Learning Sub-Character level representation for Korean Named Entity Recognition

Authors

  • Yejin Kim LG Electronics
  • Yekyung Kim

DOI:

https://doi.org/10.32473/flairs.v34i1.128509

Abstract

Most of the previous studies on the Korean Named Entity Recognition (NER) topic focused on utilizing morphological-level information because the language is rich in character diversity. This paper illustrates an improved unigram-level Korean NER model with sub-character level representation, jamo, which can represent a unique linguistic structure of Korean and its syntactic properties and morphological variations. The experimental result shows that exploiting sub-character gives us a boost of + (avg) 2 F1, also, our proposed C-GRAM model outperformed about 3 F1 comparing with the baseline.

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Published

2021-04-18

How to Cite

Kim, Y., & Kim, Y. (2021). Learning Sub-Character level representation for Korean Named Entity Recognition. The International FLAIRS Conference Proceedings, 34. https://doi.org/10.32473/flairs.v34i1.128509

Issue

Section

Special Track: Applied Natural Language Processing