# UKTA: Unified Korean Text Analyzer

arXiv: https://arxiv.org/abs/2502.09648 · HTML: https://mlsanity.com/paper/2502.09648/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 36 references that are in the map.
- First posted on arXiv 11 Feb 2025.

## Builds on (most cited first, 4 of 4)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [On the Use of BERT for Automated Essay Scoring: Joint Learning of Multi-Scale Essay Representation](https://mlsanity.com/paper/2205.03835/) (2022)
- [Rich Character-Level Information for Korean Morphological Analysis and Part-of-Speech Tagging](https://mlsanity.com/paper/1806.10771/) (2018)
- [Sentence Similarity Measures for Fine-Grained Estimation of Topical Relevance in Learner Essays](https://mlsanity.com/paper/1606.03144/) (2016)

## Abstract (arXiv)

Evaluating writing quality is complex and time-consuming often delaying feedback to learners. While automated writing evaluation tools are effective for English, Korean automated writing evaluation tools face challenges due to their inability to address multi-view analysis, error propagation, and evaluation explainability. To overcome these challenges, we introduce UKTA (Unified Korean Text Analyzer), a comprehensive Korea text analysis and writing evaluation system. UKTA provides accurate low-level morpheme analysis, key lexical features for mid-level explainability, and transparent high-level rubric-based writing scores. Our approach enhances accuracy and quadratic weighted kappa over existing baseline, positioning UKTA as a leading multi-perspective tool for Korean text analysis and writing evaluation.