Findings of the Shared Task on Multilingual Coreference Resolution

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10457094" target="_blank" >RIV/00216208:11320/22:10457094 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/49777513:23520/22:43965918

Výsledek na webu

<a href="https://aclanthology.org/2022.crac-mcr.1/" target="_blank" >https://aclanthology.org/2022.crac-mcr.1/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Findings of the Shared Task on Multilingual Coreference Resolution

Popis výsledku v původním jazyce

This paper presents an overview of the shared task on multilingual coreference resolution associated with the CRAC 2022 workshop. Shared task participants were supposed to develop trainable systems capable of identifying mentions and of clustering the mentions according to identity coreference. The public edition of CorefUD 1.0, which contains 13 datasets for 10 languages was used as the source of training and evaluation data. The CoNLL score used in previous coreference-oriented shared tasks was used as the main evaluation metric. There were 8 coreference prediction systems submitted by 5 participating teams; in addition, there was a competitive transformer-based baseline system provided by the organizers at the beginning of the shared task. The winner system outperformed the baseline by 12 percent points (in terms of the CoNLL scores averaged across all datasets for individual languages).

Název v anglickém jazyce

Findings of the Shared Task on Multilingual Coreference Resolution

Popis výsledku anglicky

This paper presents an overview of the shared task on multilingual coreference resolution associated with the CRAC 2022 workshop. Shared task participants were supposed to develop trainable systems capable of identifying mentions and of clustering the mentions according to identity coreference. The public edition of CorefUD 1.0, which contains 13 datasets for 10 languages was used as the source of training and evaluation data. The CoNLL score used in previous coreference-oriented shared tasks was used as the main evaluation metric. There were 8 coreference prediction systems submitted by 5 participating teams; in addition, there was a competitive transformer-based baseline system provided by the organizers at the beginning of the shared task. The winner system outperformed the baseline by 12 percent points (in terms of the CoNLL scores averaged across all datasets for individual languages).

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

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

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

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