Verb sense annotation for Turkish propbank via crowdsourcing
Şahin GG (2018)
Publication Type: Conference contribution
Publication year: 2018
Journal
Publisher: Springer Verlag
Book Volume: 9623 LNCS
Pages Range: 496-506
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Konya, TUR
ISBN: 9783319754765
DOI: 10.1007/978-3-319-75477-2_35
Abstract
In order to extract meaning representations from sentences, a corpus annotated with semantic roles is obligatory. Unfortunately building such a corpus requires tremendous amount of manual work for creating semantic frames and annotation of corpus. Thereby, we have divided the annotation task into two microtasks as verb sense annotation and argument annotation tasks and employed crowd intelligence to perform these microtasks. In this paper, we present our approach and the challenges on crowdsourcing verb sense disambiguation task and introduce the resource with 5855 annotated verb senses with 83.15% annotator agreement.
Involved external institutions
Turkey (TR)How to cite
APA:
Şahin, G.G. (2018). Verb sense annotation for Turkish propbank via crowdsourcing. In Alexander Gelbukh (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 496-506). Konya, TUR: Springer Verlag.
MLA:
Şahin, Gözde Gül. "Verb sense annotation for Turkish propbank via crowdsourcing." Proceedings of the 17th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2016, Konya, TUR Ed. Alexander Gelbukh, Springer Verlag, 2018. 496-506.
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