non-standard Croatian 1.1

  2 resources

  The model for lemmatisation of non-standard Croatian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the hr500k training corpus (http://hdl.handle.net/11356/1183), the ReLDI-NormTagNER-hr corpus (http://hdl.handle.net/11356/1241), the RAPUT corpus (https://www.aclweb.org/anthology/L16-1513/) and the ReLDI-NormTagNER-sr corpus (http://hdl.handle.net/11356/1240), 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 ~97.54. The difference to the previous version of the lemmatizer is that now it relies solely on XPOS annotations, and not on a combination of UPOS, FEATS (lexicon lookup) and XPOS (lemma prediction) annotations.

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• The CLASSLA-StanfordNLP model for lemmatisation of standard Croatian

  2 resources

  The model for lemmatisation of standard Croatian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the hr500k training corpus (http://hdl.handle.net/11356/1183) and using the hrLex inflectional lexicon (http://hdl.handle.net/11356/1232). The estimated F1 of the lemma annotations is ~97.6.

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