ArticleData in brief2024
FloraNER: A new dataset for species and morphological terms named entity recognition in French botanical text.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Herbarium specimens in the age of artificial intelligence: from herbarium image identification to Integrative Taxonomic AI.Journal of plant research · 2026Article
- FloraNER: A new dataset for species and morphological terms named entity recognition in French botanical text.Data in brief · 2024Article
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Authors and funding
6 authors.
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Abstract
FloraNER is a distantly supervised named entity recognition dataset (NER). The dataset is built from botanical French literature extracted from the OCR-preprocessed flora of New Caledonia, provided by the National Museum of Natural History in France (MNHN), and distantly annotated with a botanical French corpus created by merging botanical lexicons available online. FloraNER comprises separate sub-datasets for the recognition of plant species names, as well as coarse-grained and fine-grained botanical morphological terms. The resulting datasets are in CSV format, displaying textual data, identified named entities, and their annotations, covering one named entity type "Species" (Espèce in French) for species name identification, two named entity types "Organ" and "Descriptor" for coarse-grained morphological term identification, and eight named entity types for fine-grained morphological term identification: Organ, Descriptor, Form, Color, Development, Structure, Surface, Position, Disposition, and Measure. This dataset can be utilized to train and evaluate named entity recognition models for extracting information from botanical French literature.
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