--- widget: - text: CHF Capital SA - text: Fondation de Technocorp Holding S.A. - text: PICTET CH INSTITUTIONAL - SWISS EQUITIES TRACKER - text: Tin Ventures GmbH - text: The Trustee of the Michael Warshaw Trust - text: Format Aktien Schweiz mittlere und kleinere Firmen - text: Raiffeisenbank Leimental Genossenschaft - text: Alliance universelle des Unions chrétiennes de jeunes gens - text: Luzerner Pensionskasse (LUPK) - text: Armin Biehler - text: inosens ag - text: Wecken & Cie. - text: Kanton Zürich - text: CAMET KlG - text: Commune de Anières - text: STWEG Hinter Chilen 1-12 - text: Spital Limmattal - text: Ausgleichskasse des Kantons Appenzell A. Rh. - text: World Trade Organization (WTO Pension Plan) - text: Pensionskasse der Stadt Olten - text: THE MACE TRUST - text: Elips Life AG, Vaduz, Zweigniederlassung Schweiz in Zürich - text: Mirabaud (CH) - LPP25+ - text: Confédération suisse model-index: - name: Sociovestix/lenu_CH results: - task: type: text-classification name: Text Classification dataset: name: lenu type: Sociovestix/lenu config: CH split: test revision: f4d57b8d77a49ec5c62d899c9a213d23cd9f9428 metrics: - type: f1 value: 0.9514824797843666 name: f1 - type: f1 value: 0.5094035486191425 name: f1 macro args: average: macro --- # LENU - Legal Entity Name Understanding for Switzerland A Bert (multilingual uncased) model fine-tuned on swiss legal entity names (jurisdiction CH) 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). ---------------


in collaboration with


--------------- ## Model Description 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 swiss legal entities and ELF Codes within the Jurisdiction "CH". - **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 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.