The Effect of Alignment Correction on Cross-Lingual Annotation Projection
Shabnam Behzad, Seth Ebner, Marc Marone, Benjamin Van Durme, Mahsa Yarmohammadi
Abstract
Cross-lingual annotation projection is a practical method for improving performance on low resource structured prediction tasks. An important step in annotation projection is obtaining alignments between the source and target texts, which enables the mapping of annotations across the texts. By manually correcting automatically generated alignments, we examine the impact of alignment quality—automatic, manual, and mixed—on downstream performance for two information extraction tasks and quantify the trade-off between annotation effort and model performance.- Anthology ID:
- 2023.law-1.24
- Volume:
- Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Jakob Prange, Annemarie Friedrich
- Venue:
- LAW
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 244–251
- Language:
- URL:
- https://aclanthology.org/2023.law-1.24
- DOI:
- 10.18653/v1/2023.law-1.24
- Cite (ACL):
- Shabnam Behzad, Seth Ebner, Marc Marone, Benjamin Van Durme, and Mahsa Yarmohammadi. 2023. The Effect of Alignment Correction on Cross-Lingual Annotation Projection. In Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII), pages 244–251, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- The Effect of Alignment Correction on Cross-Lingual Annotation Projection (Behzad et al., LAW 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.law-1.24.pdf