TurkishDelightNLP: A Neural Turkish NLP Toolkit

Huseyin Alecakir, Necva Bölücü, Burcu Can


Abstract
We 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.
Anthology ID:
2022.naacl-demo.3
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations
Month:
July
Year:
2022
Address:
Hybrid: Seattle, Washington + Online
Editors:
Hannaneh Hajishirzi, Qiang Ning, Avi Sil
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
17–26
Language:
URL:
https://aclanthology.org/2022.naacl-demo.3
DOI:
10.18653/v1/2022.naacl-demo.3
Bibkey:
Cite (ACL):
Huseyin Alecakir, Necva Bölücü, and Burcu Can. 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, pages 17–26, Hybrid: Seattle, Washington + Online. Association for Computational Linguistics.
Cite (Informal):
TurkishDelightNLP: A Neural Turkish NLP Toolkit (Alecakir et al., NAACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.naacl-demo.3.pdf
Video:
 https://aclanthology.org/2022.naacl-demo.3.mp4
Code
 halecakir/turkish-delight-nlp-api