Publication:
A new approach to automatically find and fix erroneous labels in dependency parsing treebanks

dc.contributor.authorBilgin, Metin
dc.contributor.buuauthorBİLGİN, METİN
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentBilgisayar Mühendisliği Bölümü
dc.contributor.researcheridAAH-2049-2021
dc.date.accessioned2024-06-28T10:51:07Z
dc.date.available2024-06-28T10:51:07Z
dc.date.issued2021-05-01
dc.description.abstractDependency Parsing (DP) is the existence of sub-term/upper-term relations between the words that make up that sentence for each sentence in the text. DP serves to produce meaningful information for high-level applications. Correct labeling of the text corpus used in DP studies is very important. There will be mistakes in the results of the studies that will be performed with the wrongly-labeled text corpus. If text corpus is labeled manually or automatically by human beings, then faulty cases will occur. As a result of the cases that may arise from human factors or annotations used for labeling, faulty labels will be on freebanks. In order to prevent these errors, detection, and correction of possible faulty labeling is very important in terms of increasing the accuracy of the studies to be carried out. Manual correction of possible faulty labels requires great effort and time. The purpose of this study is to create a model that automatically finds possible faulty labels and offers new label suggestions for faulty labels. With the help of the proposed model, it is aimed to detect and correct possible faulty labels that are included in a text corpus, and to increase consistency among the text corpus of the same language. With the help of the developed model, suggesting new labels for faulty labels by a language expert will be a great convenient for the specialist. Another advantage of the model is that the developed model provides a language-independent structure. It has succeeded in obtaining successful results in finding and correcting potentially faulty labels in experimental studies for Turkish. An increase in accuracy has been detected in studies carried out for languages other than Turkish. In investigating the accuracy of the results obtained by the system, the results were analyzed with the help of 10 different language experts.
dc.identifier.doi10.34028/iajit/18/3/12
dc.identifier.endpage364
dc.identifier.issn1683-3198
dc.identifier.issue3
dc.identifier.startpage356
dc.identifier.urihttps://doi.org/10.34028/iajit/18/3/12
dc.identifier.urihttps://iajit.org/PDF/May%202021,%20No.%203/19927.pdf
dc.identifier.urihttps://hdl.handle.net/11452/42581
dc.identifier.volume18
dc.identifier.wos000667208600012
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherZarka Private Univ
dc.relation.journalInternational Arab Journal of Information Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectErrors
dc.subjectNatural language processing
dc.subjectDependency parsing
dc.subjectUniversal dependency
dc.subjectError detection
dc.subjectFreebank consistency
dc.subjectScience & technology
dc.subjectTechnology
dc.subjectComputer science, artificial intelligence
dc.subjectComputer science, information systems
dc.subjectEngineering, electrical & electronic
dc.subjectComputer science
dc.subjectEngineering
dc.titleA new approach to automatically find and fix erroneous labels in dependency parsing treebanks
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü
relation.isAuthorOfPublicationcf59076b-d88e-4695-a08c-b06b98b4e25a
relation.isAuthorOfPublication.latestForDiscoverycf59076b-d88e-4695-a08c-b06b98b4e25a

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