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---
language:
- tr
tags:
- convbert
license: cc-by-nc-sa-4.0
---
# deprem-convberturk-ner
Fine-tuned ConvBERTurk model for Turkish named entity recognition detecting PERSON, ADDRESS, CITY, STATUS of the tweets calling for help in the earthquake disaster. The model was trained using the tweets posted in the first 12 hours of the 2023 Turkey-Syria Earthquake.
The dataset and other details can be found at:
https://github.com/avaapm/deprem
### BibTeX entry and citation info
```bibtex
@misc{toraman2023earthquake,
doi = {10.48550/ARXIV.2302.13403},
url = {https://arxiv.org/abs/2302.13403},
author = {Toraman, Cagri and Kucukkaya, Izzet Emre and Ozcelik, Oguzhan and Sahin, Umitcan},
keywords = {Social and Information Networks (cs.SI), Computation and Language (cs.CL), Information Retrieval (cs.IR), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Tweets Under the Rubble: Detection of Messages Calling for Help in Earthquake Disaster},
publisher = {arXiv},
year = {2023},
copyright = {Creative Commons Attribution Non Commercial Share Alike 4.0 International}
}
``` |