Verb Sense Annotation for Turkish PropBank via Crowdsourcing

Sahin G. G.

17th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing), Konya, Turkey, 3 - 09 April 2016, vol.9623, pp.496-506 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 9623
  • Doi Number: 10.1007/978-3-319-75477-2_35
  • City: Konya
  • Country: Turkey
  • Page Numbers: pp.496-506
  • Istanbul Technical University Affiliated: Yes


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.