Please use this identifier to cite or link to this item: doi:10.22028/D291-30470
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Title: Crowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task
Author(s): Yung, Frances Pikyu
Demberg, Vera
Scholman, Merel Cleo Johanna
Editor(s): Friedrich, Annemarie
Zeyrek, Deniz
Hoek, Jet
Language: English
Title: The 13th Linguistic Annotation Workshop - proceedings of the workshop
Startpage: 16
Endpage: 25
Publisher/Platform: ACL
Year of Publication: 2019
Title of the Conference: LAW XIII 2019
Place of the conference: Florence, Italy
Publikation type: Conference Paper
Abstract: The perspective of being able to crowd-source coherence relations bears the promise of acquiring annotations for new texts quickly, which could then increase the size and variety of discourse-annotated corpora. It would also open the avenue to answering new research questions: Collecting annotations from a larger number of individuals per instance would allow to investigate the distribution of inferred relations, and to study individual differences in coherence relation interpretation. However, annotating coherence relations with untrained workers is not trivial. We here propose a novel two-step annotation procedure, which extends an earlier method by Scholman and Demberg (2017a). In our approach, coherence relation labels are inferred from connectives that workers insert into the text. We show that the proposed method leads to replicable coherence annotations, and analyse the agreement between the obtained relation labels and annotations from PDTB and RSTDT on the same texts.
DOI of the first publication: 10.18653/v1/W19-4003
URL of the first publication: https://www.aclweb.org/anthology/W19-4003/
Link to this record: hdl:20.500.11880/28861
http://dx.doi.org/10.22028/D291-30470
ISBN: 978-1-950737-38-3
Date of registration: 12-Mar-2020
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Vera Demberg
Collections:UniBib – Die Universitätsbibliographie

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