A manually annotated corpus in French for the study of urbanization and the natural risk prevention
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 Risque...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-11-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02705-y |
| _version_ | 1797453923190046720 |
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| author | Maksim Koptelov Margaux Holveck Bruno Cremilleux Justine Reynaud Mathieu Roche Maguelonne Teisseire |
| author_facet | Maksim Koptelov Margaux Holveck Bruno Cremilleux Justine Reynaud Mathieu Roche Maguelonne Teisseire |
| author_sort | Maksim Koptelov |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T15:29:52Z |
| format | Article |
| id | doaj.art-157edc9d1f474a3caef88725062ded96 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-09T15:29:52Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-157edc9d1f474a3caef88725062ded962023-11-26T12:18:08ZengNature PortfolioScientific Data2052-44632023-11-0110111410.1038/s41597-023-02705-yA manually annotated corpus in French for the study of urbanization and the natural risk preventionMaksim Koptelov0Margaux Holveck1Bruno Cremilleux2Justine Reynaud3Mathieu Roche4Maguelonne Teisseire5UNICAEN, ENSICAEN, CNRS – UMR GREYCICube, Université de StrasbourgUNICAEN, ENSICAEN, CNRS – UMR GREYCUNICAEN, ENSICAEN, CNRS – UMR GREYCUMR TETIS, Univ. Montpellier, AgroParisTech, CIRAD, CNRS, INRAEINRAEAbstract 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.https://doi.org/10.1038/s41597-023-02705-y |
| spellingShingle | Maksim Koptelov Margaux Holveck Bruno Cremilleux Justine Reynaud Mathieu Roche Maguelonne Teisseire A manually annotated corpus in French for the study of urbanization and the natural risk prevention Scientific Data |
| title | A manually annotated corpus in French for the study of urbanization and the natural risk prevention |
| title_full | A manually annotated corpus in French for the study of urbanization and the natural risk prevention |
| title_fullStr | A manually annotated corpus in French for the study of urbanization and the natural risk prevention |
| title_full_unstemmed | A manually annotated corpus in French for the study of urbanization and the natural risk prevention |
| title_short | A manually annotated corpus in French for the study of urbanization and the natural risk prevention |
| title_sort | manually annotated corpus in french for the study of urbanization and the natural risk prevention |
| url | https://doi.org/10.1038/s41597-023-02705-y |
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