The CLASSLA-StanfordNLP model for named entity recognition of standard Serbian 1.0

Name: The CLASSLA-StanfordNLP model for named entity recognition of standard Serbian 1.0
License: https://creativecommons.org/licenses/by-sa/4.0/

Ljubešić, Nikola

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dc.contributor.author	Ljubešić, Nikola
dc.date.accessioned	2020-06-20T10:47:46Z
dc.date.available	2020-06-20T10:47:46Z
dc.date.issued	2020-06-19
dc.identifier.uri	http://hdl.handle.net/11356/1323
dc.description	This model for named entity recognition 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 CLARIN.SI-embed.sr word embeddings (http://hdl.handle.net/11356/1206).
dc.language.iso	srp
dc.publisher	Jožef Stefan Institute
dc.relation.isreferencedby	http://dx.doi.org/10.18653/v1/W19-3704
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	named entity recognition
dc.subject	language model
dc.title	The CLASSLA-StanfordNLP model for named entity recognition of standard Serbian 1.0
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	2
files.size	111228370