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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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• Word embeddings CLARIN.SI-embed.mk 2.0

  3 resources

  CLARIN.SI-embed.mk contains word embeddings induced from a large collection of Macedonian texts crawled from the .mk top-level domain. The embeddings are based on the skip-gram model of fastText trained on 933,231,582 tokens of running text for 986,670 lowercased surface forms. The difference to the previous version of the embeddings is that this version was trained on the original dataset expanded with the MaCoCu-mk web crawl corpus (http://hdl.handle.net/11356/1512).

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• The CLASSLA-Stanza model for morphosyntactic annotation of standard Croatian 2.1

  3 resources

  The model for morphosyntactic annotation 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 CLARIN.SI-embed.hr word embeddings (http://hdl.handle.net/11356/1790). The model produces simultaneously UPOS, FEATS and XPOS (MULTEXT-East) labels. The estimated F1 of the XPOS annotations is ~94.87. The difference to the previous version of the model is that this version was trained using the new version of the hr500k corpus and the new version of the Croatian word embeddings.

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

  3 resources

  The model for UD dependency parsing of standard Croatian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the UD-parsed portion of the hr500k training corpus (http://hdl.handle.net/11356/1792) and using the CLARIN.SI-embed.hr word embeddings (http://hdl.handle.net/11356/1790). The estimated LAS of the parser is ~87.46. The difference to the previous version of the model is that this version was trained using the new version of the hr500k corpus and the new version of the Croatian word embeddings.

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

  2 resources

  The model for lemmatisation of standard Macedonian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the 1984 training corpus expanded with the Macedonian SETimes corpus (to be published). The estimated F1 of the lemma annotations is ~98.81. The difference from the previous version is that this version was trained using a larger training dataset.

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

  3 resources

  The model for UD dependency parsing of 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 using the CLARIN.SI-embed.sr word embeddings (http://hdl.handle.net/11356/1789). The estimated LAS of the parser is ~89.83. The difference to the previous version of the model is that this version uses the new version of Serbian word embeddings.

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• The CLASSLA-Stanza model for morphosyntactic annotation of standard Serbian 2.1

  3 resources

  The model for morphosyntactic annotation of 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) combined with the Croatian hr500k training dataset (http://hdl.handle.net/11356/1792) to ensure sufficient representation of certain labels. The CLARIN.SI-embed.sr word embeddings (http://hdl.handle.net/11356/1789) were used during training. The model produces simultaneously UPOS, FEATS and XPOS (MULTEXT-East) labels. The estimated F1 of the XPOS annotations is ~96.19. The difference to the previous version of the model is that this version was trained on the SETimes.SR corpus expanded with the Croatian hr500k training dataset to ensure sufficient representation of certain labels. it was also trained using the new version of Serbian word embeddings.

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• The CLASSLA-Stanza model for morphosyntactic annotation of standard Macedonian 2.1

  3 resources

  This model for morphosyntactic annotation of standard Macedonian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the 1984 training corpus expanded with the Macedonian SETimes corpus (to be published) and using the Macedonian CLARIN.SI word embeddings (http://hdl.handle.net/11356/1788). The model produces simultaneously UPOS, FEATS and XPOS (MULTEXT-East) labels. The estimated F1 of the XPOS annotations is ~97.14. The difference from the previous version is that this version was trained using a larger training dataset and the new version of the Macedonian word embeddings.

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

  3 resources

  This model for morphosyntactic annotation 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), the ReLDI-NormTagNER-sr corpus (http://hdl.handle.net/11356/1794) and the hr500k training corpus (http://hdl.handle.net/11356/1792), using the CLARIN.SI-embed.sr word embeddings (http://hdl.handle.net/11356/1789). These corpora were additionally augmented for handling missing diacritics by repeating parts of the corpora with diacritics removed. The model produces simultaneously UPOS, FEATS and XPOS (MULTEXT-East) labels. The estimated F1 of the XPOS annotations is ~92.64. The difference to the previous version of the model is that this version uses the new version of Serbian word embeddings and is trained on a combination of three training corpora (SETimes.SR, ReLDI-NormTagNER-sr, hr500k).

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