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--- |
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model-index: |
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- name: Sociovestix/lenu_PL |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: lenu |
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type: Sociovestix/lenu |
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config: PL |
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split: test |
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revision: f4d57b8d77a49ec5c62d899c9a213d23cd9f9428 |
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metrics: |
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- type: f1 |
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value: 0.9930020993701889 |
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name: f1 |
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- type: f1 |
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value: 0.6630198501925706 |
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name: f1 macro |
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args: |
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average: macro |
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widget: |
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- text: "INSTYTUT DIABETOLOGII SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ" |
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- text: '"METAL-SYSTEM" OGRODZENIA - SCHODY SŁAWOMIR BINKOWSKI' |
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- text: "GERLACH S.A." |
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- text: "EMU SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ SPÓŁKA KOMANDYTOWA" |
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- text: "JEREMIE SEED CAPITAL WOJEWÓDZTWA POMORSKIEGO FUNDUSZ INWESTYCYJNY ZAMKNIĘTY W LIKWIDACJI" |
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- text: "MIASTO BIELSKO-BIAŁA" |
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- text: 'MARKETING" KRYSTIAN GDOWKA, ARTUR OSTRĘGA SPÓŁKA JAWNA' |
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- text: "Bank Spółdzielczy w Poddębicach" |
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- text: 'Fundacja Dzieciom "POMAGAJ"' |
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- text: "KANCELARIA RADCÓW PRAWNYCH BRUDKIEWICZ, SUCHECKA SPÓŁKA KOMANDYTOWO-AKCYJNA" |
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- text: "AKADEMIA MARYNARKI WOJENNEJ IM. BOHATERÓW WESTERPLATTE" |
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- text: "ZGROMADZENIE SIÓSTR URSZULANEK UNII RZYMSKIEJ DOM ZAKONNY" |
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- text: "STOWARZYSZENIE AUTORÓW ZAIKS" |
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- text: "SKAT TRANSPORT PROSTA SPÓŁKA AKCYJNA" |
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- text: "Nationale-Nederlanden Dobrowolny Fundusz Emerytalny Nasze Jutro 2055" |
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- text: "STORY HOUSE EGMONT SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ" |
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- text: "Narodowy Fundusz Ochrony Środowiska i Gospodarki Wodnej" |
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- text: 'ORGANIZACJA ZAKŁADOWA NSZZ "SOLIDARNOŚĆ" NR 3395 W T-MOBILE POLSKA S.A.' |
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- text: "CI GAMES SPÓŁKA EUROPEJSKA" |
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- text: "PPK Pocztylion 2040 Dobrowolny Fundusz Emerytalny" |
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- text: "TOWARZYSTWO UBEZPIECZEŃ WZAJEMNYCH POLSKI ZAKŁAD UBEZPIECZEŃ WZAJEMNYCH" |
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- text: "KABANEK JANINA POTORSKA ROBERT POTORSKI" |
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- text: "SPÓŁDZIELCZA KASA OSZCZĘDNOŚCIOWO-KREDYTOWA ENERGIA" |
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- text: "SZOSTEK_BAR I PARTNERZY KANCELARIA PRAWNA" |
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- text: "MIEJSKI ZARZĄD BUDYNKÓW MIESZKALNYCH" |
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- text: "IZBA ADWOKACKA W KATOWICACH" |
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- text: '1. Niepubliczny Specjalistyczny Zakład Opieki Zdrowotnej "LUNG" Krzysztof Garbino 2. Drukarnia "GARBINO"' |
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--- |
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# LENU - Legal Entity Name Understanding for Poland |
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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) |
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(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). |
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--------------- |
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<h1 align="center"> |
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<a href="https://gleif.org"> |
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<img src="http://sdglabs.ai/wp-content/uploads/2022/07/gleif-logo-new.png" width="220px" style="display: inherit"> |
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</a> |
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</h1><br> |
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<h3 align="center">in collaboration with</h3> |
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<h1 align="center"> |
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<a href="https://sociovestix.com"> |
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<img src="https://sociovestix.com/img/svl_logo_centered.svg" width="700px" style="width: 100%"> |
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</a> |
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</h1><br> |
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--------------- |
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## Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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The model has been created as part of a collaboration of the [Global Legal Entity Identifier Foundation](https://gleif.org) (GLEIF) and |
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[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. |
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See also the open source python library [lenu](https://github.com/Sociovestix/lenu), which supports in this task. |
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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". |
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- **Developed by:** [GLEIF](https://gleif.org) and [Sociovestix Labs](https://huggingface.co/Sociovestix) |
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- **License:** Creative Commons (CC0) license |
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- **Finetuned from model [optional]:** dkleczek/bert-base-polish-uncased-v1 |
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- **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-) |
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# Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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An entity's legal form is a crucial component when verifying and screening organizational identity. |
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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. |
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The Jurisdiction specific models of [lenu](https://github.com/Sociovestix/lenu), trained on entities from |
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GLEIF’s Legal Entity Identifier (LEI) database of over two million records, will allow banks, |
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investment firms, corporations, governments, and other large organizations to retrospectively analyze |
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their master data, extract the legal form from the unstructured text of the legal name and |
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uniformly apply an ELF code to each entity type, according to the ISO 20275 standard. |
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# Licensing Information |
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This model, which is trained on LEI data, is available under Creative Commons (CC0) license. |
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See [gleif.org/en/about/open-data](https://gleif.org/en/about/open-data). |
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# Recommendations |
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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. |
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