lenu_CZ / README.md
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metadata
widget:
  - text: ALU  SV CZ, s.r.o.
  - text: CZ STAVEBNÍ HOLDING, a.s.
  - text: NOVA Real Estate - podfond 1
  - text: Město Libušín
  - text: Ing. Jan Řezník
  - text: Stavební bytové družstvo Jindřichův Hradec
  - text: SHERLOG SE
  - text: Interim Investment svěřenský fond
  - text: Arcidiecézní charita Praha
  - text: Nadace Kardiocentrum České Budějovice
  - text: Svaz modelářů České republiky z.s.
  - text: VAN GRAAF, k.s.
  - text: Odbory KOVO MB
  - text: Vilau v.o.s.
  - text: Společenství vlastníků jednotek Purkyňova 1106/17, Opava
  - text: OSMA - ČR - OJ034
  - text: Římskokatolická farnost Těchlovice
  - text: Nadační fond TELEPACE
  - text: MILNEA státní podnik v likvidaci
  - text: ČIPA, o.p.s.
  - text: Ústav pro evropskou integraci z.ú.
  - text: AWP P&C Česká republika - odštěpný závod zahraniční právnické osoby
  - text: Moravskoslezský kraj
  - text: ecoenerg Windkraft GmbH & Co. KG, organizační složka
  - text: Ústav experimentální botaniky AV ČR, v. v. i.
  - text: NIX.CZ, z.s.p.o.
  - text: Obvodní soud pro Prahu 9
  - text: Svazek obcí pro vodovody a kanalizace Šlapanicko
  - text: Intel Czech Tradings, Inc., organizační složka
model-index:
  - name: Sociovestix/lenu_CZ
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: lenu
          type: Sociovestix/lenu
          config: CZ
          split: test
          revision: f4d57b8d77a49ec5c62d899c9a213d23cd9f9428
        metrics:
          - type: f1
            value: 0.9909657320872274
            name: f1
          - type: f1
            value: 0.8214443745456704
            name: f1 macro
            args:
              average: macro

LENU - Legal Entity Name Understanding for Czech Republic

A Bert (multilingual uncased) model fine-tuned on czech legal entity names (jurisdiction CZ) from the Global Legal Entity Identifier (LEI) System with the goal to detect Entity Legal Form (ELF) Codes.



in collaboration with



Model Description

The model has been created as part of a collaboration of the Global Legal Entity Identifier Foundation (GLEIF) and Sociovestix Labs with the goal to explore how Machine Learning can support in detecting the ELF Code solely based on an entity's legal name and legal jurisdiction. See also the open source python library lenu, which supports in this task.

The model has been trained on the dataset lenu, with a focus on czech legal entities and ELF Codes within the Jurisdiction "CZ".

  • Developed by: GLEIF and Sociovestix Labs
  • License: Creative Commons (CC0) license
  • Finetuned from model [optional]: bert-base-multilingual-uncased
  • Resources for more information: Press Release

Uses

An entity's legal form is a crucial component when verifying and screening organizational identity. The wide variety of entity legal forms that exist within and between jurisdictions, however, has made it difficult for large organizations to capture legal form as structured data. The Jurisdiction specific models of lenu, trained on entities from GLEIF’s Legal Entity Identifier (LEI) database of over two million records, will allow banks, investment firms, corporations, governments, and other large organizations to retrospectively analyze their master data, extract the legal form from the unstructured text of the legal name and uniformly apply an ELF code to each entity type, according to the ISO 20275 standard.

Licensing Information

This model, which is trained on LEI data, is available under Creative Commons (CC0) license. See gleif.org/en/about/open-data.

Recommendations

Users should always consider the score of the suggested ELF Codes. For low score values it may be necessary to manually review the affected entities.