HeGeL: A Novel Dataset for Geo-Location from Hebrew Text

Tzuf Paz-Argaman; Tal Bauman; Itai Mondshine; Itzhak Omer; Sagi Dalyot; Reut Tsarfaty

doi:10.18653/v1/2023.findings-acl.460

HeGeL: A Novel Dataset for Geo-Location from Hebrew Text

Tzuf Paz-Argaman, Tal Bauman, Itai Mondshine, Itzhak Omer, Sagi Dalyot, Reut Tsarfaty

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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.

Original language	English
Title of host publication	Findings of the Association for Computational Linguistics, ACL 2023
Publisher	Association for Computational Linguistics (ACL)
Pages	7311-7321
Number of pages	11
ISBN (Electronic)	9781959429623
DOIs	https://doi.org/10.18653/v1/2023.findings-acl.460
State	Published - 2023
Event	Findings of the Association for Computational Linguistics, ACL 2023 - Toronto, Canada Duration: 9 Jul 2023 → 14 Jul 2023

Publication series

Name	Proceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)	0736-587X

Conference

Conference	Findings of the Association for Computational Linguistics, ACL 2023
Country/Territory	Canada
City	Toronto
Period	9/07/23 → 14/07/23

Bibliographical note

Publisher Copyright:
© 2023 Association for Computational Linguistics.

Funding

This research is funded by a grant from the European Research Council, ERC-StG grant number 677352, and a grant by the Israeli Ministry of Science and Technology (MOST), grant number 3-17992, for which we are grateful.

Funders	Funder number
ERC-STG	677352
European Commission
Ministry of Science, Technology and Space	3-17992
Ministry of science and technology, Israel

Access to Document

10.18653/v1/2023.findings-acl.460

Cite this

Paz-Argaman, T., Bauman, T., Mondshine, I., Omer, I., Dalyot, S., & Tsarfaty, R. (2023). HeGeL: A Novel Dataset for Geo-Location from Hebrew Text. In Findings of the Association for Computational Linguistics, ACL 2023 (pp. 7311-7321). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.findings-acl.460

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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.",

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Paz-Argaman, T, Bauman, T, Mondshine, I, Omer, I, Dalyot, S & Tsarfaty, R 2023, HeGeL: A Novel Dataset for Geo-Location from Hebrew Text. in Findings of the Association for Computational Linguistics, ACL 2023. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics (ACL), pp. 7311-7321, Findings of the Association for Computational Linguistics, ACL 2023, Toronto, Canada, 9/07/23. https://doi.org/10.18653/v1/2023.findings-acl.460

HeGeL: A Novel Dataset for Geo-Location from Hebrew Text. / Paz-Argaman, Tzuf; Bauman, Tal; Mondshine, Itai et al.
Findings of the Association for Computational Linguistics, ACL 2023. Association for Computational Linguistics (ACL), 2023. p. 7311-7321 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Paz-Argaman T, Bauman T, Mondshine I, Omer I, Dalyot S, Tsarfaty R. HeGeL: A Novel Dataset for Geo-Location from Hebrew Text. In Findings of the Association for Computational Linguistics, ACL 2023. Association for Computational Linguistics (ACL). 2023. p. 7311-7321. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2023.findings-acl.460

HeGeL: A Novel Dataset for Geo-Location from Hebrew Text

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