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

CreatorLjubešić, Nikola
Date2020-06-20T10:49:44Z
dc.date.accessioned2021-07-24T21:27:49Z
dc.date.available2021-07-24T21:27:49Z
Identifierhttp://hdl.handle.net/11356/1321
dc.identifier.urihttps://linghub.org/handle/123456789/924969
DescriptionThis model for named entity recognition of standard Slovenian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the ssj500k training corpus (http://hdl.handle.net/11356/1210) and using the CLARIN.SI-embed.sl word embeddings (http://hdl.handle.net/11356/1204).
PublisherJožef Stefan Institute
Rightshttps://creativecommons.org/licenses/by-sa/4.0/
RightsCreative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Subjectnamed entity recognition
Subjectlanguage model
TitleThe CLASSLA-StanfordNLP model for named entity recognition of standard Slovenian 1.0
TypetoolService
TypeSoftware
dcterms.available2020-06-20T10:49:44Z
dcterms.bibliographicCitationhttp://hdl.handle.net/11356/1321
dcterms.creatorLjubešić, Nikola
dcterms.date2020-06-20T10:49:44Z
dcterms.descriptionThis model for named entity recognition of standard Slovenian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the ssj500k training corpus (http://hdl.handle.net/11356/1210) and using the CLARIN.SI-embed.sl word embeddings (http://hdl.handle.net/11356/1204).
dcterms.identifierhttp://hdl.handle.net/11356/1321
dcterms.publisherJožef Stefan Institute
dcterms.rightshttps://creativecommons.org/licenses/by-sa/4.0/
dcterms.rightsCreative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
dcterms.subjectnamed entity recognition
dcterms.subjectlanguage model
dcterms.titleThe CLASSLA-StanfordNLP model for named entity recognition of standard Slovenian 1.0
dcterms.typetoolService
dcterms.typeSoftware
odrl.Policyhttp://purl.org/net/rdflicense/cc-by-sa4.0


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    Main data from the OLAC dataset

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Horizon 2020

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 825182.