PADI-Location-AR-EN: A normalized Arabic–English spatial entity dataset for epidemiological surveillance

International audience The location of events in multilingual texts, particularly in Arabic, represents a challenge for epidemiological monitoring. Systems such as PADI-web rely on English translation to extract spatial entities, but the scarcity of annotated spatial entities in Arabic can hamper the reliability of translations and extraction. In this context, PADI-Location-AR-EN, which is a dataset of 328 spatial entities that were manually extracted from 96 Arabic-language news articles collected by the PADI-web epidemiological monitoring system, is presented in this paper. Each entity was manually translated into English, normalized using the GeoNames database, and then classified according to its type and spatial category. The dataset can be used to evaluate the translation quality of three machine translation systems (DeepL, Microsoft Azure and Reverso) as well as the performance of named entity recognition models on the translated texts.