pytorch bert token-classification transformers license:apache-2.0 autotrain_compatible
---
license: apache-2.0
---

This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/). The model identifies the toponyms' spans in the text without predicting their location types. 

The model is trained using the training splits of all events from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRISI) under the `Type-less` LMR mode and using the `Time-based` 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-timebased-bilou/). All Location types in the data were normalized to the `LOC` tag. More details about the models are available [here](https://github.com/rsuwaileh/IDRISI/tree/main/models).

* Different variants of the model are available through HuggingFace:
  - [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-typebased](https://huggingface.co/rsuwaileh/IDRISI-LMR-EN-timebased-typebased/)


* Arabic models are also available:
  - [rsuwaileh/IDRISI-LMR-AR-random-typeless](https://huggingface.co/rsuwaileh/IDRISI-LMR-AR-random-typeless/)
  - [rsuwaileh/IDRISI-LMR-AR-random-typebased](https://huggingface.co/rsuwaileh/IDRISI-LMR-AR-random-typebased/)
  - [rsuwaileh/IDRISI-LMR-AR-timebased-typeless](https://huggingface.co/rsuwaileh/IDRISI-LMR-AR-timebased-typeless/)
  - [rsuwaileh/IDRISI-LMR-AR-timebased-typebased](https://huggingface.co/rsuwaileh/IDRISI-LMR-AR-timebased-typebased/)


To cite the models:

```
@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={...}
  }
```
