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A manually annotated corpus in French for the study of urbanization and the natural risk prevention

Authors :
Koptelov, Maksim
Holveck, Margaux
Crémilleux, Bruno
Reynaud, Justine
Roche, Mathieu
Teisseire, Maguelonne
Koptelov, Maksim
Holveck, Margaux
Crémilleux, Bruno
Reynaud, Justine
Roche, Mathieu
Teisseire, Maguelonne
Source :
Scientific Data
Publication Year :
2023

Abstract

Land artificialization is a serious problem of civilization. Urban planning and natural risk management are aimed to improve it. In France, these practices operate the Local Land Plans (PLU – Plan Local d'Urbanisme) and the Natural risk prevention plans (PPRn – Plan de Prévention des Risques naturels) containing land use rules. To facilitate automatic extraction of the rules, we manually annotated a number of those documents concerning Montpellier, a rapidly evolving agglomeration exposed to natural risks. We defined a format for labeled examples in which each entry includes title and subtitle. In addition, we proposed a hierarchical representation of class labels to generalize the use of our corpus. Our corpus, consisting of 1934 textual segments, each of which labeled by one of the 4 classes (Verifiable, Non-verifiable, Informative and Not pertinent) is the first corpus in the French language in the fields of urban planning and natural risk management. Along with presenting the corpus, we tested a state-of-the-art approach for text classification to demonstrate its usability for automatic rule extraction.

Details

Database :
OAIster
Journal :
Scientific Data
Notes :
France, text, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1410962925
Document Type :
Electronic Resource