| | --- |
| | 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](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="https://www.gleif.org/assets/build/img/logo/gleif-logo-new.svg" 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://www.sociovestix.com/img/svl_logo.png" width="450px" style="width: 75%"> |
| | </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 czech legal entities and ELF Codes within the Jurisdiction "CZ". |
| |
|
| | - **Developed by:** [GLEIF](https://gleif.org) and [Sociovestix Labs](https://huggingface.co/Sociovestix) |
| | - **License:** Creative Commons (CC0) license |
| | - **Finetuned from model [optional]:** bert-base-multilingual-uncased |
| | - **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. |
