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dc.contributor.authorYenice, A. B.
dc.contributor.authorCesur, N.
dc.contributor.authorKurgun, A.
dc.contributor.authorYıldız, Olcay Taner
dc.date.accessioned2023-08-04T13:17:59Z
dc.date.available2023-08-04T13:17:59Z
dc.date.issued2022
dc.identifier.isbn978-249381408-1
dc.identifier.urihttp://hdl.handle.net/10679/8570
dc.identifier.urihttp://www.lrec-conf.org/proceedings/lrec2022/workshops/LAWXVI/pdf/2022.lawxvi-1.9.pdf
dc.description.abstractThis paper aims to introduce StarDust, a new, open-source annotation tool designed for NLP studies. StarDust is designed specifically to be intuitive and simple for the annotators while also supporting the annotation of multiple languages with different morphological typologies, e.g. Turkish and English. This demonstration will mainly focus on our UD-based annotation tool for dependency syntax. Linked to a morphological analyzer, the tool can detect certain annotator mistakes and limit undesired dependency relations as well as offering annotators a quick and effective annotation process thanks to its new simple interface. Our tool can be downloaded from the Github. © 2022 European Language Resources Association (ELRA).en_US
dc.language.isoengen_US
dc.publisherEuropean Language Resources Association (ELRA)en_US
dc.relation.ispartofProceedings of the 16th Linguistic Annotation Workshop, LAW 2022 - held in conjunction with the Language Resources and Evaluation Conference, LREC 2022 Workshop
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.titleIntroducing StarDust: A UD-based Dependency Annotation Toolen_US
dc.typeConference paperen_US
dc.publicationstatusPublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0001-5838-4615 & YÖK ID 19848) Yıldız, Olcay Taner
dc.contributor.ozuauthorYıldız, Olcay Taner
dc.identifier.startpage79en_US
dc.identifier.endpage84en_US
dc.subject.keywordsAnnotation toolen_US
dc.subject.keywordsDependency parsingen_US
dc.subject.keywordsTurkishen_US
dc.identifier.scopusSCOPUS:2-s2.0-85146042597
dc.relation.publicationcategoryConference Paper - International - Institutional Academic Staff


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