Update README.md

README.md

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----
-license: cc-by-4.0
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+---
+license: cc-by-nc-4.0
+language:
+- fr
+pipeline_tag: token-classification
+widget:
+- text: >-
+    * ALBI, (Géog.) ville de France, capitale de l'Albigeois, dans le haut
+    Languedoc : elle est sur le Tarn. Long. 19. 49. lat. 43. 55. 44.
+- text: >-
+    HILPERHAUSEN, (Géog.) ville d'Allemagne en Franconie, sur la Werra, au comté de Henneberg, entre Cobourg & Smalcalde ; elle appartient à une branche de la maison de Saxe-Gotha. Long. 28. 15. lat. 50. 35. (D. J.)
+---
+
+# bert-base-french-cased-edda-ner-levels
+
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This model is designed to identify and classify Named Entity Recognition with the prefix IOB2. 
+It has been trained on the French *Encyclopédie ou dictionnaire raisonné des sciences des arts et des métiers par une société de gens de lettres (1751-1772)* edited by Diderot and d'Alembert (provided by the [ARTFL Encyclopédie Project](https://artfl-project.uchicago.edu)).
+Dataset: [https://huggingface.co/datasets/GEODE/GeoEDdA](https://huggingface.co/datasets/GEODE/GeoEDdA)
+
+
+## Class labels
+
+<!-- Provide a list of tag detected by the model. -->
+
+The NER detected by this model are:
+- **NC-Spatial**: a common noun that identifies a spatial entity (nominal spatial entity) including natural features, e.g. `ville`, `la rivière`, `royaume`.
+- **NP-Spatial**: a proper noun identifying the name of a place (spatial named entities), e.g. `France`, `Paris`, `la Chine`.
+- **ENE-Spatial**: nested spatial entity , e.g. `ville de France`, `royaume de Naples`, `la mer Baltique`.
+- **Relation**: spatial relation, e.g. `dans`, `sur`, `à 10 lieues de`.
+- **Latlong**: geographic coordinates, e.g. Long. 19. 49. lat. 43. 55. 44.
+- **NC-Person**: a common noun that identifies a person (nominal spatial entity), e.g. `roi`, `l'empereur`, `les auteurs`.
+- **NP-Person**: a proper noun identifying the name of a person (person named entities), e.g. `Louis XIV`, `Pline`, `les Romains`.
+- **ENE-Person**: nested people entity, e.g. `le czar Pierre`, `roi de Macédoine`
+- **NP-Misc**: a proper noun identifying entities not classified as spatial or person, e.g. `l'Eglise`, `1702`, `Pélasgique`.
+- **ENE-Misc**: nested named entity not classified as spatial or person, e.g. `l'ordre de S. Jacques`, `la déclaration du 21 Mars 1671`.
+- **Head**: entry name
+- **Domain-Mark**: words indicating the knowledge domain (usually after the head and between parenthesis), e.g. `Géographie`, `Geog.`, `en Anatomie`.
+
+
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+This model was trained entirely on French encyclopedic entries and will likely not perform well on text in other languages or other corpora. 
+
+
+## Acknowledgement
+
+
+The authors are grateful to the [ASLAN project](https://aslan.universite-lyon.fr) (ANR-10-LABX-0081) of the Université de Lyon, for its financial support within the French program "Investments for the Future" operated by the National Research Agency (ANR).
+Data courtesy the [ARTFL Encyclopédie Project](https://artfl-project.uchicago.edu), University of Chicago.
+