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  • Computer assistant for text input for persons with language impairment (RAPUT)

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  • Project: Computer assistant for text input for persons with language impairment (RAPUT)
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  • The CLASSLA-StanfordNLP model for morphosyntactic annotation of non-standard Croatian 1.0

    This model for morphosyntactic annotation 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 CLARIN.SI-embed.hr word embeddings (http://hdl.handle.net/11356/1205). 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 ~95.11.

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

    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.

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

    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.