Abstract
We introduce the AIP-Tohoku grammatical error correction (GEC) system for the BEA-2019 shared task in Track 1 (Restricted Track) and Track 2 (Unrestricted Track) using the same system architecture. Our system comprises two key components: error generation and sentence-level error detection. In particular, GEC with sentence-level grammatical error detection is a novel and versatile approach, and we experimentally demonstrate that it significantly improves the precision of the base model. Our system is ranked 9th in Track 1 and 2nd in Track 2.- Anthology ID:
- W19-4418
- Volume:
- Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Helen Yannakoudakis, Ekaterina Kochmar, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Torsten Zesch
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 176–182
- Language:
- URL:
- https://aclanthology.org/W19-4418
- DOI:
- 10.18653/v1/W19-4418
- Cite (ACL):
- Hiroki Asano, Masato Mita, Tomoya Mizumoto, and Jun Suzuki. 2019. The AIP-Tohoku System at the BEA-2019 Shared Task. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 176–182, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- The AIP-Tohoku System at the BEA-2019 Shared Task (Asano et al., BEA 2019)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/W19-4418.pdf