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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Slovenian 1.3
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Slovenian 1.2
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Macedonian 1.0
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Serbian 1.1
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Croatian 1.1
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Bulgarian 1.0
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of non-standard Serbian 1.0
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of non-standard Croatian 1.0
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of non-standard Slovenian 1.0
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Slovenian 1.1
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Slovenian
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Croatian
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Serbian
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Serbian Twitter training corpus ReLDI-NormTagNER-sr 2.1
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Abstract:
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, word normalisation, morphosyntactic tagging, lemmatisation and named entity recognition of non-standard Serbian. Each tweet is also annotated for its automatically assigned standardness levels (T = technical standardness, L = linguistic standardness). As an update to version 2.0, version 2.1 corrects some annotation errors and adds morphosyntactic annotations in the Universal Dependencies formalism in addition to the MULTEXT-East morphosyntactic descriptions. The corpus is now also available in CoNLL-U format.
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Keyword:
computer-mediated communication; lemmatisation; manual annotation; named entities; part-of-speech tagging; TEI; tokenisation; word normalisation
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URL: http://hdl.handle.net/11356/1240
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