## 5 Discussion
### Copying Mechanism  
The restoration process is the first stage in the KMAP task. This is an important step that strongly affects the performance of the following stages, which are segmentation and tagging. As we mentioned in Section 3.3, 94.9% of the syllables were unchanged during the restoration process because most syllables or characters are not the targets of the restoration. These include non-Korean characters, such as numerical, English, Chinese, and special-symbol characters, which can be easily identified by their character codes.  
We adopted a copying mechanism [41; 42; 43] to ensure they remained unchanged during not just the restoration process but also the segmentation and tagging processes. An ablation  
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline \multirow{2}{*}{**Authors**} & \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Approach**} & \multicolumn{2}{c}{**Data (K sents.)**} & \multicolumn{2}{c}{**Tagging Performance**} \\ \cline{5-8}  & & & **Training/Test** & **Syllable** & **Morpheme** & **Eojeol**ol \\ \hline [PERSON], 2013 [10] & CRF & CTag & Konan 33/3 \({}^{*}\) & 97.99 & - & **96.47** \\ \hline [PERSON], 2013 [18] & Structural SVM & CTag & Sejong 133/13 \({}^{*}\) & - & 96.99 & - \\ \hline [PERSON] et al., 2016 [19] & Structural SVM & CTag & Sejong 56/6 \({}^{*}\) & - & - & 96.41 \({}^{\lx@sectionsign}\) \\ \hline [PERSON] et al., 2017 [23] & GRU & S2S & Sejong 90/10 & - & 97.27 & 95.28 \\ \hline [PERSON] et al., 2019 [11] & BERT + BiLSTM + CRF & CTag & Sejong 753/9 & - & **98.74** & - \\ \hline [PERSON] et al., 2016 [33] & BiLSTM + CRF & IGen & Sejong 783/87 & - & - & 94.89 \\ \hline [PERSON] and [PERSON], 2017 [22] & Lattice + HMM & S2S & Sejong 200/50 & - & 96.49 & 94.77 \\ \hline [PERSON] et al., 2018 [34] & BiLSTM + CRF & IGen & Sejong 807/43 & - & - & 96.20 \({}^{\dagger}\) \\ \hline [PERSON] et al., 2019 [26] & BERT + BiLSTM & CTag \({}^{\ddagger}\) & Sejong 200/50 & - & 95.22 & 93.90 \\ \hline [PERSON] and [PERSON], 2019 [24] & BiLSTM + LSTM + PGN + CRF & S2S & Sejong 200/50 & - & 97.43 & 95.68 \\ \hline [PERSON] and [PERSON], 2020 [25] & BiLSTM + CRF & Gen & Sejong 200/50 & - & 97.27 & 95.28 \\ \hline [PERSON] and [PERSON], 2021 [28] & BiLSTM + CRF + Conv. & S2S & Sejong 200/50 & - & 98.07 & 95.92 \\ \hline [PERSON] and [PERSON], 2022 [29] & Transformer(EnDe) + CRF & IGen & Sejong 200/50 & - & 97.59 & 95.83 \\ \hline Proposed & Transformer(En) + BiLSTM & MTag & Sejong 769/87 & **98.41**\(\pm\) 0.02 & 97.74 \(\pm\) 0.02 & 96.12 \(\pm\) 0.03 \\ \hline \hline \end{tabular}  
* Estimated from the original number of eojeols (calculated using 12 eojeols per sentence). \({}^{\lx@sectionsign}\) Accuracy without using a pre-analyzed dictionary. \({}^{\ddagger}\) Accuracy for correctly annotated test data. \({}^{\ddagger}\) Subwords were used instead of syllables as the annotation units.  
\end{table}
Table 7: Performance comparison with previous work (morpheme F1, syllable, and eojeol accuracy, %).  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Approaches** & **Avg. eojeol acc.** & **End-to-End** & **n-to-n** & **Pipeline** & **n-to-m** \\ \hline MTag & 96.12 & ✓ & ✓ & & \\ \hline IGEN & 95.54 & & ✓ & ✓ & \\ \hline S2S & 95.46 & ✓ & & & ✓ \\ \hline GEN & 95.28 & & ✓ & ✓ & ✓ \\ \hline \hline \end{tabular}
\end{table}
Table 8: Performance comparison of architectures.  
test showed that the copying mechanism improved the F1-score performance of the POS tagging per cojeol by 0.03% points.