Evidence map›Paper›PMID 41970174›Full record

ArticleData in brief2026

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

Fatima Ezzahra El Houbri, Najlae Idrissi, Mathieu Roche, Sarah Valentin

Abstract read
In one paragraph

Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Fatima Ezzahra El HoubriIntelligence, Data and Computing (IDC) Team, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal 23000, Morocco.
Najlae IdrissiIntelligence, Data and Computing (IDC) Team, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal 23000, Morocco.
Mathieu RocheCIRAD, F-34398 Montpellier, France.
Sarah ValentinCIRAD, F-34398 Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ArabicEnglishEpidemiologyNLPSpatial entitiesTranslation

Identifiers

PMID41970174
PMCPMC13068574

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.