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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 The CLASSLA-StanfordNLP model for lemmatisation of non-standard Serbian 1.1 Ljubešić, Nikola; Štefanec, Vanja. - : Jožef Stefan Institute, 2020 BASE Show details 2 The CLASSLA-StanfordNLP model for lemmatisation of non-standard Croatian 1.0 Ljubešić, Nikola; Štefanec, Vanja. - : Jožef Stefan Institute, 2020 BASE Show details 3 The CLASSLA-StanfordNLP model for lemmatisation of non-standard Serbian 1.0 Ljubešić, Nikola; Štefanec, Vanja. - : Jožef Stefan Institute, 2020 BASE Show details 4 The CLASSLA-StanfordNLP model for morphosyntactic annotation of non-standard Serbian 1.0 Ljubešić, Nikola; Štefanec, Vanja. - : Jožef Stefan Institute, 2020 BASE Show details 5 The CLASSLA-StanfordNLP model for morphosyntactic annotation of non-standard Croatian 1.0 Ljubešić, Nikola; Štefanec, Vanja. - : Jožef Stefan Institute, 2020 BASE Show details 6 The CLASSLA-StanfordNLP model for lemmatisation of non-standard Croatian 1.1 Ljubešić, Nikola; Štefanec, Vanja. - : Jožef Stefan Institute, 2020 Abstract: 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. Keyword: computer-mediated communication; language model; lemmatisation URL: http://hdl.handle.net/11356/1352 BASE Hide details

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