TY - JOUR AU - Kim, Yejin AU - Kim, Yekyung PY - 2021/04/18 Y2 - 2024/03/29 TI - Learning Sub-Character level representation for Korean Named Entity Recognition JF - The International FLAIRS Conference Proceedings JA - FLAIRS VL - 34 IS - 0 SE - Special Track: Applied Natural Language Processing DO - 10.32473/flairs.v34i1.128509 UR - https://journals.flvc.org/FLAIRS/article/view/128509 SP - AB - <div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>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.</p></div></div></div> ER -