@inproceedings{tanev-de-longueville-2023-matters,
    title = "Where {\textquotedblleft}where{\textquotedblright} Matters : Event Location Disambiguation with a {BERT} Language Model",
    author = "Tanev, Hristo  and
      De Longueville, Bertrand",
    editor = {H{\"u}rriyeto{\u{g}}lu, Ali  and
      Tanev, Hristo  and
      Zavarella, Vanni  and
      Yeniterzi, Reyyan  and
      Y{\"o}r{\"u}k, Erdem  and
      Slavcheva, Milena},
    booktitle = "Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text",
    month = sep,
    year = "2023",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/icon-24-ingestion/2023.case-1.2/",
    pages = "11--17",
    abstract = "The method method presented in this paper uses a BERT model for classifying location mentions in event reporting news texts into two classes: a place of an event, called main location, or another location mention, called here secondary location. Our evaluation on articles, reporting protests, shows promising results and demonstrates the feasibility of our approach and the event geolocation task in general. We evaluate our method against a simple baseline and state of the art ML models and we achieve a significant improvement in all cases by using the BERT model. In contrast to other location classification approaches, we completelly avoid lingusitic pre processing and feature engineering, which is a pre-requisite for all multi-domain and multilingual applications."
}