MetadataShow full item record
AbstractWe introduce a neural Turkish NLP toolkit called TurkishDelightNLP that performs computational linguistic analyses from morphological level to semantic level that involves tasks such as stemming, morphological segmentation, morphological tagging, part-of-speech tagging, dependency parsing, and semantic parsing, as well as high-level NLP tasks such as named entity recognition. We publicly share the open-source Turkish NLP toolkit through a web interface that allows an input text to be analysed in real-time, as well as the open source implementation of the components provided in the toolkit, an API, and several annotated datasets such as word similarity test set to evaluate word embeddings and UCCA-based semantic annotation in Turkish. This will be the first open-source Turkish NLP toolkit that involves a range of NLP tasks in all levels. We believe that it will be useful for other researchers in Turkish NLP and will be also beneficial for other high-level NLP tasks in Turkish.
CitationAlecakir, H., Bölücü, N. and Can, B. (2022) TurkishDelightNLP: A Neural Turkish NLP Toolkit. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations, pp. 17–26, Hybrid: Seattle, Washington + Online. Association for Computational Linguistics.
DescriptionThis is a paper published by ACL in the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics, available online: https://aclanthology.org/2022.naacl-demo.3
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/