Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AFXPXP2RV" target="_blank" >RIV/00216208:11320/23:FXPXP2RV - isvavai.cz</a>

Result on the web

<a href="http://arxiv.org/abs/2311.09122" target="_blank" >http://arxiv.org/abs/2311.09122</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark

Original language description

"We introduce Universal NER (UNER), an open, community-driven project to develop gold-standard NER benchmarks in many languages. The overarching goal of UNER is to provide high-quality, cross-lingually consistent annotations to facilitate and standardize multilingual NER research. UNER v1 contains 18 datasets annotated with named entities in a cross-lingual consistent schema across 12 diverse languages. In this paper, we detail the dataset creation and composition of UNER; we also provide initial modeling baselines on both in-language and cross-lingual learning settings. We release the data, code, and fitted models to the public."

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů