Abstract
Aspect is a valuable tool for determining the perspective from which an event is observed, allowing for viewing both at the situation and viewpoint level. Uniform Meaning Representation (UMR) seeks to provide a standard, typologically-informed representation of aspects across languages. It employs an aspectual lattice to adapt to different languages and design values that encompass both viewpoint aspect and situation aspects. In the context of annotating the Chinese version of The Little Prince, we paid particular attention to the interactions between aspect values and aspect markers and we also want to know the annotation effectiveness and challenges under the UMR aspectual lattice. During our annotation process, we identified the relationships between aspectual markers and labels. We further categorized and analyzed complex examples that led to low inter-annotator agreement. The factors contributing to disagreement among annotators included the interpretations of lexical semantics, implications, and the influence of aspectual markers, which is related to the inclination of the situation aspect and the exclusivity between the two aspects’ perspectives. Overall, our work sheds light on the challenges of aspect annotation in Chinese and highlights the need for more comprehensive guidelines.- Anthology ID:
- 2024.lrec-main.104
- 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:
- 1161–1172
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.104
- DOI:
- Cite (ACL):
- Sijia Ge, Zilong Li, Alvin Po-Chun Chen, and Guanchao Wang. 2024. Annotate Chinese Aspect with UMR——a Case Study on the Liitle Prince. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 1161–1172, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Annotate Chinese Aspect with UMR——a Case Study on the Liitle Prince (Ge et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2024.lrec-main.104.pdf