UkraiNER: A New Corpus and Annotation Scheme Towards Comprehensive Entity Recognition

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AAJNW2MLV" target="_blank" >RIV/00216208:11320/25:AJNW2MLV - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195968083&partnerID=40&md5=f137210b16c92b9d973b83933fe54cdb" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195968083&partnerID=40&md5=f137210b16c92b9d973b83933fe54cdb</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

UkraiNER: A New Corpus and Annotation Scheme Towards Comprehensive Entity Recognition

Original language description

Named entity recognition as it is traditionally envisioned excludes in practice a significant part of the entities of potential interest for real-word applications: nested, discontinuous, non-named entities. Despite various attempts to broaden their coverage, subsequent annotation schemes have achieved little adoption in the literature and the most restrictive variant of NER remains the default. This is partly due to the complexity of those annotations and their format. In this paper, we introduce a new annotation scheme that offers higher comprehensiveness while preserving simplicity, together with an annotation tool to implement that scheme. We also release the corpus UkraiNER, comprised of 10,000 French sentences in the geopolitical news domain and manually annotated with comprehensive entity recognition. Our baseline experiments on UkraiNER provide a first point of comparison to facilitate future research (82 F1 for comprehensive entity recognition, 87 F1 when focusing on traditional nested NER), as well as various insights on the composition and challenges that this corpus presents for state-of-the-art named entity recognition models. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Czech name

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Czech description

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Type

D - Article in proceedings

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

2024

Confidentiality

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

Article name in the collection

Jt. Int. Conf. Comput. Linguist., Lang. Resour. Eval., LREC-COLING - Main Conf. Proc.

ISBN

978-249381410-4

ISSN

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e-ISSN

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Number of pages

12

Pages from-to

16941-16952

Publisher name

European Language Resources Association (ELRA)

Place of publication

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Event location

Torino, Italia

Event date

Jan 1, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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