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المؤلفSuwaileh, Reem
المؤلفImran, Muhammad
المؤلفElsayed, Tamer
تاريخ الإتاحة2024-03-11T06:03:07Z
تاريخ النشر2023
اسم المنشورProceedings of the Annual Meeting of the Association for Computational Linguistics
المصدرScopus
الرقم المعياري الدولي للكتاب0736587X
معرّف المصادر الموحدhttp://hdl.handle.net/10576/52848
معرّف المصادر الموحدhttp://dx.doi.org/10.18653/v1/2023.acl-long.901
الملخصExtracting geolocation information from social media data enables effective disaster management, as it helps response authorities; for example, in locating incidents for planning rescue activities, and affected people for evacuation. Nevertheless, geolocation extraction is greatly understudied for the low resource languages such as Arabic. To fill this gap, we introduce IDRISI-RA, the first publicly-available Arabic Location Mention Recognition (LMR) dataset that provides human- and automatically-labeled versions in order of thousands and millions of tweets, respectively. It contains both location mentions and their types (e.g., district, city). Our extensive analysis shows the decent geographical, domain, location granularity, temporal, and dialectical coverage of IDRISI-RA. Furthermore, we establish baselines using the standard Arabic NER models and build two simple, yet effective, LMR models. Our rigorous experiments confirm the need for developing specific models for Arabic LMR in the disaster domain. Moreover, experiments show the promising domain and geographical generalizability of IDRISI-RA under zero-shot learning.
راعي المشروعThis work was made possible by the Graduate Sponsorship Research Award (GSRA) #GSRA5-1-0527-18082 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. We would like to thank the in-house annotators for their valuable help including Noura Abdullah, Aisha Suwaileh, Rasha Hamdoon, Na-jlaa Alfuhaida, Hana Shamayleh, Lamiaa Basyoni, Sara Alrasbi, and Nada Abo Eita.
اللغةen
الناشرAssociation for Computational Linguistics (ACL)
الموضوعComputational linguistics
Disaster prevention
Disasters
Zero-shot learning
Disaster management
Effective location
Experiment confirm
Geolocations
Low resource languages
Recognition models
Rescue activities
Simple++
Social media datum
Standard arabics
Location
العنوانIDRISI-RA: The First Arabic Location Mention Recognition Dataset of Disaster Tweets
النوعConference Paper
الصفحات16298-16317
رقم المجلد1
dc.accessType Open Access


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