-
Training corpus SETimes.SR 1.0
The SETimes.SR training corpus contains 86 726 tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation, syntactic... -
Training corpus ssj500k 2.3
The ssj500k training corpus contains about 500,000 tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, and lemmatisation.... -
Trankit model for SST 2.15
This is a retrained Slovenian model for the Trankit v1.1.1 library for multilingual natural language processing (https://pypi.org/project/trankit/), trained on the SST treebank... -
The Trankit model for linguistic processing of written and spoken Slovenian 1.2
This is a retrained Slovenian model for the Trankit v1.1.1 library for multilingual natural language processing (https://pypi.org/project/trankit/), trained on the concatenation... -
CMC training corpus Janes-Norm 1.1
Janes-Norm is a manually annotated corpus of Slovene Computer-Mediated Communication (CMC). It is meant as a gold-standard training and testing dataset for tokenisation,... -
Croatian Twitter training corpus ReLDI-NormTag-hr 1.1
ReLDI-NormTag-hr 1.1 is a manually annotated corpus of Croatian tweets. It is meant as a gold-standard training and testing dataset for tokenisation, sentence segmentation, word... -
Trankit model for SST 2.15 1.1
This is a retrained Slovenian model for the Trankit v1.1.1 library for multilingual natural language processing (https://pypi.org/project/trankit/), trained on the SST treebank... -
Trankit model for linguistic processing of spoken Slovenian
This is a retrained Slovenian spoken language model for Trankit v1.1.1 library (https://pypi.org/project/trankit/). It is able to predict sentence segmentation, tokenization,... -
Serbian Twitter training corpus ReLDI-NormTagNER-sr 3.0
ReLDI-NormTagNER-sr 3.0 is a manually annotated corpus of Serbian tweets. It is meant as a gold-standard training and testing dataset for tokenisation, sentence segmentation,... -
The Trankit model for linguistic process of standard written Slovenian 1.1
This is a retrained Slovenian model for the Trankit v1.1.1 library for multilingual natural language processing (https://pypi.org/project/trankit/), trained on the reference SSJ... -
Training corpus SUK 1.0
The SUK training corpus contains about 1 million tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, and lemmatisation, with... -
The Trankit model for linguistic processing of standard Slovenian
This is a retrained Slovenian standard model for Trankit v1.1.1 library (https://pypi.org/project/trankit/). It is able to predict sentence segmentation, tokenization,... -
CMC training corpus Janes-Tag 1.2
Janes-Tag is a manually annotated corpus of Slovene Computer-Mediated Communication (CMC). It is meant as a gold-standard training and testing dataset for tokenisation, sentence... -
Training corpus hr500k 1.0
The hr500k training corpus contains about 500,000 tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation and... -
CMC training corpus Janes-Norm 3.0
Janes-Norm is a manually annotated corpus of Slovene Computer-Mediated Communication (CMC) consisting of about 20,000 short texts (280,000 words), mostly tweets but also blogs,... -
CMC training corpus Janes-Tag 2.1
Janes-Tag is a manually annotated corpus of Slovene Computer-Mediated Communication (CMC). It is meant as a gold-standard training and testing dataset for tokenisation, sentence... -
Training corpus SUK 1.1
The SUK training corpus contains about 1 million tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, and lemmatisation, with... -
Serbian Twitter training corpus ReLDI-NormTagNER-sr 2.1
ReLDI-NormTagNER-sr 2.1 is a manually annotated corpus of Serbian tweets. It is meant as a gold-standard training and testing dataset for tokenisation, sentence segmentation,... -
Training corpus ssj500k 1.4
The ssj500k training corpus contains 500,000 words, manually annotated on the levels of tokenization, sentence segmentation, morphosyntactic tagging, lemmatisation, named... -
Croatian Twitter training corpus ReLDI-NormTagNER-hr 2.1
ReLDI-NormTagNER-hr 2.1 is a manually annotated corpus of Croatian tweets. It is meant as a gold-standard training and testing dataset for tokenisation, sentence segmentation,...
