# A Sub-Character Architecture for Korean Language Processing

arXiv: https://arxiv.org/abs/1707.06341 · HTML: https://mlsanity.com/paper/1707.06341/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jul 2017.

## Built on by (most cited first, 5 of 5)

- [The Impact of Visual Information in Chinese Characters: Evaluating Large Models' Ability to Recognize and Utilize Radicals](https://mlsanity.com/paper/2410.09013/) (2024)
- [A Survey on Awesome Korean NLP Datasets](https://mlsanity.com/paper/2112.01624/) (2021)
- [Word Segmentation for Asian Languages: Chinese, Korean, and Japanese](https://mlsanity.com/paper/2407.19400/) (2024)
- [An Empirical Study on Chinese Character Decomposition in Multiword Expression-Aware Neural Machine Translation](https://mlsanity.com/paper/2512.15556/) (2025)
- [KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacters](https://mlsanity.com/paper/2604.23948/) (2026)

## Abstract (arXiv)

We introduce a novel sub-character architecture that exploits a unique compositional structure of the Korean language. Our method decomposes each character into a small set of primitive phonetic units called jamo letters from which character- and word-level representations are induced. The jamo letters divulge syntactic and semantic information that is difficult to access with conventional character-level units. They greatly alleviate the data sparsity problem, reducing the observation space to 1.6% of the original while increasing accuracy in our experiments. We apply our architecture to dependency parsing and achieve dramatic improvement over strong lexical baselines.