Koray Ak

Also published as: Koray AK


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TRopBank: Turkish PropBank V2.0
Neslihan Kara | Deniz Baran Aslan | Büşra Marşan | Özge Bakay | Koray Ak | Olcay Taner Yıldız
Proceedings of the Twelfth Language Resources and Evaluation Conference

In this paper, we present and explain TRopBank “Turkish PropBank v2.0”. PropBank is a hand-annotated corpus of propositions which is used to obtain the predicate-argument information of a language. Predicate-argument information of a language can help understand semantic roles of arguments. “Turkish PropBank v2.0”, unlike PropBank v1.0, has a much more extensive list of Turkish verbs, with 17.673 verbs in total.


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Automatic Propbank Generation for Turkish
Koray AK | Olcay Taner Yıldız
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

Semantic role labeling (SRL) is an important task for understanding natural languages, where the objective is to analyse propositions expressed by the verb and to identify each word that bears a semantic role. It provides an extensive dataset to enhance NLP applications such as information retrieval, machine translation, information extraction, and question answering. However, creating SRL models are difficult. Even in some languages, it is infeasible to create SRL models that have predicate-argument structure due to lack of linguistic resources. In this paper, we present our method to create an automatic Turkish PropBank by exploiting parallel data from the translated sentences of English PropBank. Experiments show that our method gives promising results.