@inproceedings{paz-argaman-etal-2023-hegel,
    title = "{H}e{G}e{L}: A Novel Dataset for Geo-Location from {H}ebrew Text",
    author = "Paz-Argaman, Tzuf  and
      Bauman, Tal  and
      Mondshine, Itai  and
      Omer, Itzhak  and
      Dalyot, Sagi  and
      Tsarfaty, Reut",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-acl.460",
    doi = "10.18653/v1/2023.findings-acl.460",
    pages = "7311--7321",
    abstract = "The task of textual geolocation {---} retrieving the coordinates of a place based on a free-form language description {---} calls for not only grounding but also natural language understanding and geospatial reasoning. Even though there are quite a few datasets in English used for geolocation, they are currently based on open-source data (Wikipedia and Twitter), where the location of the described place is mostly implicit, such that the location retrieval resolution is limited. Furthermore, there are no datasets available for addressing the problem of textual geolocation in morphologically rich and resource-poor languages, such as Hebrew. In this paper, we present the Hebrew Geo-Location (HeGeL) corpus, designed to collect literal place descriptions and analyze lingual geospatial reasoning. We crowdsourced 5,649 literal Hebrew place descriptions of various place types in three cities in Israel. Qualitative and empirical analysis show that the data exhibits abundant use of geospatial reasoning and requires a novel environmental representation.",
}

The task of textual geolocation {---} retrieving the coordinates of a place based on a free-form language description {---} calls for not only grounding but also natural language understanding and geospatial reasoning. Even though there are quite a few datasets in English used for geolocation, they are currently based on open-source data (Wikipedia and Twitter), where the location of the described place is mostly implicit, such that the location retrieval resolution is limited. Furthermore, there are no datasets available for addressing the problem of textual geolocation in morphologically rich and resource-poor languages, such as Hebrew. In this paper, we present the Hebrew Geo-Location (HeGeL) corpus, designed to collect literal place descriptions and analyze lingual geospatial reasoning. We crowdsourced 5,649 literal Hebrew place descriptions of various place types in three cities in Israel. Qualitative and empirical analysis show that the data exhibits abundant use of geospatial reasoning and requires a novel environmental representation.
Paz-Argaman, Tzuf Bauman, Tal Mondshine, Itai Omer, Itzhak Dalyot, Sagi Tsarfaty, Reut
HeGeL: A Novel Dataset for Geo-Location from Hebrew Text