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dc.contributor.author Ljubešić, Nikola
dc.date.accessioned 2020-09-15T10:51:11Z
dc.date.available 2020-09-15T10:51:11Z
dc.date.issued 2020-09-15
dc.identifier.uri http://hdl.handle.net/11356/1355
dc.description The model for lemmatisation of standard Serbian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the SETimes.SR training corpus (http://hdl.handle.net/11356/1200) and using the srLex inflectional lexicon (http://hdl.handle.net/11356/1233). The estimated F1 of the lemma annotations is ~97.9. The difference to the previous version is that now it relies solely on XPOS annotations, and not on a combination of UPOS, FEATS (lexicon lookup) and XPOS (lemma prediction) annotations.
dc.language.iso srp
dc.publisher Jožef Stefan Institute
dc.relation.isreferencedby http://dx.doi.org/10.18653/v1/W19-3704
dc.relation.replaces http://hdl.handle.net/11356/1288
dc.rights Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
dc.rights.uri https://creativecommons.org/licenses/by-sa/4.0/
dc.rights.label PUB
dc.source.uri https://github.com/clarinsi/classla-stanfordnlp
dc.subject lemmatisation
dc.subject language model
dc.title The CLASSLA-StanfordNLP model for lemmatisation of standard Serbian 1.2
dc.type toolService
metashare.ResourceInfo#ContentInfo.detailedType tool
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent true
has.files yes
branding CLARIN.SI data & tools
contact.person Nikola Ljubešić nikola.ljubesic@ijs.si Jožef Stefan Institute
sponsor ARRS (Slovenian Research Agency) P6-0411 Language Resources and Technologies for Slovene nationalFunds
sponsor ARRS (Slovenian Research Agency) J7-8280 FRENK: Resources, methods, and tools for the understanding, identification, and classification of various forms of socially unacceptable discourse in the information society nationalFunds
sponsor ARRS (Slovenian Research Agency) N6-0099 LiLaH: Linguistic Landscape of Hate Speech nationalFunds
files.count 1
files.size 91737237


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