Annotation of semantic roles for the Turkish Proposition Bank.
In this work, we report large-scale semantic role annotation of arguments in the Turkish dependency treebank, and present the first comprehensive Turkish semantic role labeling (SRL) resource: Turkish Proposition Bank (PropBank). We present our annotation workflow that harnesses crowd intelligence,...
| Publicado en: | Language Resources & Evaluation Vol. 52; no. 3; pp. 673 - 707 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Sep2018
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=131216683&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 131216683 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2018 vid: 52 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 131216683 10.1007/s10579-017-9390-y ppf: 673 ppct: 34 formats: fmt: – @attributes: type: T – @attributes: type: P size: 892KB tig: atl: Annotation of semantic roles for the Turkish Proposition Bank. aug: au: Şahin, Gözde Gül Adalı, Eşref affil: Department of Computer Engineering, Istanbul Technical University, 34469, Istanbul, Turkey su: Annotations Turkish language Machine learning Semantics Crowdsourcing sug: subj: Annotations Turkish language Machine learning Semantics Crowdsourcing keyword: Derivational morphology PropBank Semantic role annotation Semantic role labeling Turkish ab: In this work, we report large-scale semantic role annotation of arguments in the Turkish dependency treebank, and present the first comprehensive Turkish semantic role labeling (SRL) resource: Turkish Proposition Bank (PropBank). We present our annotation workflow that harnesses crowd intelligence, and discuss the procedures for ensuring annotation consistency and quality control. Our discussion focuses on syntactic variations in realization of predicate-argument structures, and the large lexicon problem caused by complex derivational morphology. We describe our approach that exploits framesets of root verbs to abstract away from syntax and increase self-consistency of the Turkish PropBank. The issues that arise in the annotation of verbs derived via valency changing morphemes, verbal nominals, and nominal verbs are explored, and evaluation results for inter-annotator agreement are provided. Furthermore, semantic layer described here is aligned with universal dependency (UD) compliant treebank and released to enable more researchers to work on the problem. Finally, we use PropBank to establish a baseline score of 79.10 F1 for Turkish SRL using the mate-tool (an open-source SRL tool based on supervised machine learning) enhanced with basic morphological features. Turkish PropBank and the extended SRL system are made publicly available. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2018. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2018 holdings: @attributes: islocal: N |
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