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

Autor:	Paz-Argaman, Tzuf, Bauman, Tal, Mondshine, Itai, Omer, Itzhak, Dalyot, Sagi, Tsarfaty, Reut
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Information Retrieval Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: Accepted for ACL findings 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2307.00509 Zobrazit plný text záznamu View this record from Arxiv