| This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/). | |
| The model is trained using Hurricane Dorian 2019 event (training, development, and test data are used for training) from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRISI) under the Type-based LMR mode and using the random version of the data. | |
| You can download this data in BILOU format from [here](https://github.com/rsuwaileh/IDRISI/tree/main/data/LMR/EN/gold-random-bilou/hurricane_dorian_2019). | |
| * Different variants of the model are available through HuggingFace: | |
| - [rsuwaileh/IDRISI-LMR-HD-TB-partition](https://huggingface.co/rsuwaileh/IDRISI-LMR-HD-TB-partition/) | |
| - [rsuwaileh/IDRISI-LMR-HD-TL](https://huggingface.co/rsuwaileh/IDRISI-LMR-HD-TL) | |
| - [rsuwaileh/IDRISI-LMR-HD-TL-partition](https://huggingface.co/rsuwaileh/IDRISI-LMR-HD-TL-partition/) | |
| * Larger models are available at [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/). | |
| * Models trained on the entire IDRISI-R dataset: | |
| - [rsuwaileh/IDRISI-LMR-EN-random-typeless](https://huggingface.co/rsuwaileh/IDRISI-LMR-EN-random-typeless/) | |
| - [rsuwaileh/IDRISI-LMR-EN-random-typebased](https://huggingface.co/rsuwaileh/IDRISI-LMR-EN-random-typebased/) | |
| - [rsuwaileh/IDRISI-LMR-EN-timebased-typeless](https://huggingface.co/rsuwaileh/IDRISI-LMR-EN-timebased-typeless/) | |
| - [rsuwaileh/IDRISI-LMR-EN-timebased-typebased](https://huggingface.co/rsuwaileh/IDRISI-LMR-EN-timebased-typebased/) | |
| To cite this model: | |
| ``` | |
| @article{suwaileh2022tlLMR4disaster, | |
| title={When a Disaster Happens, We Are Ready: Location Mention Recognition from Crisis Tweets}, | |
| author={Suwaileh, Reem and Elsayed, Tamer and Imran, Muhammad and Sajjad, Hassan}, | |
| journal={International Journal of Disaster Risk Reduction}, | |
| year={2022} | |
| } | |
| @inproceedings{suwaileh2020tlLMR4disaster, | |
| title={Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets}, | |
| author={Suwaileh, Reem and Imran, Muhammad and Elsayed, Tamer and Sajjad, Hassan}, | |
| booktitle={Proceedings of the 28th International Conference on Computational Linguistics}, | |
| pages={6252--6263}, | |
| year={2020} | |
| } | |
| ``` | |
| To cite the IDRISI-R dataset: | |
| ``` | |
| @article{rsuwaileh2022Idrisi-r, | |
| title={IDRISI-R: Large-scale English and Arabic Location Mention Recognition Datasets for Disaster Response over Twitter}, | |
| author={Suwaileh, Reem and Elsayed, Tamer and Imran, Muhammad}, | |
| journal={...}, | |
| volume={...}, | |
| pages={...}, | |
| year={2022}, | |
| publisher={...} | |
| } | |
| ``` | |