Abstract
Previous research on Korean FrameNet has produced several datasets that serve as resources for FrameNet parsing in Korean. However, these datasets suffer from the problem that annotations are assigned on the word level, which is not optimally designed based on the agglutinative feature of Korean. To address this issue, we introduce a morphologically enhanced annotation strategy for Korean FrameNet datasets and parsing by leveraging the CoNLL-U format. We present the results of the FrameNet parsers trained on the Korean FrameNet data in the original format and our proposed format, respectively, and further elaborate on the linguistic rationales of our proposed scheme. We suggest the morpheme-based scheme to be the standard of Korean FrameNet data annotation.- Anthology ID:
- 2024.lrec-main.1447
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 16653–16658
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.1447
- DOI:
- Cite (ACL):
- Yige Chen, Jae Ihn, KyungTae Lim, and Jungyeul Park. 2024. Towards Standardized Annotation and Parsing for Korean FrameNet. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 16653–16658, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Towards Standardized Annotation and Parsing for Korean FrameNet (Chen et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.1447.pdf