UA-KO at SemEval-2022 Task 11: Data Augmentation and Ensembles for Korean Named Entity Recognition

Hyunju Song, Steven Bethard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper presents the approaches and systems of the UA-KO team for the Korean portion of SemEval-2022 Task 11 on Multilingual Complex Named Entity Recognition. We fine-tuned Korean and multilingual BERT and RoBERTA models, conducted experiments on data augmentation, ensembles, and task-adaptive pretraining. Our final system ranked 8th out of 17 teams with an F1 score of 0.6749 F1.

Original languageEnglish (US)
Title of host publicationSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop
EditorsGuy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
PublisherAssociation for Computational Linguistics (ACL)
Pages1608-1612
Number of pages5
ISBN (Electronic)9781955917803
StatePublished - 2022
Event16th International Workshop on Semantic Evaluation, SemEval 2022 - Seattle, United States
Duration: Jul 14 2022Jul 15 2022

Publication series

NameSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop

Conference

Conference16th International Workshop on Semantic Evaluation, SemEval 2022
Country/TerritoryUnited States
CitySeattle
Period7/14/227/15/22

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Theoretical Computer Science

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