widget:
- text: Kapalula Stiftung
- text: Hilti Glasbau AG
- text: KASSALA PRIVATE TRUSTEE ESTABLISHMENT
- text: Scarabaeus Active Fund
- text: Spectrum Alternative Assets SICAV - Spectrum Growth Fund
- text: The Gani (IOM) Trust
- text: FONDECTA Trust Reg.
- text: M&N Holding GmbH
- text: LGT Select Equity Enhanced Minimum Variance
- text: HEC GmbH & Co. KG
- text: Liechtenstein-Institut
- text: HECTOR PLAST SE
- text: Liechtensteiner Milchverband eingetragene Genossenschaft
- text: Markus Haas MHS Makler Büro
library_name: transformers
tags: []
model-index:
- name: Sociovestix/lenu_LI
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: lenu
type: Sociovestix/lenu
config: LI
split: test
revision: f4d57b8d77a49ec5c62d899c9a213d23cd9f9428
metrics:
- type: f1
value: 0.9451453647833242
name: f1
- type: f1
value: 0.8044260987610308
name: f1 macro
args:
average: macro
LENU - Legal Entity Name Understanding for Liechtenstein
A Bert (multilingual uncased) model fine-tuned on Liechtenstein entity names (jurisdiction LI) 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 Liechtenstein legal entities and ELF Codes within the Jurisdiction "LI".
- 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.