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AbstractUniversal Conceptual Cognitive Annotation (UCCA) is a cross-lingual semantic annotation framework that provides an easy annotation without any requirement for linguistic background. UCCA-annotated datasets have been already released in English, French, and German. In this paper, we introduce the first UCCA-annotated Turkish dataset that currently involves 50 sentences obtained from the METU-Sabanci Turkish Treebank. We followed a semi-automatic annotation approach, where an external semantic parser is utilised for an initial annotation of the dataset, which is partially accurate and requires refinement. We manually revised the annotations obtained from the semantic parser that are not in line with the UCCA rules that we defined for Turkish. We used the same external semantic parser for evaluation purposes and conducted experiments with both zero-shot and few-shot learning. This is the initial version of the annotated dataset and we are currently extending the dataset. We are releasing the current Turkish UCCA annotation guideline along with the annotated dataset.
CitationBölücü, N. and Can, B. (2022) Turkish universal conceptual cognitive annotation, In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 89–99, Marseille, France. European Language Resources Association.
PublisherEuropean Language Resources Association
Description© 2022 The Authors. Published by Language Resources and Evaluation Conference. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: http://www.lrec-conf.org/proceedings/lrec2022/index.html
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc/4.0/