Sentence Segmentation and Punctuation for Ancient Books Based on Supervised In-context Training
Shiquan Wang, Weiwei Fu, Mengxiang Li, Zhongjiang He, Yongxiang Li, Ruiyu Fang, Li Guan, Shuangyong Song
Abstract
This paper describes the participation of team “TeleAI” in the third International Chinese Ancient Chinese Language Information Processing Evaluation (EvalHan24). The competition comprises a joint task of sentence segmentation and punctuation, categorized into open and closed tracks based on the models and data used. In the final evaluation, our system achieved significantly better results than the baseline. Specifically, in the closed-track sentence segmentation task, we obtained an F1 score of 0.8885, while in the sentence punctuation task, we achieved an F1 score of 0.7129.- Anthology ID:
- 2024.lt4hala-1.31
- Volume:
- Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Rachele Sprugnoli, Marco Passarotti
- Venues:
- LT4HALA | WS
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 251–255
- Language:
- URL:
- https://aclanthology.org/2024.lt4hala-1.31
- DOI:
- Cite (ACL):
- Shiquan Wang, Weiwei Fu, Mengxiang Li, Zhongjiang He, Yongxiang Li, Ruiyu Fang, Li Guan, and Shuangyong Song. 2024. Sentence Segmentation and Punctuation for Ancient Books Based on Supervised In-context Training. In Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024, pages 251–255, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Sentence Segmentation and Punctuation for Ancient Books Based on Supervised In-context Training (Wang et al., LT4HALA-WS 2024)
- PDF:
- https://preview.aclanthology.org/landing_page/2024.lt4hala-1.31.pdf