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Article Dans Une Revue Biodiversity Information Science and Standards Année : 2022

NEARSIDE: Structured kNowledge Extraction frAmework from SpecIes DEscriptions

Résumé

Species descriptions are stored in textual form in corpora such as in floras and faunas, but this large amount of information cannot be used directly by algorithms, nor can it be linked to other data sources. The production of knowledge bases expressing structured data can benefit from collaborative and easy-to-use platforms like Xper3 (Vignes-Lebbe et al. 2017, Kerner and Vignes 2019, Saucède et al. 2021) but is very time-consuming at the human level. It is therefore mandatory for this task to make the information contained in species descriptions measurable and compatible with computer techniques. In this work, we developed NEARSIDE, a relation extraction model adapted to biology corpora to create normalized morphological characteristic knowledge bases for species descriptions.

Dates et versions

hal-03897571 , version 1 (14-12-2022)

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Citer

Maya Sahraoui, Marc Pignal, Régine Vignes Lebbe, Vincent Guigue. NEARSIDE: Structured kNowledge Extraction frAmework from SpecIes DEscriptions. Biodiversity Information Science and Standards, 2022, 6, ⟨10.3897/biss.6.94297⟩. ⟨hal-03897571⟩
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