lenu_PL / README.md
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---
model-index:
- name: Sociovestix/lenu_PL
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: lenu
type: Sociovestix/lenu
config: PL
split: test
revision: f4d57b8d77a49ec5c62d899c9a213d23cd9f9428
metrics:
- type: f1
value: 0.9930020993701889
name: f1
- type: f1
value: 0.6630198501925706
name: f1 macro
args:
average: macro
widget:
- text: "INSTYTUT DIABETOLOGII SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ"
- text: '"METAL-SYSTEM" OGRODZENIA - SCHODY SŁAWOMIR BINKOWSKI'
- text: "GERLACH S.A."
- text: "EMU SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ SPÓŁKA KOMANDYTOWA"
- text: "JEREMIE SEED CAPITAL WOJEWÓDZTWA POMORSKIEGO FUNDUSZ INWESTYCYJNY ZAMKNIĘTY W LIKWIDACJI"
- text: "MIASTO BIELSKO-BIAŁA"
- text: 'MARKETING" KRYSTIAN GDOWKA, ARTUR OSTRĘGA SPÓŁKA JAWNA'
- text: "Bank Spółdzielczy w Poddębicach"
- text: 'Fundacja Dzieciom "POMAGAJ"'
- text: "KANCELARIA RADCÓW PRAWNYCH BRUDKIEWICZ, SUCHECKA SPÓŁKA KOMANDYTOWO-AKCYJNA"
- text: "AKADEMIA MARYNARKI WOJENNEJ IM. BOHATERÓW WESTERPLATTE"
- text: "ZGROMADZENIE SIÓSTR URSZULANEK UNII RZYMSKIEJ DOM ZAKONNY"
- text: "STOWARZYSZENIE AUTORÓW ZAIKS"
- text: "SKAT TRANSPORT PROSTA SPÓŁKA AKCYJNA"
- text: "Nationale-Nederlanden Dobrowolny Fundusz Emerytalny Nasze Jutro 2055"
- text: "STORY HOUSE EGMONT SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ"
- text: "Narodowy Fundusz Ochrony Środowiska i Gospodarki Wodnej"
- text: 'ORGANIZACJA ZAKŁADOWA NSZZ "SOLIDARNOŚĆ" NR 3395 W T-MOBILE POLSKA S.A.'
- text: "CI GAMES SPÓŁKA EUROPEJSKA"
- text: "PPK Pocztylion 2040 Dobrowolny Fundusz Emerytalny"
- text: "TOWARZYSTWO UBEZPIECZEŃ WZAJEMNYCH POLSKI ZAKŁAD UBEZPIECZEŃ WZAJEMNYCH"
- text: "KABANEK JANINA POTORSKA ROBERT POTORSKI"
- text: "SPÓŁDZIELCZA KASA OSZCZĘDNOŚCIOWO-KREDYTOWA ENERGIA"
- text: "SZOSTEK_BAR I PARTNERZY KANCELARIA PRAWNA"
- text: "MIEJSKI ZARZĄD BUDYNKÓW MIESZKALNYCH"
- text: "IZBA ADWOKACKA W KATOWICACH"
- text: '1. Niepubliczny Specjalistyczny Zakład Opieki Zdrowotnej "LUNG" Krzysztof Garbino 2. Drukarnia "GARBINO"'
---
# LENU - Legal Entity Name Understanding for Poland
A Polish Bert (uncased) model fine-tuned on Polish legal entity names (jurisdiction PL) from the Global [Legal Entity Identifier](https://www.gleif.org/en/about-lei/introducing-the-legal-entity-identifier-lei)
(LEI) System with the goal to detect [Entity Legal Form (ELF) Codes](https://www.gleif.org/en/about-lei/code-lists/iso-20275-entity-legal-forms-code-list).
---------------
<h1 align="center">
<a href="https://gleif.org">
<img src="http://sdglabs.ai/wp-content/uploads/2022/07/gleif-logo-new.png" width="220px" style="display: inherit">
</a>
</h1><br>
<h3 align="center">in collaboration with</h3>
<h1 align="center">
<a href="https://sociovestix.com">
<img src="https://sociovestix.com/img/svl_logo_centered.svg" width="700px" style="width: 100%">
</a>
</h1><br>
---------------
## Model Description
<!-- Provide a longer summary of what this model is. -->
The model has been created as part of a collaboration of the [Global Legal Entity Identifier Foundation](https://gleif.org) (GLEIF) and
[Sociovestix Labs](https://sociovestix.com) 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](https://github.com/Sociovestix/lenu), which supports in this task.
The model has been trained on the dataset [lenu](https://huggingface.co/datasets/Sociovestix), with a focus on polish legal entities and ELF Codes within the Jurisdiction "PL".
- **Developed by:** [GLEIF](https://gleif.org) and [Sociovestix Labs](https://huggingface.co/Sociovestix)
- **License:** Creative Commons (CC0) license
- **Finetuned from model [optional]:** dkleczek/bert-base-polish-uncased-v1
- **Resources for more information:** [Press Release](https://www.gleif.org/en/newsroom/press-releases/machine-learning-new-open-source-tool-developed-by-gleif-and-sociovestix-labs-enables-organizations-everywhere-to-automatically-)
# Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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](https://github.com/Sociovestix/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](https://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.