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Yayın Automatic propbank generation for Turkish(Incoma Ltd, 2019-09) Ak, Koray; Yıldız, Olcay TanerSemantic 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. © 2019 Association for Computational Linguistics (ACL).Yayın A multilayer annotated corpus for Turkish(IEEE, 2018-06-06) Yıldız, Olcay Taner; Ak, Koray; Ercan, Gökhan; Topsakal, Ozan; Asmazoğlu, CengizIn this paper, we present the first multilayer annotated corpus for Turkish, which is a low-resourced agglutinative language. Our dataset consists of 9,600 sentences translated from the Penn Treebank Corpus. Annotated layers contain syntactic and semantic information including morphological disambiguation of words, named entity annotation, shallow parse, sense annotation, and semantic role label annotation.
